Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
Gli open data nella “città intelligente”Paolo Nesi
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
Thanks to the European Commission for founding. All slides reporting logo of RESOLUTE H2020 are representing tools and research founded by European Commission for the RESOLUTE project. RESOLUTE has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 653460).
Thanks to the European Commission for founding. All slides reporting logo of REPLICATE H2020 are representing tools and research founded by European Commission for the REPLICATE project. REPLICATE has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 691735).
Thanks to the MIUR for co-fouding and to the University of Florence and companies involved. All slides reporting logo of Sii-Mobility are representing tools and research founded by MIUR for the Sii-Mobility SCN MIUR project.
Thanks to the European Commission for founding. All slides reporting logo of Snap4City https://www.snap4city.org of Select4Cities H2020 are representing tools and research founded by European Commission for the Select4Cities project. Select4Cities has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 688196)
Km4City is an open technology exploited by those projects and line of research of DISIT Lab. Some of the innovative solutions and research issues developed into the above mentioned projects are also compliant and contributing to the Km4City approach and thus are contributing to the open Km4City model of DISIT lab.
Snap4City a Solution for highly collaborative Smart Cities Environments Paolo Nesi
Snap4City has been created in response to Select4Cities PCP (http://www.select4cities.eu/) call as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp. Snap4City is a fully open source, robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, extending the powerful semantic reasoner of Km4City https://www.km4city.org, with IOT/IOE, GDPR, and city dashboards. Snap4City (Https://www.snap4city.org ) is a solution for setting up Living Labs engaging different all kinds of stakeholders (city operators, researchers, city users, in house, industries) in contributing to the city evolutions, with a platform providing online tools for developing IOT applications, web and mobile Apps, data analytics, micro Applications, external services, KPI, POI, dashboards, IOT edge, etc.
Snap4City/Km4City has been validated in multiple devices (PC, Android, Raspberry, IOT Button, Arduino, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and millions of data per day. The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, end-2-end encrypted secure communications, GDPR, .. thus setting up in a Snap smart city solutions.
The document describes the DISIT Lab and its work on smart city projects using big data and analytics to provide services for cities using an open data platform and API called Km4City that integrates data from various sources including IoT sensors, open data, social media, and more to power applications for transportation, environment, health and other domains to improve city operations and services for residents.
The data!
Services from Data via Smart City API
IOT Applications and IOT
Personal Data vs Open
Big Data Analytics
App as data collection and User Engagement
Social Media Analysis
Visual Analytics and Dashboards
The Living Lab Approach
Km4City: una soluzione aperta per erogare servizi Smart CityPaolo Nesi
Km4City: Integrated Urban Platform, Open Source
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
Open Urban Platform for Smart City: Technical View Paolo Nesi
Km4City Roadmap
Data and Model
Control Room
Monitoring Traffic Flow and Parking
Monitoring City Users via Wi-Fi
Engaging Users Via Mobile App
Development Tools
Who is using it
City Resilience and DSS
Info and Documents
Open Data Day 2016, Km4City, L’universita’ come aggregatore di Open Data del ...Paolo Nesi
Open Data Day, UNIMORE, Modena, 5 Marzo 2016.
Aggregazione dati, experienza di Firenze,
Smart City, Km4City,
Smart Decision Support,
Data Ingestion manager,
Data aggregation,
User profiling on demand.
Mobilità: inter-modalità, bigliettazione integrata, sostenibile, scambiatori, sfruttamento stazioni, etc.,
Servizi: gov ..SUAP, edu, turismo, beni culturali, salute, etc.,
Energia: risparmio energetico, riduzione amissioni, inquinamento, etc.,
Ambiente: qualità dell’aria, fiumi, meteo, rifiuti, etc.,
… commercio, industria, etc.
... Infrastrutture critiche. resilienza
Collezionamento dati statici, quasi statici e real time, stream
Dati open: geo localizzati, servizi, statistiche, censimenti, etc.
Dati privati degli operatori: con licenze limitate per non permettere di fare profitto ad altri operatori sulla base dei loro dati
Dati personali delle persone: profili, comportamenti tramite APP, IOT, sensori, web, etc.
Integrazione dati per renderli semanticamente interoperabili, ed operare deduzioni (time, space… )
I tradizionali collettori di open data danno visioni statistiche ma non sono adatti a produrre servizi integrati
Integrazione con modelli semantici unificanti come Km4City
Control Room delle Città Metropolitane devono:
arrivare a supervisionare domini multipli e le interdipendenze fra mobilità, energia, comunicazione, servizi, flussi traffico, flussi pedonali, turismo, etc.
Migliorare la loro Resilienza, capacità di reazione ed assorbimento
ridurre i costi sociali della mobilità per le persone
consentendo minori disagi, maggiore efficienza,
maggiore sensibilità verso le necessità del cittadino,
minori emissioni, migliori condizioni ambientali;
percorsi info-formativi in modo che il cittadino cambi le abitudini non virtuose;
ridurre i costi di trasporto ed i tempi di percorrenza per gli utenti, per i gestori e le amministrazioni, tramite soluzioni di ottimizzazione.
Gli open data nella “città intelligente”Paolo Nesi
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
Thanks to the European Commission for founding. All slides reporting logo of RESOLUTE H2020 are representing tools and research founded by European Commission for the RESOLUTE project. RESOLUTE has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 653460).
Thanks to the European Commission for founding. All slides reporting logo of REPLICATE H2020 are representing tools and research founded by European Commission for the REPLICATE project. REPLICATE has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 691735).
Thanks to the MIUR for co-fouding and to the University of Florence and companies involved. All slides reporting logo of Sii-Mobility are representing tools and research founded by MIUR for the Sii-Mobility SCN MIUR project.
Thanks to the European Commission for founding. All slides reporting logo of Snap4City https://www.snap4city.org of Select4Cities H2020 are representing tools and research founded by European Commission for the Select4Cities project. Select4Cities has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 688196)
Km4City is an open technology exploited by those projects and line of research of DISIT Lab. Some of the innovative solutions and research issues developed into the above mentioned projects are also compliant and contributing to the Km4City approach and thus are contributing to the open Km4City model of DISIT lab.
Snap4City a Solution for highly collaborative Smart Cities Environments Paolo Nesi
Snap4City has been created in response to Select4Cities PCP (http://www.select4cities.eu/) call as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp. Snap4City is a fully open source, robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, extending the powerful semantic reasoner of Km4City https://www.km4city.org, with IOT/IOE, GDPR, and city dashboards. Snap4City (Https://www.snap4city.org ) is a solution for setting up Living Labs engaging different all kinds of stakeholders (city operators, researchers, city users, in house, industries) in contributing to the city evolutions, with a platform providing online tools for developing IOT applications, web and mobile Apps, data analytics, micro Applications, external services, KPI, POI, dashboards, IOT edge, etc.
Snap4City/Km4City has been validated in multiple devices (PC, Android, Raspberry, IOT Button, Arduino, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and millions of data per day. The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, end-2-end encrypted secure communications, GDPR, .. thus setting up in a Snap smart city solutions.
The document describes the DISIT Lab and its work on smart city projects using big data and analytics to provide services for cities using an open data platform and API called Km4City that integrates data from various sources including IoT sensors, open data, social media, and more to power applications for transportation, environment, health and other domains to improve city operations and services for residents.
The data!
Services from Data via Smart City API
IOT Applications and IOT
Personal Data vs Open
Big Data Analytics
App as data collection and User Engagement
Social Media Analysis
Visual Analytics and Dashboards
The Living Lab Approach
Km4City: una soluzione aperta per erogare servizi Smart CityPaolo Nesi
Km4City: Integrated Urban Platform, Open Source
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
Open Urban Platform for Smart City: Technical View Paolo Nesi
Km4City Roadmap
Data and Model
Control Room
Monitoring Traffic Flow and Parking
Monitoring City Users via Wi-Fi
Engaging Users Via Mobile App
Development Tools
Who is using it
City Resilience and DSS
Info and Documents
Open Data Day 2016, Km4City, L’universita’ come aggregatore di Open Data del ...Paolo Nesi
Open Data Day, UNIMORE, Modena, 5 Marzo 2016.
Aggregazione dati, experienza di Firenze,
Smart City, Km4City,
Smart Decision Support,
Data Ingestion manager,
Data aggregation,
User profiling on demand.
Mobilità: inter-modalità, bigliettazione integrata, sostenibile, scambiatori, sfruttamento stazioni, etc.,
Servizi: gov ..SUAP, edu, turismo, beni culturali, salute, etc.,
Energia: risparmio energetico, riduzione amissioni, inquinamento, etc.,
Ambiente: qualità dell’aria, fiumi, meteo, rifiuti, etc.,
… commercio, industria, etc.
... Infrastrutture critiche. resilienza
Collezionamento dati statici, quasi statici e real time, stream
Dati open: geo localizzati, servizi, statistiche, censimenti, etc.
Dati privati degli operatori: con licenze limitate per non permettere di fare profitto ad altri operatori sulla base dei loro dati
Dati personali delle persone: profili, comportamenti tramite APP, IOT, sensori, web, etc.
Integrazione dati per renderli semanticamente interoperabili, ed operare deduzioni (time, space… )
I tradizionali collettori di open data danno visioni statistiche ma non sono adatti a produrre servizi integrati
Integrazione con modelli semantici unificanti come Km4City
Control Room delle Città Metropolitane devono:
arrivare a supervisionare domini multipli e le interdipendenze fra mobilità, energia, comunicazione, servizi, flussi traffico, flussi pedonali, turismo, etc.
Migliorare la loro Resilienza, capacità di reazione ed assorbimento
ridurre i costi sociali della mobilità per le persone
consentendo minori disagi, maggiore efficienza,
maggiore sensibilità verso le necessità del cittadino,
minori emissioni, migliori condizioni ambientali;
percorsi info-formativi in modo che il cittadino cambi le abitudini non virtuose;
ridurre i costi di trasporto ed i tempi di percorrenza per gli utenti, per i gestori e le amministrazioni, tramite soluzioni di ottimizzazione.
Km4City: A reusable example of a Metropolitan-Wide Data Platform, MAJORCITIES...Paolo Nesi
This document describes Km4City, an open source smart city platform developed by DISIT Lab. It consists of tools to 1) keep cities under control via personalized dashboards, 2) improve city resilience through risk reduction and decision support, and 3) transform data into value for cities. The platform integrates data from various city systems and sensors to power applications for operators, decision makers, and citizens. It has been implemented in Florence and Tuscany to support projects like Sii-Mobility.
Km4city Smart City Ecosystem Urban PlatformPaolo Nesi
keep city under control via personalized dashboards
improve city resilience, reducing risks and decision support
transform data in value for the city
monitoring services’ status of city operators
Smart City Dashboards, http://dashboard.km4city.org Dashboard Builder
monitoring and understanding the city users behaviour
Recommender and User Behavior Analyzer, http://recommender.km4city.org
WiFi monitor, http://wifimap.km4city.org
Origin Destination matrix tools http://www.disit.org/6694
collecting moods, contributions and data from the city users
Collecting contributions: images, stars, comments and Social Media
monitoring social media for city services and events, event predictions
Twitter Vigilance, http://www.disit.org/tv , http://tvsolr.disit.org
assessing city resilience level
Resilience Decision Support, http://resilienceds.km4city.org
Smart decision support system, http://smartds.km4city.org
improving city resilience, providing objective hints
Resilience Decision Support implementing European Resilience Management Guidelines (ERMG) http://www.resolute-eu.org
improving city users awareness with personal city assistants and participatory tools
Dashboard: http://dashboard.km4city.org
Km4City Web App http://www.km4city.org
Km4City Mobile App: http://www.km4city.org/app
enabling commercial and business applications
decision support access
aggregating multi-domain data and services for SMEs and city operators
Data /Service Aggregator: open, flexible and suitable access
data aggregation and access Smart City API
integrated data and services, accessible as on demand basis
providing services for third party portals and Apps: geo-localized data and services, info, suggestions
suggestion on demand service for SMEs and city operators
Suggestion On Demand see above
Personal Assistance: information, engagement, soundage
development tool for fast and low cost implementation of business and service oriented Apps
Smart City API
Km4City, Smart City Urban Platform, From Data to Services for the Sentient Ci...Paolo Nesi
The document describes the Km4City Smart City Ecosystem project. Km4City aims to use data collected from smart city systems and citizens to 1) keep cities under control via personalized dashboards, 2) improve city resilience by reducing risks, and 3) transform data into value for cities. It provides open-source tools for monitoring services, user behavior, social media, and more. These tools help cities manage operations, understand users, and make data-driven decisions. The ecosystem is currently deployed in Florence, Italy.
DAI DATI INTELLIGENTI AI SERVIZI Smart City API HackathonPaolo Nesi
DAI DATI INTELLIGENTI AI SERVIZI
Smart City API Hackathon
Premi per 14.000 euro
Data: 7 e 8 aprile 2017
Luogo: Scuola di Ingegneria, Università degli Studi di Firenze
Il progetto Sii-Mobility, Smart City nazionale (MIUR), organizza il primo hackathon per promuovere lo sviluppo di applicazioni fisse e mobili sulla base delle http://www.disit.org/6991che si basano sul modello http://www.km4city.org .
Scopo dell'evento di hackathon è identificare nuove applicazioni che possano essere sviluppate sulla base di dati ed elaborazioni messi disposizione dalle smart city API di Sii-Mobility. I Dati sono in tutta la toscana e come dagli scenari http://www.disit.org/6995, sono relativi alla mobilità pubblica e privata, alla partecipazione, alle informazioni geolocalizzate dei punti di interesse, della salute, ambiente, e servizi di suggerimento e di coinvolgimento e assistenza.
Le tematiche affrontate dalle App proposte dovranno essere relative ad aspetti di mobilità, e in particolare ai seguenti 5 temi: Trasporto pubblico; Coinvolgimento dei cittadini, mobilità e turismo, mobilità e servizi, giochi in mobilità.
http://www.sii-mobility.org/index.php/eventi/hackathon-sii-mobility/registrati-all-evento-del-7-mattina
Documentazione e informazioni dalla pagina: http://www.sii-mobility.org/
Scadenza sottomissione delle proposte: 31 marzo 2017.
Premi per 14.000 euro, #hackathon #smartcity API, #bigdata #opendata della #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
#hackathon #smartcity #bigdata #opendata #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
Smart City API, 14.000 euro di premi, Hackathon
hackathon smart city API, dai dati ai serviziPaolo Nesi
DAI DATI INTELLIGENTI AI SERVIZI
Smart City API Hackathon
Premi per 14.000 euro
Data: 7 e 8 aprile 2017
Luogo: Scuola di Ingegneria, Università degli Studi di Firenze
Il progetto Sii-Mobility, Smart City nazionale (MIUR), organizza il primo hackathon per promuovere lo sviluppo di applicazioni fisse e mobili sulla base delle http://www.disit.org/6991che si basano sul modello http://www.km4city.org .
Scopo dell'evento di hackathon è identificare nuove applicazioni che possano essere sviluppate sulla base di dati ed elaborazioni messi disposizione dalle smart city API di Sii-Mobility. I Dati sono in tutta la toscana e come dagli scenari http://www.disit.org/6995, sono relativi alla mobilità pubblica e privata, alla partecipazione, alle informazioni geolocalizzate dei punti di interesse, della salute, ambiente, e servizi di suggerimento e di coinvolgimento e assistenza.
Le tematiche affrontate dalle App proposte dovranno essere relative ad aspetti di mobilità, e in particolare ai seguenti 5 temi: Trasporto pubblico; Coinvolgimento dei cittadini, mobilità e turismo, mobilità e servizi, giochi in mobilità.
http://www.sii-mobility.org/index.php/eventi/hackathon-sii-mobility/registrati-all-evento-del-7-mattina
Documentazione e informazioni dalla pagina: http://www.sii-mobility.org/
Scadenza sottomissione delle proposte: 31 marzo 2017.
Premi per 14.000 euro, #hackathon #smartcity API, #bigdata #opendata della #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
#hackathon #smartcity #bigdata #opendata #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
Smart City API, 14.000 euro di premi, Hackathon
Integrated infrastructure for urban platform in Florence Replicate project scc1Paolo Nesi
Integrated infrastructure for urban platform in Florence Replicate project scc1.
Aggregate & integrate data and streams of any urban system, operator,
provider, user, .., exploiting
– open data, IOT, sensors, internet of everything,
– cloud, mobile devices, Wi‐Fi, social media,
– big data analytics, ecc;
• Perform integrated and unified data management and data analytics by a set
of tools at service of city operators and city users, to:
– Control Room, Real Time Monitoring tools, ….
– Perform predictions, reasoning, business intelligence, city users behavior analysis
• Produce value from data enabling to
– Stimulate virtuous behavior, influence City Users!
– Increase efficiency in energy consumption
– Reduce pollution and traffic congestion
– Improve quality of service, quality of life
– Create an ecosystem for innovation and punt in action any smart city solutions
and services.
Km4city: Open Urban Platform for a Sentient Smart CityPaolo Nesi
1) Km4City is an open urban platform that aggregates data from IoT sensors and city services to create a smart city ecosystem.
2) The platform includes tools for real-time monitoring, data analytics, influencing citizen behavior, and transforming data into new smart city services.
3) Example tools include smart city dashboards, predictive models, mobile apps, and Twitter analysis to gain citizen input and assess sentiment.
Km4City: Smart City HowTo and Overview, 2016Paolo Nesi
Km4City storia e roadmap
Dati e Modello
Development Tools
App: Web e Mobile
Mobile reasoning and Monitoring
Monitoring via Wi-Fi
Control Room
Twitter Vigilance
Progetti Connessi
Set up an ICT based Urban Platform integrated and unified data management among services, city operators and city users:
Control Room, Real Time Monitoring
decision support, assessing and monitoring risk and resilience
Data analytics and business intelligence
predictions, reasoning, city users behavior analysis, ….
Reading the city: data, users behavior and needs, ...
IOT, Open data sensors, private data, static and real time data.
City Strategies: stimulate virtuous behavior of City Users
participation, totem, twitter, Apps, etc.
Transform Data into value
Put in action smart city innovative solutions and services, development tools
Smart City Strategic Forecast, SmartCity360, BratislavaPaolo Nesi
Smart City strategy, city smartening, big data amanagement,
-Taking into account results of participatory actions
-Smart city strategic plan, city agenda: prioritizing interventions
-Agreements for collaborations with main actors:
main research centers, main City Operators, etc.
-Direct collaborations on specific projects on:
ICT, Mobility, Culture, Energy, etc.
Experimenting on specific projects of the Smart City Strategic Plan
-Needs of harmonizing results and aggregating data towards dashboards
KM4city, Il Valore degli #OpenData: Esperienze a confrontoPaolo Nesi
le città si stanno adeguando alle crescenti necessità cercando di: garantire elevati livelli di qualità della vita, fornire nuovi servizi; limitando i costi, aumento di efficienza; allestire strutture decisionali adeguate; facilitare la creazione di nuovi servizi anche da parte di terzi:
-Pubblicazione Open Data
-Creare i presupposti per un mercato dei dati anche privati ma connessi agli -OpenData
->per una la crescita sostenibile da vari punti di vista
I dati, statici e real time sono stati resi interoperabili tramite algoritmi di data mining che possono essere applicati anche alle vostre problematiche
I dati aggregati ora sono accessibili in modo semplice tramite degli strumenti di sviluppo ed accesso che permettono di abbattere I costi di sviluppo delle applicazioni web e mobili
Service Map:http://servicemap.disit.org
Permette allo sviluppatore di realizzare delle query in modo visuale e farsi mandare il codice di richiesta tramite email.
Questo codice può essere utilizzato in App mobili e web per semplificare la programmazione e realizzare app che non devono essere manutenute quanto il server cambia…
La selezione effettuata può essere richiamata e anche inserita in pagine web di terzi, l’applicazione web è già pronta.
Manteniamo le App Vive, la complessità sta sul server e non sulle App !!
LOG: http://log.disit.org
Permette allo sviluppatore di navigare nelle strutture complesse di uno o più database RDF accessibili per formulare dei grafici e delle query in modo visuale e farsi mandare il codice di richiesta tramite email.
Questo codice può essere utilizzato in App mobili e web per semplificare la programmazione e realizzare app che non devono essere manutenute quanto il server cambia…
Il grafo puo’ essere richiamato e anche inserito in pagine web di terzi, l’applicazione web è già pronta.
Manteniamo le App Vive !!
Snap4City: SCALABLE SMART ANALYTIC APPLICATION BUILDER FOR SENTIENT CITIESPaolo Nesi
• Dashboards: from City Dashboard to Applications
• Data gathering and City Data Knowledge Management
• Forging & Managing Open and Flexible Web and Mobile Apps
• IOT/IOE Devices and Networks
• IOT Applications, the Logic and the Smartness
• IOT Applications vs IOT Edge Devices
• Advanced Smart City API, MicroServices, Snap4City API
• Snap4City Living Lab for Collaborative Work
• Snap4City for Beginners
• Open to developers and stakeholders
• Snap4City Architecture and Ecosystem
• Decision Support System vs Resilience
• Twitter Vigilance: Social Media Analysis
• Snap4City and Km4City Projects
• How to Adopt Snap4City, and our Roadmap
• Snap4City: the view of the Administrators
Snap4City November 2019 Course: Smart City IOT development of IOT ApplicationsPaolo Nesi
• IOT Applications, Devices and Dashboards
– Managing IOT Applications
– Authoring IOT Applications
– IOT App vs Data Analytic
– IOT App vs Web Scraping
– IOT Apps Examples
• From Simple to Data Processing IOT Applications
– Create a Simple IOT Application (Demo)
– Production of IOT Application (Exercitation)
– Data Processing with IOT Application (Demo)
– Processing Data with IOT Applications (Exercitation)
• IOT Network Support
– Proprietary IOT Devices as Well as Open hardware / Open Software
• IOT end-2-end Secure Stack
Snap4City November 2019 Course: Smart City IOT Geernal overview, from dashboa...Paolo Nesi
• Overview
• Urban Platform (main concepts vs Living Lab)
• Snap4City Architecture, roadmap, logos, innovations
• Dashboards: from City Dashboards to Applications
• Trajectories and real time tracking
• Dashboards Intelligence and web and mobile devices
• Dashboard chatrooms and notifications
• Smart City Control Room
• Dashboards production
• Data Gathering and City Data Knowledge Management
• Protocol vs Data
• Data Gathering processes
• GIS Data Import, Export and Exploitation
• Semantic Modeling and City Knowledge Base: Km4CIty
• IOT Applications, Devices and Dashboards
• IOT Devices
• Forging & Managing Flexible Mobile Apps, Web App, MicroApplications
• Web and Mobile App with Open Development Kit
• Understanding how city users are using the city services
• Engaging City Users Towards Virtuous Behaviour
• Data Analytic, Big Data Science
• Data Analytics: predictions
• Smart Parking: predictions
• User behaviour Analysis via Wi-Fi, OD Matrices, Trajectories
• Recognition of Used Transportation Means
• Traffic Flow Reconstruction, from traffic sensors data
• Quality of Public Transport
• Origin Destination Matrices
• Demand of Mobility vs Offer of Transportation
• Modal and Multimodal Routing for Navigation and Travel Planning
• Environmental Data Predictions
• Prediction of Qir Quality
• Anomaly Detection
• Environmental data prediction
• Social Media Analysis
• Snap4City Living Lab for Collaborative Work
• Development Life Cycle
• Development tools
• Data protection, personal da vs GDPR
• Snap4City and Km4City Projects
• Acknowledgment
EDF2014: Talk of European Data Innovator Award Winner: Johann Mittheisz, form...European Data Forum
This document summarizes an award given to Johann Mittheisz for European Data Innovator in 2014. It discusses Vienna's success as one of the world's most innovative cities, ranking highly in areas like quality of living, public transport, and being a congress city. It highlights Vienna's open data initiative and some apps created using open data like a toilet map, parking app, and voice assistant. Key dates are provided for Vienna's open data program in 2014 and an open invitation is extended to provide feedback on the program.
RESOLUTE: Governing for Resilience – Implementation Challenges Paolo Nesi
The document discusses the RESOLUTE project, which aims to develop guidelines and tools to help cities improve resilience. It focuses on applying these to urban transport systems. The project will create European Resilience Management Guidelines, validate them using the Collaborative Resilience Assessment and Management Support System in pilot cities Florence and Athens, and disseminate the guidelines across Europe. The document provides details on the RESOLUTE objectives, outcomes, architecture and tools developed to help assess and improve city resilience.
Smart City at DISIT Lab, step two after smart city for beginnersPaolo Nesi
Smart City Concepts
Architecture of Smart City Infrastructures
Peripheral processors
Data ingestion and mining
Reasoning and Deduction
Data Acting processors
SmartCity Project Coll@bora
SmartCity Project Sii-Mobility
Data Mining and smart City problematic
DISIT Smart City Ontology
Data ingestion and integration
Service Map and Linked Open Graph
Blog Vigilance via Natural Language Processing
Mobile Emergency
Smart Health
Smart Education
Smart Mobility
Smart Energy
Smart Governmental
Smart economy
Smart people
Smart environment
Smart living
Smart Telecommunication
In lab en_nov2012-smartcitiescongress-smartcities-ictinLabFIB
The document summarizes research areas and projects of inLab FIB, an innovation and research lab of the Barcelona School of Informatics. The lab's areas of expertise include modeling and simulation, smart cities, mobile apps and GIS, collaborative internet, data analysis, IT services, and infrastructure. Projects focus on transportation optimization, dynamic ridesharing, energy efficiency, open data, and developing apps to promote public health. The lab collaborates with industry and government on applied research and technology transfer.
The document discusses Rennes, France, a city of 420,000 inhabitants that is focused on digital technologies and citizen participation. It describes Rennes' open data portal, hackathons, and network of FabLabs that encourage residents to co-create public services. The city sees opportunities in using IoT and open data to improve services around transportation, waste management, and urban innovation. Rennes aims to empower citizens as actors in their city through collective learning, skills sharing, and open innovation projects.
inLab FIB is a multidisciplinary research and innovation lab located at the Barcelona School of Informatics within the Universitat Politècnica de Catalunya. The lab has over 30 years of experience developing applications using the latest technologies and collaborating on research projects with public administrations, industry, and other organizations. inLab FIB's areas of expertise include modeling and simulation, smart cities, mobile apps and GIS, collaborative internet, data analysis, IT services, and infrastructure. Some of the lab's current projects focus on dynamic ridesharing, open source device tracking, optimizing energy consumption on metro lines, and apps to promote health in cities.
Snap4City has been created in response to Select4Cities PCP (http://www.select4cities.eu/) call as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp.
Snap4City is 100% open source:
robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, GDPR, and city dashboards.
extending with IOT/IOE the semantic reasoner of Km4City https://www.km4city.org
Km4City has been validated in multiple devices (PC, Android, Raspberry, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and million of data per day.
The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, .. thus
setting up smart city solutions in a snap
Serve as a City Dashboard, App User Interface, etc.
Real time and historical data, any device, sensors and actuators
Sensors, KPI, maps, data trends, real time data, charts, etc.
Referral / historical data, and Open Data:
shadow, access (API, storage, any protocol), production of OD, export
Data Driven Real Time communication & processing:
IOT Applications, IOT edge, multiple operating systems, embedded systems, MicroServices
in/out data driven from/to the field into: applications, notifications, etc.
Data Analytics: Machine Learning, statistics, reasoning, …
Serve as Living Lab: open innovation, coworking; collaborative work; sharing: data, processes, dashboard, experiences, solutions, ….
Experimented on large scale cases
A Smart City Development kit for designing Web and Mobile AppsPaolo Nesi
Presentation of some of the Km4City development tools: ServiceMap and App Development Kit, ADK.
ServiceMap is focused on providing information to the developers, to help them learning how to access to the data model, to exploit and use the API
ADK is a drafted modular web and mobile application based on HTML5 and JavaScript (apache Cordova) that can be used to exploit Smart City API to develop a large range of applications.
It is modular, flexible, etc. and allow performing users behavior analysis.
The solutions are currently in use on several EC and national Projects such as: Sii-Mobility, RESOLUTE, REPLICATE, Weee, …
Cities aims at providing new Smart Services to city users:
operators, final users, etc.
In most cases via Web and Mobile Apps which exploit data:
Structural data, open data, real time data, etc., private data from companies
to be aggregated and transformed in services (providing: prediction, information, early warning, relations)
at reasonable cost for: developers, operators, and SME to realize new Apps and services.
If cost is not affordable, Services and Apps are not developed, in most cases the Apps are also provided for free, so that high costs are not sustainable Public Private Partnership
Scenarious vs SmartCity API
Search data: by text, near, along, etc...
Resolving text to GPS and formal city nodes model
Empowering the city users
Access to event information
Supporting City Users in using Public Mobility
Supporting City Users in using Private Mobility
New Experience to access at Cultural and Touristic info
New way to access at health services
Access at Environmental information
Profiled Suggestions to City Users
Personal Assistant
Sharing knowledge among cities
ServiceMap tool
with Km4City are substantially a Smart City Expert System, SCES
includes the Smart City API
is a for developers to: search and browse on Smart City Knowledge, also to generate examples of the Smart City API call to be used in the development of Web and Mobile Apps
The IEEE Smart World Congress originated from the 2005 Workshop on Ubiquitous Smart Worlds (USW, Taipei) and the 2005 Symposium on Ubiquitous Intelligence and Smart World (UISW, Nagasaki). SmartWorld 2017 in San Francisco is the next edition after the successful SmartWorld 2016 in Toulouse France and SmartWorld 2015 in Beijing China. SmartWorld 2017 is to provide a high-profile, leading-edge platform for researchers and engineers to exchange and explore state-of-art advances and innovations in graceful integrations of Cyber, Physical, Social, and Thinking Worlds for the theme
http://ieee-smartworld.org/2017/smartworld/
Km4City: A reusable example of a Metropolitan-Wide Data Platform, MAJORCITIES...Paolo Nesi
This document describes Km4City, an open source smart city platform developed by DISIT Lab. It consists of tools to 1) keep cities under control via personalized dashboards, 2) improve city resilience through risk reduction and decision support, and 3) transform data into value for cities. The platform integrates data from various city systems and sensors to power applications for operators, decision makers, and citizens. It has been implemented in Florence and Tuscany to support projects like Sii-Mobility.
Km4city Smart City Ecosystem Urban PlatformPaolo Nesi
keep city under control via personalized dashboards
improve city resilience, reducing risks and decision support
transform data in value for the city
monitoring services’ status of city operators
Smart City Dashboards, http://dashboard.km4city.org Dashboard Builder
monitoring and understanding the city users behaviour
Recommender and User Behavior Analyzer, http://recommender.km4city.org
WiFi monitor, http://wifimap.km4city.org
Origin Destination matrix tools http://www.disit.org/6694
collecting moods, contributions and data from the city users
Collecting contributions: images, stars, comments and Social Media
monitoring social media for city services and events, event predictions
Twitter Vigilance, http://www.disit.org/tv , http://tvsolr.disit.org
assessing city resilience level
Resilience Decision Support, http://resilienceds.km4city.org
Smart decision support system, http://smartds.km4city.org
improving city resilience, providing objective hints
Resilience Decision Support implementing European Resilience Management Guidelines (ERMG) http://www.resolute-eu.org
improving city users awareness with personal city assistants and participatory tools
Dashboard: http://dashboard.km4city.org
Km4City Web App http://www.km4city.org
Km4City Mobile App: http://www.km4city.org/app
enabling commercial and business applications
decision support access
aggregating multi-domain data and services for SMEs and city operators
Data /Service Aggregator: open, flexible and suitable access
data aggregation and access Smart City API
integrated data and services, accessible as on demand basis
providing services for third party portals and Apps: geo-localized data and services, info, suggestions
suggestion on demand service for SMEs and city operators
Suggestion On Demand see above
Personal Assistance: information, engagement, soundage
development tool for fast and low cost implementation of business and service oriented Apps
Smart City API
Km4City, Smart City Urban Platform, From Data to Services for the Sentient Ci...Paolo Nesi
The document describes the Km4City Smart City Ecosystem project. Km4City aims to use data collected from smart city systems and citizens to 1) keep cities under control via personalized dashboards, 2) improve city resilience by reducing risks, and 3) transform data into value for cities. It provides open-source tools for monitoring services, user behavior, social media, and more. These tools help cities manage operations, understand users, and make data-driven decisions. The ecosystem is currently deployed in Florence, Italy.
DAI DATI INTELLIGENTI AI SERVIZI Smart City API HackathonPaolo Nesi
DAI DATI INTELLIGENTI AI SERVIZI
Smart City API Hackathon
Premi per 14.000 euro
Data: 7 e 8 aprile 2017
Luogo: Scuola di Ingegneria, Università degli Studi di Firenze
Il progetto Sii-Mobility, Smart City nazionale (MIUR), organizza il primo hackathon per promuovere lo sviluppo di applicazioni fisse e mobili sulla base delle http://www.disit.org/6991che si basano sul modello http://www.km4city.org .
Scopo dell'evento di hackathon è identificare nuove applicazioni che possano essere sviluppate sulla base di dati ed elaborazioni messi disposizione dalle smart city API di Sii-Mobility. I Dati sono in tutta la toscana e come dagli scenari http://www.disit.org/6995, sono relativi alla mobilità pubblica e privata, alla partecipazione, alle informazioni geolocalizzate dei punti di interesse, della salute, ambiente, e servizi di suggerimento e di coinvolgimento e assistenza.
Le tematiche affrontate dalle App proposte dovranno essere relative ad aspetti di mobilità, e in particolare ai seguenti 5 temi: Trasporto pubblico; Coinvolgimento dei cittadini, mobilità e turismo, mobilità e servizi, giochi in mobilità.
http://www.sii-mobility.org/index.php/eventi/hackathon-sii-mobility/registrati-all-evento-del-7-mattina
Documentazione e informazioni dalla pagina: http://www.sii-mobility.org/
Scadenza sottomissione delle proposte: 31 marzo 2017.
Premi per 14.000 euro, #hackathon #smartcity API, #bigdata #opendata della #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
#hackathon #smartcity #bigdata #opendata #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
Smart City API, 14.000 euro di premi, Hackathon
hackathon smart city API, dai dati ai serviziPaolo Nesi
DAI DATI INTELLIGENTI AI SERVIZI
Smart City API Hackathon
Premi per 14.000 euro
Data: 7 e 8 aprile 2017
Luogo: Scuola di Ingegneria, Università degli Studi di Firenze
Il progetto Sii-Mobility, Smart City nazionale (MIUR), organizza il primo hackathon per promuovere lo sviluppo di applicazioni fisse e mobili sulla base delle http://www.disit.org/6991che si basano sul modello http://www.km4city.org .
Scopo dell'evento di hackathon è identificare nuove applicazioni che possano essere sviluppate sulla base di dati ed elaborazioni messi disposizione dalle smart city API di Sii-Mobility. I Dati sono in tutta la toscana e come dagli scenari http://www.disit.org/6995, sono relativi alla mobilità pubblica e privata, alla partecipazione, alle informazioni geolocalizzate dei punti di interesse, della salute, ambiente, e servizi di suggerimento e di coinvolgimento e assistenza.
Le tematiche affrontate dalle App proposte dovranno essere relative ad aspetti di mobilità, e in particolare ai seguenti 5 temi: Trasporto pubblico; Coinvolgimento dei cittadini, mobilità e turismo, mobilità e servizi, giochi in mobilità.
http://www.sii-mobility.org/index.php/eventi/hackathon-sii-mobility/registrati-all-evento-del-7-mattina
Documentazione e informazioni dalla pagina: http://www.sii-mobility.org/
Scadenza sottomissione delle proposte: 31 marzo 2017.
Premi per 14.000 euro, #hackathon #smartcity API, #bigdata #opendata della #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
#hackathon #smartcity #bigdata #opendata #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
Smart City API, 14.000 euro di premi, Hackathon
Integrated infrastructure for urban platform in Florence Replicate project scc1Paolo Nesi
Integrated infrastructure for urban platform in Florence Replicate project scc1.
Aggregate & integrate data and streams of any urban system, operator,
provider, user, .., exploiting
– open data, IOT, sensors, internet of everything,
– cloud, mobile devices, Wi‐Fi, social media,
– big data analytics, ecc;
• Perform integrated and unified data management and data analytics by a set
of tools at service of city operators and city users, to:
– Control Room, Real Time Monitoring tools, ….
– Perform predictions, reasoning, business intelligence, city users behavior analysis
• Produce value from data enabling to
– Stimulate virtuous behavior, influence City Users!
– Increase efficiency in energy consumption
– Reduce pollution and traffic congestion
– Improve quality of service, quality of life
– Create an ecosystem for innovation and punt in action any smart city solutions
and services.
Km4city: Open Urban Platform for a Sentient Smart CityPaolo Nesi
1) Km4City is an open urban platform that aggregates data from IoT sensors and city services to create a smart city ecosystem.
2) The platform includes tools for real-time monitoring, data analytics, influencing citizen behavior, and transforming data into new smart city services.
3) Example tools include smart city dashboards, predictive models, mobile apps, and Twitter analysis to gain citizen input and assess sentiment.
Km4City: Smart City HowTo and Overview, 2016Paolo Nesi
Km4City storia e roadmap
Dati e Modello
Development Tools
App: Web e Mobile
Mobile reasoning and Monitoring
Monitoring via Wi-Fi
Control Room
Twitter Vigilance
Progetti Connessi
Set up an ICT based Urban Platform integrated and unified data management among services, city operators and city users:
Control Room, Real Time Monitoring
decision support, assessing and monitoring risk and resilience
Data analytics and business intelligence
predictions, reasoning, city users behavior analysis, ….
Reading the city: data, users behavior and needs, ...
IOT, Open data sensors, private data, static and real time data.
City Strategies: stimulate virtuous behavior of City Users
participation, totem, twitter, Apps, etc.
Transform Data into value
Put in action smart city innovative solutions and services, development tools
Smart City Strategic Forecast, SmartCity360, BratislavaPaolo Nesi
Smart City strategy, city smartening, big data amanagement,
-Taking into account results of participatory actions
-Smart city strategic plan, city agenda: prioritizing interventions
-Agreements for collaborations with main actors:
main research centers, main City Operators, etc.
-Direct collaborations on specific projects on:
ICT, Mobility, Culture, Energy, etc.
Experimenting on specific projects of the Smart City Strategic Plan
-Needs of harmonizing results and aggregating data towards dashboards
KM4city, Il Valore degli #OpenData: Esperienze a confrontoPaolo Nesi
le città si stanno adeguando alle crescenti necessità cercando di: garantire elevati livelli di qualità della vita, fornire nuovi servizi; limitando i costi, aumento di efficienza; allestire strutture decisionali adeguate; facilitare la creazione di nuovi servizi anche da parte di terzi:
-Pubblicazione Open Data
-Creare i presupposti per un mercato dei dati anche privati ma connessi agli -OpenData
->per una la crescita sostenibile da vari punti di vista
I dati, statici e real time sono stati resi interoperabili tramite algoritmi di data mining che possono essere applicati anche alle vostre problematiche
I dati aggregati ora sono accessibili in modo semplice tramite degli strumenti di sviluppo ed accesso che permettono di abbattere I costi di sviluppo delle applicazioni web e mobili
Service Map:http://servicemap.disit.org
Permette allo sviluppatore di realizzare delle query in modo visuale e farsi mandare il codice di richiesta tramite email.
Questo codice può essere utilizzato in App mobili e web per semplificare la programmazione e realizzare app che non devono essere manutenute quanto il server cambia…
La selezione effettuata può essere richiamata e anche inserita in pagine web di terzi, l’applicazione web è già pronta.
Manteniamo le App Vive, la complessità sta sul server e non sulle App !!
LOG: http://log.disit.org
Permette allo sviluppatore di navigare nelle strutture complesse di uno o più database RDF accessibili per formulare dei grafici e delle query in modo visuale e farsi mandare il codice di richiesta tramite email.
Questo codice può essere utilizzato in App mobili e web per semplificare la programmazione e realizzare app che non devono essere manutenute quanto il server cambia…
Il grafo puo’ essere richiamato e anche inserito in pagine web di terzi, l’applicazione web è già pronta.
Manteniamo le App Vive !!
Snap4City: SCALABLE SMART ANALYTIC APPLICATION BUILDER FOR SENTIENT CITIESPaolo Nesi
• Dashboards: from City Dashboard to Applications
• Data gathering and City Data Knowledge Management
• Forging & Managing Open and Flexible Web and Mobile Apps
• IOT/IOE Devices and Networks
• IOT Applications, the Logic and the Smartness
• IOT Applications vs IOT Edge Devices
• Advanced Smart City API, MicroServices, Snap4City API
• Snap4City Living Lab for Collaborative Work
• Snap4City for Beginners
• Open to developers and stakeholders
• Snap4City Architecture and Ecosystem
• Decision Support System vs Resilience
• Twitter Vigilance: Social Media Analysis
• Snap4City and Km4City Projects
• How to Adopt Snap4City, and our Roadmap
• Snap4City: the view of the Administrators
Snap4City November 2019 Course: Smart City IOT development of IOT ApplicationsPaolo Nesi
• IOT Applications, Devices and Dashboards
– Managing IOT Applications
– Authoring IOT Applications
– IOT App vs Data Analytic
– IOT App vs Web Scraping
– IOT Apps Examples
• From Simple to Data Processing IOT Applications
– Create a Simple IOT Application (Demo)
– Production of IOT Application (Exercitation)
– Data Processing with IOT Application (Demo)
– Processing Data with IOT Applications (Exercitation)
• IOT Network Support
– Proprietary IOT Devices as Well as Open hardware / Open Software
• IOT end-2-end Secure Stack
Snap4City November 2019 Course: Smart City IOT Geernal overview, from dashboa...Paolo Nesi
• Overview
• Urban Platform (main concepts vs Living Lab)
• Snap4City Architecture, roadmap, logos, innovations
• Dashboards: from City Dashboards to Applications
• Trajectories and real time tracking
• Dashboards Intelligence and web and mobile devices
• Dashboard chatrooms and notifications
• Smart City Control Room
• Dashboards production
• Data Gathering and City Data Knowledge Management
• Protocol vs Data
• Data Gathering processes
• GIS Data Import, Export and Exploitation
• Semantic Modeling and City Knowledge Base: Km4CIty
• IOT Applications, Devices and Dashboards
• IOT Devices
• Forging & Managing Flexible Mobile Apps, Web App, MicroApplications
• Web and Mobile App with Open Development Kit
• Understanding how city users are using the city services
• Engaging City Users Towards Virtuous Behaviour
• Data Analytic, Big Data Science
• Data Analytics: predictions
• Smart Parking: predictions
• User behaviour Analysis via Wi-Fi, OD Matrices, Trajectories
• Recognition of Used Transportation Means
• Traffic Flow Reconstruction, from traffic sensors data
• Quality of Public Transport
• Origin Destination Matrices
• Demand of Mobility vs Offer of Transportation
• Modal and Multimodal Routing for Navigation and Travel Planning
• Environmental Data Predictions
• Prediction of Qir Quality
• Anomaly Detection
• Environmental data prediction
• Social Media Analysis
• Snap4City Living Lab for Collaborative Work
• Development Life Cycle
• Development tools
• Data protection, personal da vs GDPR
• Snap4City and Km4City Projects
• Acknowledgment
EDF2014: Talk of European Data Innovator Award Winner: Johann Mittheisz, form...European Data Forum
This document summarizes an award given to Johann Mittheisz for European Data Innovator in 2014. It discusses Vienna's success as one of the world's most innovative cities, ranking highly in areas like quality of living, public transport, and being a congress city. It highlights Vienna's open data initiative and some apps created using open data like a toilet map, parking app, and voice assistant. Key dates are provided for Vienna's open data program in 2014 and an open invitation is extended to provide feedback on the program.
RESOLUTE: Governing for Resilience – Implementation Challenges Paolo Nesi
The document discusses the RESOLUTE project, which aims to develop guidelines and tools to help cities improve resilience. It focuses on applying these to urban transport systems. The project will create European Resilience Management Guidelines, validate them using the Collaborative Resilience Assessment and Management Support System in pilot cities Florence and Athens, and disseminate the guidelines across Europe. The document provides details on the RESOLUTE objectives, outcomes, architecture and tools developed to help assess and improve city resilience.
Smart City at DISIT Lab, step two after smart city for beginnersPaolo Nesi
Smart City Concepts
Architecture of Smart City Infrastructures
Peripheral processors
Data ingestion and mining
Reasoning and Deduction
Data Acting processors
SmartCity Project Coll@bora
SmartCity Project Sii-Mobility
Data Mining and smart City problematic
DISIT Smart City Ontology
Data ingestion and integration
Service Map and Linked Open Graph
Blog Vigilance via Natural Language Processing
Mobile Emergency
Smart Health
Smart Education
Smart Mobility
Smart Energy
Smart Governmental
Smart economy
Smart people
Smart environment
Smart living
Smart Telecommunication
In lab en_nov2012-smartcitiescongress-smartcities-ictinLabFIB
The document summarizes research areas and projects of inLab FIB, an innovation and research lab of the Barcelona School of Informatics. The lab's areas of expertise include modeling and simulation, smart cities, mobile apps and GIS, collaborative internet, data analysis, IT services, and infrastructure. Projects focus on transportation optimization, dynamic ridesharing, energy efficiency, open data, and developing apps to promote public health. The lab collaborates with industry and government on applied research and technology transfer.
The document discusses Rennes, France, a city of 420,000 inhabitants that is focused on digital technologies and citizen participation. It describes Rennes' open data portal, hackathons, and network of FabLabs that encourage residents to co-create public services. The city sees opportunities in using IoT and open data to improve services around transportation, waste management, and urban innovation. Rennes aims to empower citizens as actors in their city through collective learning, skills sharing, and open innovation projects.
inLab FIB is a multidisciplinary research and innovation lab located at the Barcelona School of Informatics within the Universitat Politècnica de Catalunya. The lab has over 30 years of experience developing applications using the latest technologies and collaborating on research projects with public administrations, industry, and other organizations. inLab FIB's areas of expertise include modeling and simulation, smart cities, mobile apps and GIS, collaborative internet, data analysis, IT services, and infrastructure. Some of the lab's current projects focus on dynamic ridesharing, open source device tracking, optimizing energy consumption on metro lines, and apps to promote health in cities.
Snap4City has been created in response to Select4Cities PCP (http://www.select4cities.eu/) call as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp.
Snap4City is 100% open source:
robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, GDPR, and city dashboards.
extending with IOT/IOE the semantic reasoner of Km4City https://www.km4city.org
Km4City has been validated in multiple devices (PC, Android, Raspberry, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and million of data per day.
The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, .. thus
setting up smart city solutions in a snap
Serve as a City Dashboard, App User Interface, etc.
Real time and historical data, any device, sensors and actuators
Sensors, KPI, maps, data trends, real time data, charts, etc.
Referral / historical data, and Open Data:
shadow, access (API, storage, any protocol), production of OD, export
Data Driven Real Time communication & processing:
IOT Applications, IOT edge, multiple operating systems, embedded systems, MicroServices
in/out data driven from/to the field into: applications, notifications, etc.
Data Analytics: Machine Learning, statistics, reasoning, …
Serve as Living Lab: open innovation, coworking; collaborative work; sharing: data, processes, dashboard, experiences, solutions, ….
Experimented on large scale cases
A Smart City Development kit for designing Web and Mobile AppsPaolo Nesi
Presentation of some of the Km4City development tools: ServiceMap and App Development Kit, ADK.
ServiceMap is focused on providing information to the developers, to help them learning how to access to the data model, to exploit and use the API
ADK is a drafted modular web and mobile application based on HTML5 and JavaScript (apache Cordova) that can be used to exploit Smart City API to develop a large range of applications.
It is modular, flexible, etc. and allow performing users behavior analysis.
The solutions are currently in use on several EC and national Projects such as: Sii-Mobility, RESOLUTE, REPLICATE, Weee, …
Cities aims at providing new Smart Services to city users:
operators, final users, etc.
In most cases via Web and Mobile Apps which exploit data:
Structural data, open data, real time data, etc., private data from companies
to be aggregated and transformed in services (providing: prediction, information, early warning, relations)
at reasonable cost for: developers, operators, and SME to realize new Apps and services.
If cost is not affordable, Services and Apps are not developed, in most cases the Apps are also provided for free, so that high costs are not sustainable Public Private Partnership
Scenarious vs SmartCity API
Search data: by text, near, along, etc...
Resolving text to GPS and formal city nodes model
Empowering the city users
Access to event information
Supporting City Users in using Public Mobility
Supporting City Users in using Private Mobility
New Experience to access at Cultural and Touristic info
New way to access at health services
Access at Environmental information
Profiled Suggestions to City Users
Personal Assistant
Sharing knowledge among cities
ServiceMap tool
with Km4City are substantially a Smart City Expert System, SCES
includes the Smart City API
is a for developers to: search and browse on Smart City Knowledge, also to generate examples of the Smart City API call to be used in the development of Web and Mobile Apps
The IEEE Smart World Congress originated from the 2005 Workshop on Ubiquitous Smart Worlds (USW, Taipei) and the 2005 Symposium on Ubiquitous Intelligence and Smart World (UISW, Nagasaki). SmartWorld 2017 in San Francisco is the next edition after the successful SmartWorld 2016 in Toulouse France and SmartWorld 2015 in Beijing China. SmartWorld 2017 is to provide a high-profile, leading-edge platform for researchers and engineers to exchange and explore state-of-art advances and innovations in graceful integrations of Cyber, Physical, Social, and Thinking Worlds for the theme
http://ieee-smartworld.org/2017/smartworld/
Keynote: Making Smarter Tuscany and Florence with Km4CityPaolo Nesi
Keynote at International Summit on Smart World and Smart Cities, In Conjunction With 2017 IEEE Smart World Congress
August 5, 2017, San Francisco, USA
http://smart-city-conference.com/summit2017/
Sentient Urban Platform for Smart City
Set up an ICT based Urban Platform integrated and unified data management among services, city operators and city users:
Control Room, Real Time Monitoring
decision support, assessing and monitoring risk and resilience
Data analytics and business intelligence
predictions, reasoning, city users behavior analysis, ….
Reading the city: big data, users behavior and needs, ...
IOT, Open data sensors, private data, static and real time data.
City Strategies: stimulate virtuous behavior of City Users
participation, totem, twitter, Apps, etc.
Transform Data into value
Put in action smart city innovative solutions and services, development tools
What is enabling and providing smart services
Smart Parking, in Tuscany
Smart First Aid in Tuscany
Smart Fuel pricing in Tuscany
Smart search for POI and public transport srv.
Public Transportation in Tuscany
Routing and multimodal in Tuscany
Social Media Monitoring and acting
Traffic events and Resilience in Florence
Bike Sharing in Pisa and Siena
Recharge stations for e-vehicles
Entertainment Events in Florence
Traffic Sensors in Tuscany
Weather forecast/condition in Tuscany
Pollution and Pollination in Tuscany
People Monitoring Assessment in the City, in Florence via WiFi
People Monitoring, in Tuscany via App
All Point of Interests, cultural activities, IOT, …
Over than 1.2 Million of complex events per day!
Snap4City November 2019 Course: Smart City IOT Data Ingestion Interoperabilit...Paolo Nesi
• Data Ingestion Capabilities
• Data Ingestion Strategy
• Setting Up the Road Graph on Knowledge Base
• Data Set Load via Data Gate (plus how to load triples into Knowledge base)
• Data Ingestion and Transformation via ETL Processes
• Data Ingestion via IOT Brokers
• IOT Network: recall of basic concepts
• IOT Directory
• IOT Devices and IOT Brokers Registration
• Data Ingestion via IOT Applications
• Data Ingestion from API, External Services, Custom MicroServices
• Data Ingestion via Web Scraping
• Data Streams from Smart City API, participatory
• Data Streams from Mobile Devices
• Data Streams from Dashboards
• GIS Data Import and Export
• Social Media data collection and exploitation
• Acknowledgements
DISIT: Competenze per Industria 4.0
Technical Areas:
Industrial Internet: integrazione di fabbrica, ..
Smart/Advanced manufacturing: mobility, delivering, optimization, etc.
(Smart City: mobility and transport, energy, IOT/IOE, analytics, …)
(Smart Retail: user behavior analysis, engagement, …)
Technologies:
Big Data and Analytics: data management, user analysis, user engagement, prediction, early detection, data intelligence, …
Data Mining: artificial intelligence, semantic computing, semantic reasoner, expert systems, statistic analysis, ..
IOT/IOE: internet of things/everything, brokers, microservices, ..
Cloud: smart cloud, cloud simulation, optimization, ..
Mobile Computing: mobile application, user behavior analysis, ..
NLP and Sentiment Analysis: response Vigilance, interaction, answering, ..
See projects on: http://www.disit.org/5501
Big Data analytics Aree Applicative
-Smart manufacturing
-Personal assistants
-Autonomous engine, semantic reasoners
-Experts systems
-Smart Cloud
-Services and microservices integration
-Industrie farmaceutiche
-Mobilità e Trasporti
-Turismo e Cultura
-Smart City, Innovation Lab
Servizi alla persona
Smart City and Open Data Projects and tools of DISIT LabPaolo Nesi
Current research topics
• Social media, collaborative work, Mobile computing, OpenData, LOD
• SmartCity, BigData, data analytics
• Railway signaling, autonomous driving systems, formal methods
• Cloud Computing, grid computing, smart cloud
• Data Mining, Knowledge Acceleration, natural language processing
Main research results
• Knowledge Management and Natural Language Processing: OSIM, CoSkoSAM
• Content and Protection Management, grid computing: AXMEDIS AXCP
• Social Media, recommendations and tool: ECLAP.eu, MyStoryPlayer, Social Graph, IPR Wizard…
• Mobile Computing: Mobile Medicine, Mobile Emergency, etc.….
• Music Transcode, winner of MIREX for piano
• Awards: IEEE ICECCS, DMS, Italia degli Innovatori, etc.
Main sources of funding
• European Commission: ECLAP (social media, Cultural Heritage, open data), AXMEDIS (DRM, protection, automation e grid computing), WEDELMUSIC, IMAESTRO, VARIAZIONI, IMUTUS, MUSICNETWORK, MOODS, MUPAAC, OFCOMP, etc. ……
• Italian Ministry: Smart Cities COLL@BORA (collaborative work, social media), FIRB e PRIN
• Regional: SACVAR (knowledge mining and reasoning), TRACE‐IT (Railway signalling), RAISSS (Railway signalling), ICARO (cloud)
• Fondations: MatchMaking (NLP), OSIM (Knowledge Acceleration, NLP)
DISIT Potential challenges and interests
DISIT is interested in participating in the next calls of the European Commission and in particular for:
• Working on open data and linked open data for smart city, smart cloud, smart manufacturing, smart museum, etc.
• Creating semantic models and reasoning engines
• Creating data mining and natural language processing tools as SACVAR/OSIM
• Working on defining big data solutions and infrastructures
• Working on data analytics algorithms computing:
• Predictions and trends,
• unexpected correlations,
• data inconsistencies and incompleteness,
• etc.
Snap4City has been created in response to Select4Cities PCP (http://www.select4cities.eu/) call as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp.
Snap4City is a fully open source, robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, extending the powerful semantic reasoner of Km4City https://www.km4city.org, with IOT/IOE, GDPR, and city dashboards.
Km4City has been validated in multiple devices (PC, Android, Raspberry, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and million of data per day.
The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, .. thus setting up smart city solutions in a snap
Big Data Smart City processes and tools, Real Time data processing toolsPaolo Nesi
Big Data Smart City Architecture
Smart-city Ontology
Data Ingestion and Mining
-Data Ingestion Manager
-DataSets already integrated
-Static Data: harvesting
-Data Quality Improvement
-Data mapping to Triples
Distributed and real time processes
-Distributed Scheduler
-Real Time Data Ingestion
-Blog Vigilance, NLP, Text Mining
-Parallel and distributed processing
RDF processing
-RDF Store Indexing
-RDF Store Validation
-Semantic Interoperability, reconciliation
-RDF Store Enrichment, for link discovering
-RDF Store Enrichment, for service discovering via web crawling
Smart City Engine
-Service Level Agreements
-Distributed SPARQL queries
-Decision Support System Processes
Development Interfaces
-Service map: http://servicemap.disit.org
service based on OpenStreetMaps that allows to search services available in a preset range from the selected bus stop.
-Linked Open Graph: http://log.disit.org
a tool developed to allow exploring semantic graph of the relation among the entities. It can be used to access to many different LOD repository.
-Ontology Documentation: http://www.disit.org/6507,
http://www.disit.org/5606, http://www.disit.org/6461
-Data Status Web pages: active
Visual Query Graph: under development
Sii-Mobility
Complexity of IOT/IOE Architectures for Smart Service Infrastructures Panel:...Paolo Nesi
The complexity of smart and sentient applications in smart cities is progressively increasing.
to reach higher precision.
time series prediction artificial intelligent, machine learning
Single data sets multi data sets, and big data: addressing heterogeneity, low quality and discontinuity, etc.
integration of open data, real time data and private IOT / personal data is increasing complexity of cyber-physical-social aspects:
to have the full control on the rights associated to their content
GDPR normative (since May 2018 in force) to regulate the access and control of privacy
I am bringing the experience of addressing
GDPR and Security and into Smart City Solutions with IOT
-----smart city impact----------------
Signed Consent vs Informed Consent
Smart Applications exploit personal data about (for example)
user position and actions for providing geolocated suggestions
home/work position, trajectories,
Payments and traces from bike sharing, from navigators, etc.
body signals/data for monitoring healthiness (glucose, temperature, etc.), for training sport, ..
User actions on applications: choices on menu, queries performed, mobile phones, requested paths, payments, etc.
IOT Devices data: mobile, buttons, trackers, but also temperature in house; position of our dogs, children, cars, bikes, …
etc.
----GDPR: General Data Protection Regulation ---
Users are going to decide to:
provide access to who, for do what, until we consent
accept terms of use by signed consent for each data management service, before was a simple informed consent
from each service, the user has to be capable to
See what the provider collect in terms of its Data Type: traces, logs, paths, profiles, accesses, IOT devices, sensors, maps, etc.
Download, delete, inspect each single Data Type
Auditing and Revoke access or grant access right to each single Data Type
Delete all Data Types in single shot or singularly (forget all about me)
Km4City: Smart City Model and Tools for City Knowledge ExploitationPaolo Nesi
The proposed presentation is going to expose the integrated solutions around Km4City model which has been set up by the DISIT lab in Florence (http://www.disit.org/6056 ) and adopted in some EC and national smart city projects (Sii-Mobility Smart City MIUR project, RESOLUTE H2020, Km4City service and tools in place in the Florence Area, with many industrial partners as Thales, Swarco, ECM, etc.). The solution is based on Km4City model that is capable to model a large set of the above data kind and provides support for inference and reasoning, on time and space, on public and private data, on static and real time data. In more details, the solution developed is open and accessible for city providing models and tools for its adoption and exploitation, also enabling the full customization. It includes a set of tools:
• Service map: http://servicemap.disit.org is a tool for PA administrators and for developers. For the PA administrators provide access to several kinds of geospatial queries in Florence and in the whole Tuscany region, taking as a results static and real time data, geo-localized. The ServiceMap is also a tool for developers, which can be used to understand the usage of API to access at the Km4City services http://www.disit.org/6597 . The ServiceMap facility allows the visual creation of queries on the city, and may send to the connected user via email the SPARQL code of the visual queries performed, and in addition also a simple Query ID. The Query ID can be used to pose the query without writing it, from any Mobile and Web applications without the needs of learning complex ontological and SPARQL models;
• Linked Open Graph for browsing LOD RDF Stores model including the Km4City Smart City model in Florence and Tuscany and thus for learning how to formulate SPARQL queries http://LOG.disit.org. See for example a view of Florence http://log.disit.org/service/?graph=0f50fffc5bcfc205de5a19b606b61310
• Demonstrative mobile application exploiting ServiceMap API, also presented at the Florence Open Data Day and accessible as open source via: http://www.disit.org/6595 .
• Km4City ontology model and documentation [1], http://smartcity.linkeddata.es/, document http://www.disit.org/5606 , http://www.disit.org/km4city/schema/
• Parallel and distributed architecture based on ETL, scheduler, HBase, Hadoop, for massive big data ingestion (static, quasi static, and real time data), reconciliation, data enrichment (for connecting Km4City URI to dbPedia, geonames, etc. [3]) and for making decision: [1], slide http://www.disit.org/6566 with thousands of accesses on SlideShare. Several examples are accessible about the ETL transformation for data ingestion, quality improvement, conversion in triples, reconciliation in SILK, [1], etc. This engine is also adopted in other Smart City Projects as SMST national cluster.
CINI icitie workshop on smart city and communities, palermo, ottobre 2015
Snap4City November 2019 Course: Smart City IOT Data AnalyticsPaolo Nesi
• Data Analytics: Examples from Snap4City
o Smart parking: Predictions
o User Behavior Analysis, via Wi-Fi, OD, Trajectories
o Recognition of Used Transportation means
o Traffic Flow Reconstruction, from Traffic Sensors Data
o Quality of Public Transport Service
o Origin Destination Matrices from: Wi-Fi, Mobile Apps, etc.
o Demand of Mobility vs Offer of Transportation
o Modal and Multimodal Routing for Navigation and Travel Planning
o Environmental Data Analysis and Predictions, early Warning
o Prediction of Air Quality Conditions
o Anomaly Detection
o What-IF Analysis
• Data Analytics: Enforcing and Exploiting
o Real Time Data Analytics: using R Studio Exploitation in IOT Applications
• Decision Support Systems, Smart DS and Resilience DS
• Twitter Vigilance: Social Media Analysis: Early Warning, Predictions
Km4City: Smart City Ontology Building for Effective Erogation of ServicesPaolo Nesi
Provides a unique point of service with integrated and aggregated data and tools for
-- Qualified users: public administrations à developers
-- Operators: mobility, energy, SME, shops, ….. à developers
-- Final users à citizens, students, pendular, tourists
Problems:
--Aggregated Data are not available:
not semantically interoperable, heterogeneous for: format, vocabulary, structure, velocity, volume, ownership/control, access / license, …
---As OD, LD, LOD, private data, ..
---Lack of Services and tools to make the adoption simple
Final Users tools:
--Km4City mobile app with personal assistant is coming…
--Km4City mobile applications: Google Play, Apple Store, …
--Km4City web application: http://www.km4city.org
--Open Source Mobile Application, FODD: an example in open source http://www.disit.org/6595
Public administrator tools:
--Smart decision support system, http://smartds.disit.org
--Developers http://www.disit.org/km4city tools:
--Service Map Server, plus API, http://servicemap.disit.org
--LOG LOD browser: an ultimate visual tool to browse the RDF Store.
--Ontology Documentation: an ultimate tool to understand,
if needed !!
The dirty work of Km4City service
--Data Ingestion Manager, DIM
--RDF Indexer Manager, RIM
--RDF Store Methodology
--RDF store enricher with dbPedia
--Distributed SCE Scheduler, DISCES
--SCE: Smart City Engine
--Doc and info on http://www.disit.org/km4city
IOT/IOE Elastically Scalable Architecture for Smart City and Industry 4.0Paolo Nesi
Snap4 has been created as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp. Snap4 is a fully open source, robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, extending the powerful semantic reasoner of Km4City https://www.km4city.org, with IOT/IOE, GDPR, and city dashboards. Snap4 for Smart city is Snap4City (Https://www.snap4city.org ) is an open platform and solution for setting up Living Labs engaging different all kinds of stakeholders (city operators, researchers, city users, in house, industries) in contributing to the city evolutions, with a platform providing online tools for developing IOT applications, web and mobile Apps, data analytics, micro Applications, external services, KPI, POI, dashboards, IOT edge, etc.
Snap4city has been validated in multiple devices (PC, Android, Raspberry, IOT Button, Arduino, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and millions of data per day. The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, end-2-end encrypted secure communications, GDPR, .. thus setting up in a Snap smart city solutions.
The solution is fully complient with NodeJS with nodex published on JS foundation, is powered by Fi-Ware, compliant with LoraWan, SigFox, Mqtt, AMQP, Coap, NGSI, OMAM2M, WSs, Https, powered by Km4City, TensorFlow NVIDIA, Hadoop, etc. etc.
slides and demos: the platform includes full stack, any format, any protocol, from IOT Device, IOT Edges, Data Analytics, and Dashboards.
DISIT Lab overview: smart city, big data, semantic computing, cloudPaolo Nesi
Smart City
• Projects: http://www.disit.org/5501
– Sii-Mobility, http://www.sii-mobility.org
– Service Map: http://servicemap.disit.org
– Social Innovation: Coll@bora http://www.disit.org/5479
– Navigation Indoor/outdoor: Mobile Emergency http://www.disit.org/5404
– Mobility and Transport: TRACE-IT, RAISSS, TESYSRAIL
• Tools: http://www.disit.org/5489
– Data gathering, data mining and reconciliation
– Data reasoning, deduction, prediction
– Smart city ontology and reasoning tools
– Service analysis and recommendations
– Autonomous train operator, train signaling
– Risk analysis, decision support systems
– Mobile Applications
Data Analytics - Big data
• Projects: http://www.disit.org/5501
– Linked Open Graph: http://LOG.disit.org
– Sii-Mobility, http://www.sii-mobility.org
– Service on a number of projects
• Tools: http://www.disit.org/5489
– Open data and Linked Open Data
– LOG LOD service and tools
– Data mining and reconciliation
– Data reasoning, deduction, prediction, decision support
– SN Analysis and recommendations
– User behavior monitoring and analysis
Smart Cloud - Computing
• Projects: http://www.disit.org/5501
– ICARO: http://www.disit.org/5482
– Cloud ontology: http://www.disit.org/5604
– Cloud simulator:
– Smart Cloud: http://www.disit.org/6544
• Tools: http://www.disit.org/5489
– Cloud Monitoring
– Smart Cloud Engine and reasoner,
– Service Level Analyzer and control
– Configuration analysis and checker
– Cloud Simulation
Text and Web Mining
• Projects: http://www.disit.org/5501
– OSIM: http://www.disit.org/5482
– SACVAR: http://www.disit.org/5604
– Blog/Twitter Vigilance
• Tools: http://www.disit.org/5489
– Text and web mining, Natural Language Processing
– Service localization
– Web Crawling
– Competence analysis
– Blog Vigiliance, sentiment analysis
Social Media and e-Learning
• Projects: http://www.disit.org/5501
– ECLAP, http://www.eclap.eu
– ApreToscana: http://www.apretoscana.org
– Others: AXMEDIS, VARIAZIONI, SMNET, etc.
– Samsung Smart TV: http://www.disit.org/6534
• Tools: http://www.disit.org/5489
– XLMS, Cross Media Learning System
– IPR and content protection and distribution
– Mobile and SmartTv Applications
– Suggestions and recommendations
– Matchmaking solutions
– Media Tools for cross media content
Mobile Computing
• Projects:
– ECLAP: http://www.eclap.eu
– Mobile Medicine: http://mobmed.axmedis.org
– Mobile Emergency: http://www.disit.org/5500
– Smart City, FODD 2015: http://www.disit.org/6593
– Resolute: Mobiles as sensors
• Tools and support:
– Content distribution: e-learning
– Integrated Indoor/outdoor navigation
– User networking and collaboration
– Service localization
– Smart city and services
– OS: iOS, Android, Windows Phone, etc.
– Tech: IOT, iBeacoms, NFC, QR, ….
Basi di dati, SQL
Casi: Analisi della struttura di documenti
Intelligenza Artificiale
Apprendimento, clustering, alberi decisionali
Web crawling, XML, analisi dei testo
Casi di studio: OSIM
Reasoning and inferential
Big data introduction: NoSQL, graph database, ..
Social Media: user profiling, recommendations
Caso di Studio: Twitter Vigilance, sentiment analysis
Architetture parallele
Casi di studio: smart city
Casi di studio: Smart Cloud
Ontology Building vs Data Harvesting and Cleaning for Smart-city ServicesPaolo Nesi
Presently, a very large number of public and private data sets are available around the local governments. In most cases, they are not semantically interoperable and a huge human effort is needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity and reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to smart-city ontology and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users. The paper presents the process adopted to produce the ontology and the knowledge base and the mechanisms adopted for the verification, reconciliation and validation. Some examples about the possible usage of the coherent knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection. Keywords Smart city, knowledge base construction, reconciliation, validation and verification of knowledge base, smart city ontology, linked open graph.
Similar to Open Urban Platform: Technical View 2018: Km4City (18)
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
1. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT lab, 15 Agust 2017
http://www.disit.org/km4city
Paolo Nesi, paolo.nesi@unifi.it
Open Urban Platform: Technical View 2018
www.Km4City.org
2. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4City: Integrated Urban Platform
DISIT lab, 15 Agust 2017
• Aggregate & integrate data
– Multiple protocols from urban operators, ....
– open data, IOT, sensors, internet of everything,
cloud, mobile devices, Wi-Fi, social media, ...
• Data Exploitation performing
– predictions, reasoning, business intelligence, ..
– users behavior analysis, decision support system, ..
– Control Room, Real Time Monitoring tools, ….
• Produce value from data enabling to
– Stimulate virtuous behavior, influence City Users!
– Put in action CITY Strategies
3. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4City in Tuscany Area
Road Graph (Tuscany region)
132,923 Roads , 389,711 Road Elements
318,160 Road Nodes, 1,508,207 Street Numbers
Info on: points, paths, areas, etc.
Services (20 cat, 512 cat.)
16 Public Transport Operators
21.280 Bus stops & 1081 bus lines
Dynamic/real-time in Tuscany Region
• Real time bus lines: 144 updates X day X line
• 1081 Transport Pub Lines: 1-2 up per day, time-path
• >210 parking lots status: 76 updates X day X sensor
• >796 traffic Sensors: 288 updates X day X sensor
• 285 weather area: 2 updates X day X area
• >12 hospital Triage status: 96 updates X day X FA
• 22 Environmental data: 20 updates X day X sensor
• 39 Bike Sharing data: Pisa and Siena
• 12 Pollination data
• 140 recharging stations
• Smart benches, waste mng, irrigators, lighting,…
• Florence ent.events: about 60 new events X day
• Different kinds of Florence traffic events,
• [1600 Fuel stations: 1 update X day X station]
• Wi-Fi: > 400.000 measures X day
• App mobiles: >50.000 measures X day
• more than 40.000 distinct users X day
• From 600.000 to 4.5 M Tweets X day
• many IOT sensors ……http://servicemap.km4city.org
4. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4City in Tuscany Area
What is enabling and providing smart services
• Smart Parking, in Tuscany
• Smart First Aid in Tuscany
• Smart Fuel pricing in Tuscany
• Smart search for POI and public transport srv.
• Public Transportation in Tuscany
• Routing in Tuscany
• Social Media Monitoring and acting
• Traffic events and Resilience in Florence
• Bike Sharing in Pisa and Siena
• Recharge stations for e-vehicles
• Entertainment Events in Florence
• Traffic Sensors in Tuscany
• Weather forecast/condition in Tuscany
• Pollution and Pollination in Tuscany
• People Monitoring Assessment in the City, in
Florence via WiFi
• People Monitoring, in Tuscany via App
All Point of Interests, cultural activities, IOT, …
Over than 1.2 Million of complex events per day!http://servicemap.km4city.org
5. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Services
• Dashboard and Notifications for Decision Makers
– Control Room Dashboard, Notifications, personalized
– Widgets in third party web pages
• Development Tools for Applications
– Development of Web and Mobile App, HTML5, Open
– Development of IOT Application for all
– Smart City API to access and exploit the city knowledge Km4City
– Easy upload of Data Set and Data Analytics/Processing Processes
– Development Environment for Data Analytics
• Sand Box, VM for developers: ETL, Phython, C/C++, Java, etc.
DISIT lab, Gennaio 2018
6. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Mobile e Web Apps
Tools for Final Users
Km4City Smart City Engine
Transport systems
Mobility, parking
Km4CitySmartCityAPI
Public Services
Govern, events, …
Sensors, IOT
Cameras, ..
Environment,
Water, energy
Social Media
WiFi, network
DISCES--DistributedandparallelarchitectureonCloud
Shops, services,
operators
Km4City
Big Data Analytics
Smartening Tools
Development Tools
Recommender
Personal Assistant
Http://www.km4city.org
Smart Decision Support
Twitter VigilanceServiceMap browser
Analyzers of City User Behavior
Dashboards
City Operators and Decision Makers
DISIT lab, 15 Agust 2017
7. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Cycling Paths
DISIT lab, 15 Agust 2017
8. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org ServiceMap
Search
along a line
Search for
Geo Located
Services
Search around
a GPS point
Search in
an area Get Real Time data
(public busses, car parks,
sensors, traffic flows)
Get
weather
forecast
Get Events
in the city
DISIT lab, 15 Agust 2017
9. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
• Areas, Bus lines, bike lanes, tram, RTZ, etc.
DISIT lab, 15 Agust 2017
Km4City in Firenze
10. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Dashboard vs Data Types
http://www.km4city.org/?controlRoom
DISIT lab, 15 Agust 2017
11. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Filtering data to reach selection
• High Level Types: sensors, special, KPI, POI, etc.
• Nature: accommodation, mobility, financial, wine, health, etc.
– Dashboard → IOT APP, IOT Device to system
• SubNature: a subclassification of the nature
• ValueType: temperature, humidity, memory, pressure, glucose, etc…
• ValueName: name of variable of the: IOT sensor, data, etc.
• DataType: integer, text, Boolean, float, webpage
• LastDate: last date and time of data acquisition
• LastValue: the last value, an example; in some case a parameter
• Healthiness: green or red according to the data quality criteria defined
• LastCheck: date and time of the last valid data
• Ownership: Public or Private; it may be: private, private (Delegated), private
(MyOwn) Snap4City Overview, September 2018 (C) 11
12. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: Complex events
Snap4City Overview, September 2018 (C)
Traffic Events
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
12
13. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: external services
Snap4City Overview, September 2018 (C)
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
13
14. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
External Services
• Twitter Vigilance:
– daily and real time
– Volume and sentiment
analysis
• Traffic Flow
• Services on Maps
• Tracking vehicles
• Real time sensors on 3D
• Web HTML5 Applications
• User behaviour monitoring
Snap4City Overview, September 2018 (C) 14
15. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: MicroApplications
Snap4City Overview, September 2018 (C)
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
15
16. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: Special Widgets
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
Snap4City Overview, September 2018 (C) 16
17. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: POI
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
Snap4City Overview, September 2018 (C) 17
18. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: KPI
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
Snap4City Overview, September 2018 (C)
Real Time
Event Driven
Historical Data
18
19. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets:
Sensors• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
Snap4City Overview, September 2018 (C)
Real Time
Event Driven
Historical Data
19
20. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Data Kinds vs Widgets: KPI
• Complex Event
• External Service
• MicroApplication
• Special Widget
• POI, Point of Interest
• KPI, Key Performance
Indicator
• Sensor
• Sensor-Actuator
• My Personal Data
• Dashboard-IOT App
Snap4City Overview, September 2018 (C) 20
21. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Dashboard intelligence
http://www.km4city.org/?controlRoom
DISIT lab, 15 Agust 2017
22. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
dashboard with intelligence App
• Dashboards with IOT Applications for enforcing smart and
intelligence into them.
DashboardsIOT and City data World IOT Applications
My IOT Devices
Snap4City Overview, September 2018 (C) 22
Applications
23. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Snap4City Overview, September 2018 (C) 23
City Dashboard + IOT App
Control Room Operator
Would like to:
- Monitor traffic flow,
Environment, Car parking,
Cycling, First aid, temp., ..
- Act and monitor Dynamic
Plates
- Act and monitor red lights
Driver, Policeman
Would like to:
- Monitor traffic,
Parking, env., speed
limit, …
- Act and monitor red
lights
24. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
IOT Application with City Dash
simpler development
Snap4City Overview, September 2018 (C) 24
25. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Smart City Control Room
http://www.km4city.org/?controlRoom
DISIT lab, 15 Agust 2017
26. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Sentient City Control Room
DISIT lab, 15 Agust 2017
27. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Transport
systems,
Mobility, Parking
Sensors, IOT
Cameras, ..
Environment,
Water, energy
Shops,
services,
operators
Social Media,
WiFi, Network
Public services,
Govern, EventsDashboards
28. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Snap4City Overview, September 2018 (C) 28
29. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Snap4City Overview, September 2018 (C) 29
https://dashboard.km4city.org/view/index.php?iddasboard=MjY1
https://www.disit.org/dashboardSmartCity/view/index.php?iddasboard=MjI5
https://www.disit.org/dashboardSmartCity/view/index.php?iddasboard=MjQ2 https://www.disit.org/dashboardSmartCity/view/index.php?iddasboard=MjUw
30. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
https://dashboard.km4city.org/view/index.php?iddasboar
d=MTY2
https://dashboard.km4city.org/dashboardSmartCity/view/inde
x.php?iddasboard=MTE5
Snap4City Overview, September 2018 (C) 30
https://dashboard.km4city.org/view/index.php?iddasboard=MjY3 https://dashboard.km4city.org/view/index.php?iddasboard=MjQ3
31. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Snap4City Overview, September 2018 (C) 31
https://dashboard.km4city.org/view/index.php?iddasboard=MTU1 https://dashboard.snap4city.org/dashboardSmartCity/view/index.php?iddas
board=MjY2
• Grid on the frame to simplify the sizing of dash
and widgets
• Spaces among widgets to simplify the reading
• Full set of colour, which can be used more
moderately than us ☺
32. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
33. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Smart City Dashboard
DISIT lab, 15 Agust 2017
34. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
35. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
36. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
37. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
38. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
39. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
40. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
41. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 28 June 2017
42. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, Gennaio 2018
43. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 28 June 2017
44. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 28 June 2017
45. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
(1)
(2a) (2b)
(3) (4)
(7) (10) (8)
(9)
(5)
(6)
(11)
(12)
46. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
(1)
(2)
(3)
(4a) (4b) (4c)
(7)
(5) (6 gas)
(6 calore)
(12)
(11)
(10)
(9)
(8)
(15)
(16)
(14)
(17)
47. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
48. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Wi-Fi OD estimation.
DISIT lab, 15 Agust 2017
49. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org Embedded Widgets
DISIT lab, Gennaio 2018
50. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Smart City Monitoring: Notificator
DISIT lab, 15 Agust 2017
51. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Smart City API
http://www.disit.org/7044
DISIT lab, 15 Agust 2017
52. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Scenarious vs SmartCity API
• Search data: by text, near, along, etc...
– Resolving text to GPS and formal city nodes model
• Empowering the city users
• Access to event information
• Supporting City Users in using Public Mobility
• Supporting City Users in using Private Mobility
• New Experience to access at Cultural and Touristic info
• New way to access at health services
• Access at Environmental information
• Profiled Suggestions to City Users
• Personal Assistant
• Sharing knowledge among cities
DISIT lab, 15 Agust 2017
53. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Thematic Data Domain Tuscany
• Street and geoinformation of the territory and
details for routing, navigation, …
• Mobility and Transport: public and private,
public transport, parking status, fuel
stations prices, traffic sensors, etc.
• Culture and Tourism: POI, churches,
museum, schools, university, theatres,
events in Florence
• Environmental: pollution real time,
weather forecast, etc.
• Social Media: twitter data
• Health: hospital, pharmacies, status
of the first aid triage in major hospitals, …
• Alarms: civil protection alerts,
hot areas, …
DISIT lab, 15 Agust 2017
54. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Concepts of
Services:
Macro and
subcathegory
DISIT lab, 15 Agust 2017
20 Service Macro Classes
Service Class
55. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Access to Point of Interest information, POI
• POI: point of interest
• type: macro and subcategories
• Position: GPS, address, telephone, fax, email, URL, ..
• Description: textual, multilingual, with images, …
• Link to dbPedia, Linked Open Data
• Links to other services
• Real time data if any: sensors data, timeline, events,
prices, opening time, rules of access, status of
services, status of queue, etc..
• See transversal services on ServiceMap
– Regular and in test platform
DISIT lab, 15 Agust 2017
56. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Service Information: different kind of services
DISIT lab, 15 Agust 2017
57. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
General Text Search Features
• Search by text for POIs via
– Full text: description, title, macro and
category name
– Filtering by macro-cat and subcategory
– Filtering on distance and geometric
shape
• Search by text with assisted
suggestion to get:
– Streets and civic numbers, or POI,
locations
DISIT lab, 15 Agust 2017
58. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Search by Shape and Distance
DISIT lab, 15 Agust 2017
Around a point or POI
Inside a closed polyline Along a polyline
Inside an area
Each request or search in the Km4City model
can be referred to a point and a ray, to an area,
to a polyline
59. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Main ServiceMap features
• Search: provides a set of different searches on MAP and LOG
• Save & Get API Call: saves the performed visual query to send via
e-mail the Rest call to the developer
• Save & Get QueryID API Call: saves the performed visual queries
and send via e-mail a Rest call with a simplified syntax referring to
a QueryID and not reporting the complexity of the query.
• Save & Get Embed Code: saves the visual query of the user in
visually recall smart city elements on the map, and gives the
HTML Iframe code for embedding the view on a third party web
page; DISIT lab, 15 Agust 2017
60. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Empowering City Users
• Allow city users to
– provide comments, images and scores
associated with a certain Service (or place,
via GPS)
– Get list of last contributions of the same kind
provided by other users
• They can be:
– used as feedbacks
– moderated by a back office personnel
– ..
• In the future (→) connection with a more
powerful server based on 311 standard
would be possible
DISIT lab, 15 Agust 2017
61. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Access to Event information
• Getting Traffic Events
• Getting Critical Events
• Getting Events in the city
– Theater, museum, show, sport, etc.
– Getting Event details
• Event kind, and thus ordering
• in the day, week, and month
• Location, and thus ordering, or selecting events
per area, per residence
• General information
• Opening and cost (if any)
• Etc.
DISIT lab, 15 Agust 2017
62. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Supporting City Users in using Public Mobility
• Public Transport, PT
– Getting tickets
– Getting bus stops, lines, and timelines for
bus, train and tramline (GTFS, ETL, ..)
– Searching Services along a Pub. Transport
line or closer to a stop
– Searching the closest bus stops
– searching for BUS stops via name
– real time delays of busses
– modal routing for Pub. Transport
DISIT lab, 15 Agust 2017
63. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Supporting City Users using Private Mobility
• Private Transport
– Getting closer parking
– Getting parking forecast
– Getting closer free space on parking
– Getting fuel stations location and fuel product
prices
– Getting bike sharing rack status
– Searching Services along a path or closer to a
point or Service as Hotel, Restaurants, square,
etc.
– Getting closer cycling paths
– Recharging stations: location and status
– Getting traffic information
63
DISIT lab, 15 Agust 2017
64. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Private Mobility: routing
and navigation paths
• To get the path from two
points/POIs:
–Shortest for pedestrian
–Quietest for pedestrian
–Shortest for private vehicles
• Search for POIs along the
identified Path!
• http://www.disit.org/ServiceMap
DISIT lab, 15 Agust 2017
65. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
New Experience to access at Cultural and Touristic info
• Getting location and description of Point of
Interests, POIs: culture and tourism first
– Location, images, phone, URL, etc.
– Get image, video, audio, …
• Search for POIs in areas and closer
• Get routing to reach location or POI by
walking downtown
– searching Services along the path
• Search for location, full text assisted
• Leave a score, take a picture, etc..
DISIT lab, 15 Agust 2017
66. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
New way to access at health services
• Searching for pharmacies and
hospitals
• Getting the closest hospital first
aid locations and status
• Getting real time updated
information about the first aid
status of major hospitals (triage)
DISIT lab, 15 Agust 2017
67. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Access at Environmental information
• Getting weather forecast for the next hours
and days
• Getting alert information from Civil
protection
• Getting air quality status
• Getting pollination status
• getting actual weather status:
temperature, humidity, pressure, rain level,
• etc.
DISIT lab, 15 Agust 2017
68. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Profiled Suggestions to City Users
• Personalized suggestions
– The server provide suggestions in the user
context (location and time) arranged in a
number of categories
• Culture, mobility, food and drink, etc.
• Alerts: civil protection, city council, twitter data, etc.
– The city user may reject some of them, thus
the suggestion engine learns about preferred
topics and category
DISIT lab, 15 Agust 2017
69. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Profiled Engagements to City Users
• The user are profiled to learn habits:
– Personal POI and paths
– Mobility habits
• Information and engagements sent to the city
users are programmed according to the user
evolution to:
– Stimulate virtuous habits
– More sustainable habits
– More healthy habits, etc.
– Get feedbacks
– Provide bonus and prices, …..
– Send alerts, ….
DISIT lab, 15 Agust 2017
Personal Assistant
70. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Monitoring Traffic
Flow and Parking
DISIT lab, 15 Agust 2017
http://www.km4city.org/?controlRoom
71. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Traffic Flows
DISIT lab, 15 Agust 2017
72. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.orgTraffic Flow Tools
• Spire and Virtual Spires (cameras), Bluetooth, ..
• Specifically located: along, around, ..
• Traffic
Tuscany
Pisa
DISIT lab, 15 Agust 2017
73. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Traffic Flow data
74. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org Free Parking space trends
DISIT lab, 15 Agust 2017
Pieraccini Meyer,
Careggi
Beccaria S. Lorenzo
12 parking areas in Florence
75. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Free Parking PREDICTIONS
• Active on Apps
– «Firenze dove cosa»
– «Toscana dove cosa»
DISIT lab, 15 Agust 2017
Careggi car park
Model
features
BRNN model results
R-squared RMSE MASE
Baseline 0.974 24 1.87
Baseline + Weather 0.975 24 1.75
Baseline + Traffic sensors 0.975 24 2.04
Baseline + Weather + Traffic
sensors
0.975 24 1.87
76. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Traffic and People Flow Assessment
• Origin Destination Matrix
– Specific Sensors, vehicle Kits, mobile App,
Wi-Fi Access Points, etc.
• Assess people and traffic flows to
– improve services
– predict critical conditions on Crit. Infra.
– take real time decisions and sending
messages in push to population
– Increase city resilience
– optimize traffic flow
– take decision of routing
77. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Monitoring City users
Via Wi-Fi
DISIT lab, 15 Agust 2017
http://www.km4city.org/?controlRoom
http://www.km4city.org/?devTools
http://www.km4city.org/?infoDocs
http://www.km4city.org/?app
78. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
User Behaviour Analysis
DISIT lab, 15 Agust 2017
• Monitoring movements by traffic
flow sensors
– Spires and virtual spires
• Monitoring movements from
Mobile Cells
– Unsuitable for precise tracking and OD
production
• Monitoring movements from Wi-Fi
• Monitoring movements and much
more from mobile Apps
79. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Predicting Models for Admin. & City Users
• Aiming at improving
– quality of service, distributing workload
– early warning
• Predictions: Short (15 min, 30 Min)
and mid Term (1 week)
• Data Analytics: ML, NLP/SA, Clust…
– Traffic Flows → multiflow reconstruction
– Parking Status → free slots
– People Flows (WiFi, Twitter)
→ crowd , #number of people
DISIT lab, 15 Agust 2017
Predicting at EXPO2015
Early Warning Water Bomb
Early Warning Hot in Tuscany
Predicting City Users on Areas
80. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Real Time Monitoring of Wi-Fi network
DISIT lab, 15 Agust 2017
81. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
WiFi Monitor tool
Recency and frequency
82. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org User Behavior Analysis
DISIT lab, 15 Agust 2017
Distinct APs: 343
Distinct APs (last 24 hours): 311
Distinct Users (last 180 days): 1102098
Distinct Excursionists (last 180 days, < 24 h): 687025
Recency
Where
Excursionists
New City Users
VS
Returning
First Day actions
83. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Characterizing City Areas
Predicting City Areas Crowd level
characterizing Users’ BehaviorsWi-Fi based
DISIT lab, 15 Agust 2017
84. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Cluster confidence
AP average and confidence
Actual AP trend for today
AP prediction for the next time slot in the day on the basis of past weeks
Guessing number of users of Wi-Fi Access Points
Prediction and identification of anomalies
85. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Origin Destination Matrix Estimation
Wi-Fi based
DISIT lab, 15 Agust 2017
86. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Engaging Users
via Mobile App
DISIT lab, 15 Agust 2017
http://www.km4city.org/?controlRoom
http://www.km4city.org/?devTools
http://www.km4city.org/?infoDocs
http://www.km4city.org/?app
87. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
ADK features
• Exploiting Km4City Smart City API
– Open Source
– Multiplatform: exploiting Apache Cordova Framework
– Active since 2015
– Adopted by a community of several Projects, Cities and SME.
• Respecting user privacy:
– Anonymous usage vs Authenticated usage (OAuth, email, ..)
• Modular & Dynamic:
– loading new modules from the WEB, and/or creating App by modular approach
• Personalization and Profiling:
– personalized menu, proposed POI for search,
• Reaching City Users:
– alerting and notifications by location, by user behaviour
DISIT lab, 15 Agust 2017
88. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4CityMobile App
http://www.km4city.org
web application
DISIT lab, 15 Agust 2017
89. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4City APP, features 1/3
• 5 languages: IT, EN, SP, DE, FR
• Profiles city users: Citizens, commuter,
student, tourist, operator, etc..
• Profiled Menu per POI
– adaptive
• Main Menu: dynamic, and personalized
• Search Text
• Search per POI
– Near to you, near to a point, line...
• Other search
– Close to you, events green areas, public
transport, tickets , Cycling, parking, ….
– Etc.
• POI
– Preferred, Social icon
– Ranking, Comments, images
DISIT lab, 15 Agust 2017
90. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4City APP
• Smart Parking, in Tuscany
• Smart First Aid in Tuscany
• Smart Public Transportation in
Tuscany
• Smart Fuel pricing in Tuscany
• Bike Sharing in Pisa
• Weather condition in Tuscany
• Pollution and Pollination in
Tuscany
• Traffic Sensors in Tuscany
• Smart Routing in Tuscany
• Smart Transportation in Florence
• Events, traffic, …
• Entertainment Events in Florence
DISIT lab, 15 Agust 2017
91. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.orgKm4City APP
• Mobility
– Paths and stops, time
– Parching + prediction
– Ticketing
– Flow + prediction
– Navigation
– Connection with devices
– XXX Sharing
• Personal Assistant
– Info, Engagement
– Help, Civil protection
• Suggestions:
– Personalized and adaptive:
banned e typed per city user.
– POI, Twitter, Events,
– Weather forecast,
– Civil Protection
– …
DISIT lab, 15 Agust 2017
92. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Km4City APP, features 3/3
• Navigation 3D (BETA)
• Ticketing for busses
• App used are tool for city assessment
– Wifi status
– iBeacon status
– User behavior analysis
• GPS movements kinds
• OD matrix
• International flows
DISIT lab, 15 Agust 2017
93. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Reasoning on App Data and for App
• Suggestions….
–ML, clustering..
• Engagements….
–Rules systems, ML, city strategies
• User behavior analysis
–Reconstruction of user behavior on t he
move
and in the city in general
–Pedestrian, TPL, Bike, private, etc.
DISIT lab, 15 Agust 2017
94. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
User Behavior Analyzer for Collective profiling
DISIT lab, 15 Agust 2017
Who
When
What
Where?
Why?
How move
Where they go ahead
95. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
OD Matrix scalabile
96. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Anonymous User Behavior Analysis
How city users are moving
Mobile App based
DISIT lab, 15 Agust 2017
97. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Problems of Trajectories from Apps
• From mobile app:
– Resolving GPS location: GPS, cells,
wifi-network, ..mixt
– Noisy, different kind of devices, ..
– Smart algorithm on devices for location
acquisition
– Anonymized data, terms of use on mobile
• Issues and Filtering
– Gps Accuracy, kind of measure (GPS, mixt)
– Jump in time, space, velocity
– General noise (diff. devices)
– Knowledge of precision map
• Clustering: time, space, user kind, etc.
DISIT lab, 15 Agust 2017
• X area, x user type
• Velocity,, Direction
• Time, acceleration
• Vehicle kind ??
• Record and Replay, …
98. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Heat Map from Mobile: users as sensors
DISIT lab, 15 Agust 2017
99. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
User Behavior Analyzer
100. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Inform
You have parked out of your residential parking zone
The Road cleaning is this night
The waste in S.Andreas Road is full
Engage
Provide a comment, a score, etc..
Stimulate / recommend
Events in the city, services your may be interested,
etc..
Provide Bonus
Since you have parked here you we can get 1 Bonus
We suggest you to leave the car out of the city, this
bonus can be used to by a bus ticket
Any Mobile
and Web
App
City & City Operators
Strategy Editor
101. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Engagement & Assisstant Rules
DISIT lab, 15 Agust 2017
• Detecting city users’ habits about mobility
– Private cars → stimulating Bus Usage & Bikes
– Private cars parking → usage of peripheral parking-lot + bus
– Leave the car and take the bus twice → by using bonus, tickets..
– ….. → different solutions for moving…
• Assisting by notifying when one is
– parking out of the residential parking zone
– parking in a zone subjected to cleaning in the next two days
– entering in the restricted traffic zone
• Suggesting you about
– Events, Civil Protection Alerts, …..
– Closer free parking …
• Administering questionnaires
– Getting assessment about services, city experience
– ….
• Requesting ranking, photo and/or comments
102. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, September 2018
103. REWARDING’S RULES
• ASSISTANCE
• If public transport is detected after bus line suggestion on
trajectory usually made on private transport → 10points
– Why don’t you take the bus line 4 in Piazza Marconi to
reach your workplace?You save money, you respect the
environment and you will be stress free for not worry
about parking!
• Once a day, if public transport is detected after suggestion
on an alternative bus line availability →3points
– Why don’t you take the bus line 4 that stop just 50
meters far from you?You save money, you respect the
environment and you will be stress free for the traffic jam!
• If public transport is detected for at least 30(?) minutes a day
→ 1point
• ?parking
• ENGAGEMENT
• Survey on commuter and their preferred way of mobility →
1point
– How many minutes you usually commute to go to work?
How do you rate the service?
• Feedback on public transport →1point
– Which current public transport are you using? Are the
service in line with your expectation?
• Comments/Photo/Rate or survey on POI (public transport)
→1point
• Survey on use of the App after N days or for tourist coming
home → 1point
• Feedback on PPOI or mobility → 1point
• ?events
104. WALLET / PROFILE
• On homepage
– How many points have been distributed?
– How many rewards has been already
delivered?
– How many rewards are still available?
– How many CO2 has been saved?
– How many km our users made this week?
105. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Monitoring City users
Via Social Media
DISIT lab, 15 Agust 2017
http://www.km4city.org/?controlRoom
http://www.km4city.org/?devTools
http://www.km4city.org/?infoDocs
http://www.km4city.org/?app
106. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Twitter Vigilance
• http://www.disit.org/tv
• http://www.disit.org/rttv
• Citizens as sensors to
– Assess sentiment on services,
events, …
– Response of consumers wrt…
– Early detection of critical
conditions
– Information channel
– Opinion leaders
– Communities
– Formation
– Predicting volume of visitors for
tuning the services
DISIT lab, 15 Agust 2017
107. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Real Time Twitter Vigilance, Early Warning
Sentiment Analysis
108. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Prediction/Assessment
• Football game results as related to the volume of Tweets
• Number of votes on political elections,
via sentiment analysis, SA
• Size and inception of contagious diseases
• marketability of consumer goods
• public health seasonal flu
• box-office revenues for movies
• places to be visited, most visited
• number of people in locations like airports
• audience of TV programmes, political TV shows
• weather forecast information
• Appreciation of services
DISIT lab, 15 Agust 2017
109. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
110. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Development Tools
DISIT lab, 15 Agust 2017
http://www.km4city.org/?controlRoom
http://www.km4city.org/?devTools
http://www.km4city.org/?infoDocs
http://www.km4city.org/?app
111. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org Development Tools
• Smart City API:
– Several kind of APIs
• Generator “ServiceMap”,
http://servicemap.km4city.org
– Call per web and mobile App
– Embedding in web pages
– Collaborative work
• Load new data: manual and automatic
– POI, IOT, etc.
– Load of Shape & Paths
– Collaborative work
• Dashboard builder
– Production of dashboard per control room
– Embedding view of any other analytics of Km4City or of third
party: wifi, 3D, flow, recommend, engager, etc.
– Collaborative work
DISIT lab, 15 Agust 2017
112. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Higher level Dashboard
DISIT lab, 15 Agust 2017
113. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Dashboard Builder
DISIT lab, 15 Agust 2017
http://www.disit.org/6935
114. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.orgServiceMap Development Tool
Search
along a line
Search for
Geo Located
Services
Search around
a GPS point
Search in
an area Get Real Time data
(public busses, car parks,
sensors, traffic flows)
Get
weather
forecast
Get Events
in the city
DISIT lab, 15 Agust 2017
115. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org ServiceMap Dev Tool
Search
along a line
Search around
a GPS point
Web App HTML5
Embed into Web pages
http://www.disit.org/6873
SmartCityAPIcallgeneration
Mobile Apps
DISIT lab, 15 Agust 2017
116. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Using and Contributing
to Km4City
DISIT lab, 15 Agust 2017
117. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
• demonstrate Smart City technologies in energy,
transport and ICT in districts in:
– San Sebastian, Florence and Bristol,
– follower cities of Essen, Nilufer and Lausanne
• Cities are the customer: considering local
specificities
• Solutions must be replicable, interoperable and
scalable.
– Integrated Infrastructure: deployment of ICT
architecture, from internet of things to applications
– Low energy districts
– Urban mobility: sustainable and smart urban services
DISIT lab, 15 Agust 2017
1 (coordinator) FOMENTO DE SAN SEBASTIAN FSS SPAIN
2 AYUNTAMIENTO DE SAN SEBASTIAN SAN SEBASTIAN SPAIN
3 COMUNE DI FLORENCE FLORENCE ITALY
4 BRISTOL COUNCIL BRISTOL UNITED KINGDOM
5 STADT ESSEN ESSEN GERMANY
6 NILUFER BELEDIYESI NILUFER TURKEY
7 VILLE DE LAUSANNE LAUSANNE SWITZERLAND
8 IKUSI ANGEL IGLESIAS, S.A. IKUSI SPAIN
9 ENDESA ENERGÍA, S.A. ENDESA SPAIN
10 EUROHELP CONSULTING, S.L. EUROHELP SPAIN
11 ILUMINACION INTELIGENTE LUIX, S.L. LUIX SPAIN
12 FUNDACION TECNALIA RESEARCH & INNOVATION TECNALIA
SPAIN
13 EUSKALTEL, S.A. EUSKALTEL SPAIN
14 COMPAÑÍA DEL TRANVÍA DE SAN SEBASTIÁN DBUS SPAIN
15 CONSIGLIO NAZIONALE DELLE RICERCHE CNR ITALY
16 ENEL DISTRIBUZIONE, SPA ENEL ITALY
17 MATHEMA, SRL MATHEMA ITALY
18 SPES CONSULTING SPES ITALY
19 TELECOM ITALIA, SPA TELECOM ITALY
20 UNIVERSITA DEGLI STUDI DI FLORENCE UNIFI ITALY:
DINFO.DISIT Lab and DIEF
21 THALES ITALIA, SPA THALES ITALY
22 ZABALA INNOVATION CONSULTING ZABALA SPAIN
23 TECHNOMAR TECHNOMAR GERMANY
24 UNIVERSITY OF BRISTOL UOB UNITED KINGDOM
25 UNIVERSITY OF OXFORD UOXF UNITED KINGDOM
26 BRISTOL IS OPEN, LTD BIO UNITED KINGDOM
27 ZEETTA NETWORKS ZEETTA UNITED KINGDOM
28 KNOWLE WEST MEDIA CENTRE, LGB KWMC UNITED KINGDOM
29 TOSHIBA RESEARCH EUROPE, LTD TREL UNITED KINGDOM
30 ROUTE MONKEY, LTD ROUTE MONKEY UNITED KINGDOM
31 ESOTERIX SYSTMES, LTD ESOTERIX UNITED KINGDOM
32 NEC LABORATORIES EUROPE, LTD NEC UNITED KINGDOM
33 COMMONWHEELS CAR CLUB CIC CO-WHEELS UNITED
KINGDOM
34 UNIVERSITY OF THE WEST OF ENGLAND UWE UNITED
KINGDOM
35 ESADE BUSINESS SCHOOL ESADE SPAIN
36 SISTELEC SOLUCIONES DE TELECOMUNICACION, S.L.
SISTELEC SPAIN
http://replicate-project.eu/
118. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
• Experimentations and validation in Tuscany
• Integration with present central station and subsystems
• DISIT lab, Università di Firenze, is the tech-scientific coordinator
Sii-Mobility
DISIT lab, 15 Agust 2017
http://www.Sii-Mobility.org
ECM; Swarco Mizar;
Inventi In20; Geoin;
QuestIT; Softec; T.I.M.E.;
LiberoLogico; MIDRA
(autostrade, motorola);
ATAF; Tiemme; CTT
Nord; BUSITALIA;
A.T.A.M.; Effective
Knowledge; eWings;
Argos Engineering; Elfi;
Calamai & Agresti;
Project; Negentis
119. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
DISIT lab, 15 Agust 2017
Sii-Mobilityhttp://www.Sii-Mobility.org
120. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
General Objectives
• Reduce the social costs of mobility
– minor inconvenience,
– greater efficiency,
– greater sensitivity to the needs of the
citizen,
– lower emissions,
– better environmental conditions;
– info-training programs to help city user in
getting virtuous habits;
– reduce transportation costs and travel
times for users, for operators and
administrations,
– optimization solutions.
DISIT lab, 15 Agust 2017
• simplify the use of mobility systems
– innovative sensors for AVM and
private transport on the territory
– integrated systems for payment and
identification
– driving / offline routing solutions
– connect the drive, smart drive or walk
– Integration of data from operators
and different type sources
– advanced management of resources
measurement of flows realization of
sensors, actuators
• Testing on municipalities and provinces of Tuscany
• Contribute to the improvement of national and international standards
http://www.Sii-Mobility.org
121. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
PA Tipo di atto
Provincia di Prato Delibera di Giunta n.267 del 30.10.2012
Comune di Prato Delibera di Giunta n.474 del 30.10.2012
Provincia di Firenze Delibera di Giunta n.147 del 06.11.2012
Comune di Firenze Delibera di Giunta n.403 del 06.11.2012
Provincia di Pistoia Delibera di Giunta n.156 del 08.11.2012
Comune di Pistoia Delibera di Giunta n.321 del 08.11.2012
Comune di Pisa Delibera di Giunta n.203 del 06.11.2012
Comune di Arezzo Delibera di Giunta n.498 del 07.11.2012
Regione Toscana Delibera di Giunta n.249 del 15.04.2013
DISIT lab, 15 Agust 2017
Principali Delibere su Sii-Mobility
http://www.Sii-Mobility.org
122. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
• Snap4City is an open, standardized, data-driven, service-oriented, user-centric
platform enabling large-scale co-creation IOT/IOE applications.
• Snap4City is a fully open source, robust, scalable, easy to use solution, provides
tools for
– co-creation of mixt data driven, stream and batch processing, extending the powerful
semantic reasoner of Km4City https://www.km4city.org, with IOT/IOE, GDPR, and city
dashboards.
• validated in multiple devices (PC, Android, Raspberry, ..), and domains: mobility
and transport, tourism, health,
welfare, social
• The innovation on semantic
reasoning, IOT interoperability,
microservices, automated
dashboard production, .. thus
• smart city solutions in a
DISIT lab, September 2018
DashboardsIOT and City data World IOT Applications
My IOT Devices
Applications
123. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
http://www.resolute-eu.org
• Develop European Resilience Management
Guidelines (ERMG)
– Develop a conceptual framework for creating/
maintaining Urban Transport Systems
• Enhance resilience through improved support of
human decision making processes, particularly by
training professionals and civil users on the ERMG
and the RESOLUTE system
• Operationalize and validate the ERMG by
implementing the RESOLUTE Collaborative Resilience
Assessment and Management Support Systems
(CRAMSS) for Urban Transport Systems addressing
Road and Urban Rail Infrastructures
– Pilots in Florence and Athens
• Adoption of the ERMG at EU and Associated
Countries level
DISIT lab, 15 Agust 2017
University of Florence:
DISIT lab DINFO (Proj
coordinator), DISIA and DST
UNIFI IT
THALES THALES IT
ATTIKOMetro ATTIKO GR
Comune di Firenze CDF IT
Centre for Research and
Technology Hellas
CERTH GR
Fraunhofer-Gesellschaft zur
Förderung der angewandten
Forschung e.V.
FHG DE
HUMANIST HUMANISTFR
SWARCO Mizar SWMIZ IT
Associação para o
Desenvolvimento da Investigação
no Instituto Superior de Gestão
ADI-ISG PT
Consorzio Milano Ricerche CMR IT
124. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
**
• 6/2018
Roadmap
WEEE
2017-2020
Snap4City• waste
• IOT/IOE
• Monitoring
• Smart City IOT
integration
• Living Lab
• 11/2018
2021
• Smart City vs
IOT, Industria 4.0
Trafair CEF
MOSAIC
ALTAIR
• 12/2018
125. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://www.disit.org
Acknowledgement
• Thanks to the European Commission for founding. All slides reporting logo of RESOLUTE H2020
are representing tools and research founded by European Commission for the RESOLUTE
project. RESOLUTE has received funding from the European Research Council (ERC) under the
European Union's Horizon 2020 research and innovation programme (grant agreement n°
653460).
• Thanks to the European Commission for founding. All slides reporting logo of REPLICATE H2020
are representing tools and research founded by European Commission for the REPLICATE
project. REPLICATE has received funding from the European Research Council (ERC) under the
European Union's Horizon 2020 research and innovation programme (grant agreement n°
691735).
• Thanks to the MIUR for co-fouding and to the University of Florence and companies involved.
All slides reporting logo of Sii-Mobility are representing tools and research founded by MIUR
for the Sii-Mobility SCN MIUR project.
• Thanks to the European Commission for founding. All slides reporting logo of Snap4City
https://www.snap4city.org of Select4Cities H2020 are representing tools and research
founded by European Commission for the Select4Cities project. Select4Cities has received
funding from the European Research Council (ERC) under the European Union's Horizon 2020
research and innovation programme (grant agreement n° 688196)
• Km4City is an open technology exploited by those projects and line of research of DISIT Lab.
Some of the innovative solutions and research issues developed into the above mentioned
projects are also compliant and contributing to the Km4City approach and thus are contributing
to the open Km4City model of DISIT lab.
DISIT lab, September 2018