Esta jornada explicará el concepto de Internet de las Cosas (IoT) y su encaje dentro de las últimas tendencias tecnológicas como Big Data o blockchain. Describirá las tecnologías que lo hacen posible. Ofrecerá ejemplos de aplicación de IoT a diferentes ámbitos como salud, ciudades inteligentes o industria. Identificará su grado de desarrollo actual. Explorará su potencial implantación en nuestras entornos vitales e influencia en nuestras actividades cotidianas en un futuro cercano.
Empowering citizens to turn them into co-creatorsof demand-driven public services. CO-CREATION methodology, supporting platform and tools. Ecosystem of co-created artefacts. Open Government enablling
Two of the main current challenges faced by society are the growing urbanization and ageing of population. ICTs play a key role helping us addressing these socioeconomic problems which are paramount for our future progress. Firstly, this talk will overview the opportunities and strengths brought forward by ICT democratization in all societal sectors to make cities more age-friendly, sustainable, productive and satisfying environments. On the other hand, it will also review the weaknesses and threats associated to the increasing adoption of ICT to face these societal challenges. For instance, it will review the need to capture and process personal information to offer assistance services and ease decision making in cities, together with the threats to privacy that personal data management may cause. Several European projects facing the challenges of Sustainable and Inclusive Cities will be described in order to illustrate the high potential of this idea. Both their scientific-technological contributions and their economic potential will be overviewed, highlighting the potential of the Silver Economy – the new market opened to address the progressive societal ageing. Secondly, this talk will give further details about three core pillars to make reality this idea of more elderly-friendly ambient assisted cities, namely Internet of Things, Big Data and higher stakeholder participation and collaboration. Through use cases extracted from European projects, examples of novel personal health devices connected to Internet, new ways to correlate and process information in order to enhance decision-making and emerging approaches to make elderly people to have a higher involvement and engagement in aspects related to personal autonomy and their higher societal involvement will be provided. Finally, the talk will conclude exemplifying how Spanish administrations are addressing ageing problems through smart healthcare technologies.
Panel #4: Open Knowledge - Data, Citizens and Governance
FIWARE Global Summit
Smart Cities
Participative Cities
Citizen participation
Beyond Open Data Portals
CO-CREATION
Urban Intelligence
Knowledge Graphs
Actionable Knowledge to the service of citizens
Introduction: Technological and methodical pillars for Smarter Environment Enablement
Part I: Smarter Environments Theoretical Grounding
What is a Smart Environment?
Technological enablers: IoT, Web of Data and Persuasive Technologies
Technology mediated Human Collaboration: need for co-creation
Killer application domains: Open Government & Age-friendly cities
Part II: Review of core enablers for Smarter Environments
Co-creation methodologies: Design for Thinking
Internet of Things and Web of Things
Web of Data: Linked Data, Crowdsourcing & Big Data
Part III: WeLive Case Study
WeLive as Open Government enabling methodology and platform
Reflections on the need for collaboration among stakeholders to realize Smarter Cities
Conclusions and practical implications
This presentation overviews the reseach areas, active project and scientific contributions produced by DeustoTech-INTERNET and the MORElab research group (http://www.morelab.deusto.es)
Introduction: Technological and methodical pillars for Smarter Environment Enablement
Part I: Smarter Environments Theoretical Grounding
What is a Smart Environment?
Technological enablers: IoT, Web of Data and Persuasive Technologies
Technology mediated Human Collaboration: need for co-creation
Killer application domains: Open Government & Age-friendly cities
Part II: Review of core enablers for Smarter Environments
Co-creation methodologies: Service Design and Design for Thinking
Internet of Things and Web of Things
Web of Data: Linked Data, Crowdsourcing & Big Data
Persuasive technologies and Behaviour Change
Part III: Implications for CyberParks
European projects on enabling Smarter Environments: WeLive, City4Age, GreenSoul
Reflections on the need for collaboration among stakeholders mediated with technology to realize CyberParks
Conclusions and practical implications
Empowering citizens to turn them into co-creatorsof demand-driven public services. CO-CREATION methodology, supporting platform and tools. Ecosystem of co-created artefacts. Open Government enablling
Two of the main current challenges faced by society are the growing urbanization and ageing of population. ICTs play a key role helping us addressing these socioeconomic problems which are paramount for our future progress. Firstly, this talk will overview the opportunities and strengths brought forward by ICT democratization in all societal sectors to make cities more age-friendly, sustainable, productive and satisfying environments. On the other hand, it will also review the weaknesses and threats associated to the increasing adoption of ICT to face these societal challenges. For instance, it will review the need to capture and process personal information to offer assistance services and ease decision making in cities, together with the threats to privacy that personal data management may cause. Several European projects facing the challenges of Sustainable and Inclusive Cities will be described in order to illustrate the high potential of this idea. Both their scientific-technological contributions and their economic potential will be overviewed, highlighting the potential of the Silver Economy – the new market opened to address the progressive societal ageing. Secondly, this talk will give further details about three core pillars to make reality this idea of more elderly-friendly ambient assisted cities, namely Internet of Things, Big Data and higher stakeholder participation and collaboration. Through use cases extracted from European projects, examples of novel personal health devices connected to Internet, new ways to correlate and process information in order to enhance decision-making and emerging approaches to make elderly people to have a higher involvement and engagement in aspects related to personal autonomy and their higher societal involvement will be provided. Finally, the talk will conclude exemplifying how Spanish administrations are addressing ageing problems through smart healthcare technologies.
Panel #4: Open Knowledge - Data, Citizens and Governance
FIWARE Global Summit
Smart Cities
Participative Cities
Citizen participation
Beyond Open Data Portals
CO-CREATION
Urban Intelligence
Knowledge Graphs
Actionable Knowledge to the service of citizens
Introduction: Technological and methodical pillars for Smarter Environment Enablement
Part I: Smarter Environments Theoretical Grounding
What is a Smart Environment?
Technological enablers: IoT, Web of Data and Persuasive Technologies
Technology mediated Human Collaboration: need for co-creation
Killer application domains: Open Government & Age-friendly cities
Part II: Review of core enablers for Smarter Environments
Co-creation methodologies: Design for Thinking
Internet of Things and Web of Things
Web of Data: Linked Data, Crowdsourcing & Big Data
Part III: WeLive Case Study
WeLive as Open Government enabling methodology and platform
Reflections on the need for collaboration among stakeholders to realize Smarter Cities
Conclusions and practical implications
This presentation overviews the reseach areas, active project and scientific contributions produced by DeustoTech-INTERNET and the MORElab research group (http://www.morelab.deusto.es)
Introduction: Technological and methodical pillars for Smarter Environment Enablement
Part I: Smarter Environments Theoretical Grounding
What is a Smart Environment?
Technological enablers: IoT, Web of Data and Persuasive Technologies
Technology mediated Human Collaboration: need for co-creation
Killer application domains: Open Government & Age-friendly cities
Part II: Review of core enablers for Smarter Environments
Co-creation methodologies: Service Design and Design for Thinking
Internet of Things and Web of Things
Web of Data: Linked Data, Crowdsourcing & Big Data
Persuasive technologies and Behaviour Change
Part III: Implications for CyberParks
European projects on enabling Smarter Environments: WeLive, City4Age, GreenSoul
Reflections on the need for collaboration among stakeholders mediated with technology to realize CyberParks
Conclusions and practical implications
WeLive project Open Government We-Government Tools Open Innovation Open Services Open Data Focus Groups Public Service Apps Bilbao Smart Cities Sustainable Participative Cities
The quest for realizing Smart Environments has taken place for the last 30 years. Diverse adaptations of the original UbiComp vision have been developed, each highlighting diverse aspects who have been considered critical to enable a wider and more acceptable adoption of Smart Environments. Notable examples of such interesting adaptations are Context-aware Computing, Sentient Computing, Ambient Intelligence, Ambient Assisted Living and Internet of Everything. Under those different umbrella terms, researchers have explored the 3 stage enabling equation for Smart Environments, i.e. “SENSE + PROCESS = ACT”, i.e. spaces where the environment is aware of the needs, profiles and preferences from the sensed users and accommodates its behaviour to ease their daily interactions. Contributions around these different perspectives and applied to distinct environments, i.e. Smart Offices, Smart Homes, Smart Factories or Smart Cities, have been produced, all addressing the challenges posed by ever more complex systems of systems populated by multiple users. This talk will exemplify research results on how to accomplish these three core steps. Firstly, in the SENSE part, the importance of location sensing and the spread of low cost highly dense sensing environments (RFID, NFC or low range Bluetooth) will be described. Secondly, the PROCESS stage where ever more sophisticated analytics mechanisms to take into account historic and real-time data are considered, combining domain-driven (rules) and data-driven solutions, will be analysed. Thirdly, the ACT stage will be explored, considering the evolution from reactive to learning persuasive environments which aim to collaborate with their users. Thus, a middle ground fostering collaboration between smart things and people will be defended giving place to Smarter environments. The implications of the Smarter environments approach will be illustrated with use cases in the Open Government and Efficient Energy Management domains.
This paper describes the WeLive framework, a set of tools to enable co-created urban apps by means of bringing together Open Innovation, Open Data and Open Services paradigms.
Proposes a more holistic involvement of stakeholders across service ideation, creation and exploitation WeLive co-creation process
The two-phase evaluation methodology designed and the evaluation results of pre-pilot sub-phase are also presented.
Including early user experience evaluation for WeLive
Introduction:
Context: societal urbanization and ageing
Interdependence analysis: Ambient Assisted Cities
ICT & Social Innovation leading towards Smarter Cities
Technologies for enablement of Smarter Cities:
Internet of Things
Web of Data
Crowdsourcing
Building Smarter Cities
Broad Data Analysis Tools
European projects about Smarter Ambient Assisted Cities
Conclusion
From 2020 to 2025, the annual growth rate of the global smart city market is 14.8%, reaching US$820.7 billion.
This is the result of a market survey conducted recently by market analysts.
The most interesting aspect of the report did not appear in the data, and the data hardly explained anything. Instead, we should see this in the logic of the ecosystem in which they are located. An ecosystem involving not only public administration and local authorities, but also citizens, utility companies, and technology suppliers (hardware and software) gives us a rough idea of what we expect in the next five years.
Let us understand the results of the research in more detail.
Bordeaux - Operating Urban Data Platforms based on Minimal Interoperability M...Open & Agile Smart Cities
Presentation given by Christophe Colinet, City of Bordeaux at Open & Agile Smart Cities' annual Connected Smart Cities & Communities Conference 2020 on 23 January in Brussels, Belgium.
Smart cities or smart citizens : which is the future?Naba Barkakati
A brief talk on smart cities or smart citizens, which is the future?
For more see http://nbtmv.blogspot.com/2016/03/smart-cities-or-smart-citizens-which-is.html
Presentation installed at the Invisible Cities Graduate Symposium and Expo, held in Kitchener, Ontario on October 26th, 2013 through the University of Waterloo's Critical Media Lab. This presentation summarizes my research on smart city technology and the idea of using big data to better understand cities.
Alex Gluhak & Michael Nilsson - Smart CitiesFIA2010
Alex Gluhak & Michael Nilsson
Part I: Experimentation and Innovation Facilities for Smart Cities – Opportunities and Needs,
Part II: Collaboration Requirements and Opportunities in the Future Internet, Living Labs and Smart City Communities
Internet of People is a new computing paradigm designed to enable Smart Sustainable Places which follow Social Good principles
Smart Sustainable Places =
IoT +
Big Data +
Blockchain +
People Participation through CO-PRODUCTION
Smart Cities are all about collaboration, sharing and transparency. They need true openness of data. It is not just governments opening up their data for everyone in public platforms. It is individual citizens and privately-owned companies offering their data to the government or government departments sharing their data with one another. That is the true meaning of ‘Open Data’, which goes beyond the traditional definitions. Because Smart Cities eat the ‘status quo’ for breakfast. They change at the speed of light, together with their environment. They are the cities of the future.
A smart city / Region with smart citizen and smart business
ecosystem. - prezentacja Sergiego Figueroli podczas konferencji „SMART_KOM. Kraków w sieci inteligentnych miast”, 7.11.2014 r., Kraków
WeLive project Open Government We-Government Tools Open Innovation Open Services Open Data Focus Groups Public Service Apps Bilbao Smart Cities Sustainable Participative Cities
The quest for realizing Smart Environments has taken place for the last 30 years. Diverse adaptations of the original UbiComp vision have been developed, each highlighting diverse aspects who have been considered critical to enable a wider and more acceptable adoption of Smart Environments. Notable examples of such interesting adaptations are Context-aware Computing, Sentient Computing, Ambient Intelligence, Ambient Assisted Living and Internet of Everything. Under those different umbrella terms, researchers have explored the 3 stage enabling equation for Smart Environments, i.e. “SENSE + PROCESS = ACT”, i.e. spaces where the environment is aware of the needs, profiles and preferences from the sensed users and accommodates its behaviour to ease their daily interactions. Contributions around these different perspectives and applied to distinct environments, i.e. Smart Offices, Smart Homes, Smart Factories or Smart Cities, have been produced, all addressing the challenges posed by ever more complex systems of systems populated by multiple users. This talk will exemplify research results on how to accomplish these three core steps. Firstly, in the SENSE part, the importance of location sensing and the spread of low cost highly dense sensing environments (RFID, NFC or low range Bluetooth) will be described. Secondly, the PROCESS stage where ever more sophisticated analytics mechanisms to take into account historic and real-time data are considered, combining domain-driven (rules) and data-driven solutions, will be analysed. Thirdly, the ACT stage will be explored, considering the evolution from reactive to learning persuasive environments which aim to collaborate with their users. Thus, a middle ground fostering collaboration between smart things and people will be defended giving place to Smarter environments. The implications of the Smarter environments approach will be illustrated with use cases in the Open Government and Efficient Energy Management domains.
This paper describes the WeLive framework, a set of tools to enable co-created urban apps by means of bringing together Open Innovation, Open Data and Open Services paradigms.
Proposes a more holistic involvement of stakeholders across service ideation, creation and exploitation WeLive co-creation process
The two-phase evaluation methodology designed and the evaluation results of pre-pilot sub-phase are also presented.
Including early user experience evaluation for WeLive
Introduction:
Context: societal urbanization and ageing
Interdependence analysis: Ambient Assisted Cities
ICT & Social Innovation leading towards Smarter Cities
Technologies for enablement of Smarter Cities:
Internet of Things
Web of Data
Crowdsourcing
Building Smarter Cities
Broad Data Analysis Tools
European projects about Smarter Ambient Assisted Cities
Conclusion
From 2020 to 2025, the annual growth rate of the global smart city market is 14.8%, reaching US$820.7 billion.
This is the result of a market survey conducted recently by market analysts.
The most interesting aspect of the report did not appear in the data, and the data hardly explained anything. Instead, we should see this in the logic of the ecosystem in which they are located. An ecosystem involving not only public administration and local authorities, but also citizens, utility companies, and technology suppliers (hardware and software) gives us a rough idea of what we expect in the next five years.
Let us understand the results of the research in more detail.
Bordeaux - Operating Urban Data Platforms based on Minimal Interoperability M...Open & Agile Smart Cities
Presentation given by Christophe Colinet, City of Bordeaux at Open & Agile Smart Cities' annual Connected Smart Cities & Communities Conference 2020 on 23 January in Brussels, Belgium.
Smart cities or smart citizens : which is the future?Naba Barkakati
A brief talk on smart cities or smart citizens, which is the future?
For more see http://nbtmv.blogspot.com/2016/03/smart-cities-or-smart-citizens-which-is.html
Presentation installed at the Invisible Cities Graduate Symposium and Expo, held in Kitchener, Ontario on October 26th, 2013 through the University of Waterloo's Critical Media Lab. This presentation summarizes my research on smart city technology and the idea of using big data to better understand cities.
Alex Gluhak & Michael Nilsson - Smart CitiesFIA2010
Alex Gluhak & Michael Nilsson
Part I: Experimentation and Innovation Facilities for Smart Cities – Opportunities and Needs,
Part II: Collaboration Requirements and Opportunities in the Future Internet, Living Labs and Smart City Communities
Internet of People is a new computing paradigm designed to enable Smart Sustainable Places which follow Social Good principles
Smart Sustainable Places =
IoT +
Big Data +
Blockchain +
People Participation through CO-PRODUCTION
Smart Cities are all about collaboration, sharing and transparency. They need true openness of data. It is not just governments opening up their data for everyone in public platforms. It is individual citizens and privately-owned companies offering their data to the government or government departments sharing their data with one another. That is the true meaning of ‘Open Data’, which goes beyond the traditional definitions. Because Smart Cities eat the ‘status quo’ for breakfast. They change at the speed of light, together with their environment. They are the cities of the future.
A smart city / Region with smart citizen and smart business
ecosystem. - prezentacja Sergiego Figueroli podczas konferencji „SMART_KOM. Kraków w sieci inteligentnych miast”, 7.11.2014 r., Kraków
The Internet of Things (IoT) is the network of physical objects or "things" embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange data. .The Internet of Things allows objects to be sensed and controlled remotely across existing network infrastructure .
In the era of digital transformation, the concept of Digital Twins has emerged as a revolutionary approach to managing and optimizing the lifecycle of physical assets, systems, and processes. This talk delves into the transformative potential of Digital Maintenance in the Digital Twin Era, highlighting the seamless integration of digital replicas with real-world operations to foster unprecedented levels of efficiency, predictability, and sustainability in maintenance practices. We will explore how Digital Twins serve as dynamic, real-time reflections of physical assets, allowing for meticulous monitoring, analysis, and simulation. Through vivid examples, we'll demonstrate the benefits of this paradigm, such as predictive maintenance, which leverages data analytics and machine learning to anticipate failures and optimize maintenance schedules, thereby reducing downtime and extending asset lifespan. Further, the talk will showcase the role of Digital Twins in facilitating remote maintenance operations. By providing a comprehensive, virtual view of assets, maintenance professionals can perform diagnostics and identify issues without being physically present, enhancing safety and reducing response times. We'll also explore the environmental benefits of Digital Maintenance within the Digital Twin framework. By optimizing maintenance schedules and operations, organizations can significantly reduce their carbon footprint and resource consumption, contributing to more sustainable industrial practices. Finally, the presentation will highlight case studies from various industries, including manufacturing, energy, and transportation, where the adoption of Digital Twins has led to substantial cost savings, improved operational efficiency, and enhanced decision-making processes. These examples will illustrate the tangible value and competitive advantage that Digital Maintenance in the Digital Twin Era offers to forward-thinking organizations.
Large Techno Social Systems (LTSS) involve leveraging technological advancements and digital platforms to improve access to essential services, enhance quality of life, and ensure social inclusivity. In LTSS, people cannot be mere users of networked technologies and services designed for optimization purposes. Their behaviour should become one of the key levers for designing technologies turning them into real “Smart citizens” that teach their surrounding environment (and embedded devices) but learn reciprocally from it. LTSS can be realized by promoting smart communities which leverage technology, data, and innovation to improve the quality of life for its residents, enhance sustainability, and optimize the use of resources. Human-centric technology can empower citizens to actively engage in societal decision-making processes, participate in deliberative systems, and contribute to societal welfare. On the other hand, technological advancements, including data analytics and artificial intelligence, can inform evidence-based policymaking and planning processes. Indeed, digital technologies have the potential to influence human behaviour change by providing information, personalized feedback, social support, targeted interventions, and opportunities for learning. This work explores two approaches to realize LTSS driven smart communities that leverage digital technologies to achieve a higher collaboration and reciprocal learning between machines and people. On one hand, co-production in smart communities promotes behaviour change by empowering citizens in the co-design and co-delivery process, designing user-centric solutions, leveraging local knowledge, fostering collaboration, and facilitating capacity building. On the other hand, Citizen Science can inspire and enable behaviour change that leads to more sustainable, responsible, and community-oriented actions by promoting awareness, empowering individuals, and facilitating collaboration.
realizing human-centric innovation around public services
From data collector to co-researcher - how to successfully collaborate with society
Delivered to UNIC CityLab 10 November 2022, 10:00-12:00, https://unic.eu/en
Towards more citizen-centric and sustainable public services
INTERLINK co-production methodology
INTERLINK’s key principles and concepts
INTERLINK Collaborative Environment
INTERLINK: co-production of public services
A public service is an aggregation of all activities that realize a public authority's commitment to make available to individuals, businesses, or other public authorities some capabilities intended to answer their needs, giving them some possibilities to control whether, how and when such capabilities are manifested
Co-production is defined as the process in which services are jointly designed and/or delivered by public authorities and other stakeholders
FAIR Data
Principles
FAIR vs Open Data
Implementing FAIR & FAIRmetrics
FAIRness de ASIO-HERCULES
Research Objects
Definition
Standard RO-CRATE
Usage examples
What is linked data
What is open data
What is the difference between linked and open data
How to publish linked data (5-star schema)
The economic and social aspects of linked data.
Introducción a la Web de Datos
Grafos de Conocimiento
Web Semántica
Ontologías
Linked Data: Wikidata & Dbpedia
Ontología ROH: Red de Ontologías Hércules
Proceso de diseño de la ontología
Descripción de la ontología en detalle
Entidades principales explicadas en base a casos de uso
Generación de datos: IoP & Citizen science
Explosión datos + IA = Economía de Datos
Data Marketplaces: EDI & REACH
Explotación de los datos:
Ciudadanos co-idean, co-crean y co-explotan (WeLive)
Colaboración sostenible entre ciudadanos y personas (AUDABLOK)
More from Diego López-de-Ipiña González-de-Artaza (20)
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Essentials of Automations: Optimizing FME Workflows with Parameters
Internet de las Cosas: del Concepto a la Realidad
1. 1
Internet de las Cosas: del Concepto a la
Realidad
CETIC (Centro de Tecnologías de la Información y Comunicación), Vitoria-Gasteiz
29 de Mayo de 2018, 18:00-20:30
Dr. Diego López-de-Ipiña González-de-Artaza
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina
http://www.morelab.deusto.es
@dipina
2. 2
Abstract
Esta jornada explicará el concepto de Internet de las Cosas (IoT)
y su encaje dentro de las últimas tendencias tecnológicas como
Big Data o blockchain. Describirá las tecnologías que lo hacen
posible. Ofrecerá ejemplos de aplicación de IoT a diferentes
ámbitos como salud, ciudades inteligentes o industria.
Identificará su grado de desarrollo actual. Explorará su potencial
implantación en nuestras entornos vitales e influencia en
nuestras actividades cotidianas en un futuro cercano.
3. 3
Agenda
1. ¿Qué es la Internet de las Cosas (IoT)?
2. Encaje dentro del ámbito tecnológico actual: Web de Datos,
Cloud Computing, Big Data y Blockchain
3. Tecnologías que hacen posible IoT: RFID, NFC, Arduino, Fog
Computing, Blockchain …
4. Áreas de aplicación de la IoT: Smart Cities, Salud e industria
4.0
5. Casos de éxito de IoT
6. IoT como habilitador de Servicios Inteligentes Personalizados
7. Conclusión
4. 4
Misión de la Future Internet (FI)
• Ofrecer a todos los usuarios un entorno seguro,
eficiente, confiable y robusto, que:
– Permita un acceso abierto, dinámico y
descentralizado a la red y a su información y
– Sea escalable, flexible y adapte su rendimiento a
las necesidades de los usuarios y su contexto
5. 5
Los Pilares de la Internet del
Futuro
• La Internet del Futuro consta de 4 pilares apoyados
en una nueva infraestructura de red como base:
– Internet Por y Para la Gente
– Internet de los Contenidos y del Conocimiento
– Internet de los Servicios
– Internet de las Cosas
7. 7
Internet de las Cosas (IoT):
Motivación
• ¿Quieres saber cuántos pasos
has andado?
• ¿Los kilómetros que has
conducido?
• ¿Los watios que has consumido?
• ¿Cómo mejorar la eficiencia y
seguridad en tu fábrica?
• Internet de las Cosas te puede
decir eso y mucho más
12. 12
Historia IoT
• El concepto de dispositivo
inteligente conectado fue
acuñado en 1982 con máquina
expendedora conectada en
CMU
• El artículo de Mark Weiser en
1991 "The Computer of the
21st Century", y los conceptos
académicos de UbiComp y
PerCom fueron el germen de
IoT
• El término IoT fue acuñado
por Kevin Aston del MIT en
1999
13. 13
Internet of Things: Definition (I)
• Internet of Things (IoT) is a dynamic global network
infrastructure with self-configuring capabilities based on
standard and interoperable communication protocols where
physical and virtual “things” have identities, physical
attributes and virtual personalities and use intelligent
interfaces and are seamlessly integrated into the information
network.
from the IERC (the European Research Cluster on Internet of Things
http://www.internet-of-things-research.eu/)
– Things can range from tagged objects (RFID, NFC, QR codes, Barcodes,
Image Recognition) to Wireless Sensor Networks (WSN), machines,
vehicles and consumer electronics
14. 14
Internet of Things: Definition (II)
• The internet of things (IoT) is the network of physical
devices, vehicles, buildings and other items—
embedded with electronics, software, sensors, and
network connectivity that enables these objects to
collect and exchange data
– Opportunity for more direct integration of the physical
world into computer-based systems, and resulting in
improved efficiency, accuracy and economic benefit
– Encompasses technologies such as Smart Grids, Smart
Homes, Intelligent Transportation and Smart Cities
15. 15
6 facts about IoT
1. IoT is the term used to describe any kind of application that
connected and made “things” interact through the Internet
2. IoT is a communication network connecting things which
have naming, sensing and processing abilities
3. IoT is the next stage of the information revolution, i.e. the
inter-connectivity of everything from urban transport to
medical devices to household appliances
4. Intelligent interactivity between human and things to
exchange information & knowledge for new value creation
5. IoT is not just about gathering of data but also about the
analysis and use of data
6. IoT is not just about “smart devices”; it is also about devices
and services that help people become smarter
20. 20
Internet de las Cosas
• Red universal de objetos interconectados
y direccionables basada en protocolos de
comunicación estándar
– IoT exhibirá un alto nivel de heterogeneidad,
combinando objetos de distinta funcionalidad,
tecnología o campos de aplicación
– Protocolos semánticos noveles serán
desarrollados para permitir a IoT escalar y
coordinar a los millones de objetos que nos
rodean
– RFID y redes de sensores proporcionan un
mecanismo de bajo coste y robusto de
identificación y sensibilidad al contexto
• El uso de Internet pasará de modelo
request/reply a push-and-process
22. 22
IoT: 3rd wave of Internet
• Key attributes that distinguish IoT from “regular” Internet, as
captured by Goldman Sachs’s S-E-N-S-E framework: Sensing,
Efficient, Networked, Specialized, Everywhere
23. 23
Internet of Things (IoT) Promise
• There will be around 25 billion devices connected to the
Internet by 2015, 50 billion by 2020
– A dynamic and universal network where billions of identifiable
“things” (e.g. devices, people, applications, etc.) communicate
with one another anytime anywhere; things become context-
aware, are able to configure themselves and exchange
information, and show “intelligence/cognitive” behaviour
24. 24
Internet of Everything (I)
• CISCO view: “From the Internet of Things (IoT), where we are today, we
are just beginning to enter a new realm: the Internet of Everything (IoE),
where things will gain context awareness, increased processing power,
and greater sensing abilities”
– IoE brings together people, process, data, and things to make networked
connections more relevant and valuable than ever before-turning information
into actions that create new capabilities, richer experiences, and
unprecedented economic opportunity.
27. 27
Rapid growth of connected things
"Fixed" computing Mobility/BYOD Internet of things Internet of everything
Source: Cisco IBSG, 2013
(you go to the device) (the device goes with you) (age of devices) (people, process, data, things)
1995 2000 2013 2020
200M
10B
50B
28. 28
IoT Predictions (by 2020-22)
7,1tn IoT Solutions Revenue | IDC
1,9tn IoT Economic Value Add | Gartner
309bn IoT Supplier Revenue | Gartner
50bn Connected Devices | Cisco
14bn Connected Devices | Bosch SI
http://postscapes.com/internet-of-things-market-size
Peter Middleton, Gartner:
“By 2020, component
costs will have come
down to the point that
connectivity will become a
standard feature, even for
processors costing less
than
$1
“
30. 30
Tipos de Internet de las Cosas
• Al menos dos sabores:
– Consumer IoT (CIoT): orientada a consumidores
– Industrial IoT (IIoT)
• Industria 4.0
31. 31
Consumer Internet of Things (CIoT)
• The Consumer Internet of Things (CIoT) represents
the class of consumer-oriented applications where:
– Devices are consumer devices, such as smart appliances,
e.g. refrigerator, washer, dryer, personal gadgets such as,
fitness sensors, Google Glasses, etc.
– Data volumes and rates are relatively low
– Applications are not mission or safety critical, e.g., the
failure of fitness gadget will make you, at worse, upset, but
won’t cause any harm
– CIoT applications tend to be “consumer-centric”
35. 35
Quantified Self & Life
Logging
• Quantified self is self-knowledge through self-tracking with technology
– Movement to incorporate technology into data acquisition on aspects of a
person's daily life in terms of inputs (e.g. food consumed, quality of
surrounding air), states (e.g. mood, arousal, blood oxygen levels), and
performance (mental and physical)
• Self-monitoring and self-sensing through wearable sensors (EEG, ECG, video, etc.)
and wearable computing lifelogging
• Application areas:
– Health and wellness improvement
– Improve personal or professional productivity
• Products and companies:
– Apple Watch, Fitbit tracker, Jawbone UP, Pebble, Withings scale
37. 37
Google Glass
• Su misión es producir un ubiquitous computer de venta
masiva
– Lanzadas para los desarrolladores de Google I/O por
1500$ en el año 2013
• Renovadas en 2017 con Google Glass Enterprise Edition
• Muestra información disponible sin utilizar las manos,
accede a Internet mediante órdenes de voz, de manera
comparable a Google Now
38. 38
• Google Home
– Features
• Amazon Echo
– Alexa API
Audible Computing
• Apple AirPods
– Comparison
39. 39
Features of Audible Computing
Products
Google Home Amazon Echo
Price $130 $180
Responds to voice
commands
Yes Yes
Always listening Yes Yes
Wake word "Okay Google" Alexa, Echo, or Amazon
Music streaming
options
Google Play Music, YouTube Music, Spotify, Pandora,
iHeartRadio, TuneIn, others
Amazon Prime Music, Spotify, Pandora,
iHeartRadio, TuneIn, others
Smart home
partnerships
Nest, SmartThings, Philips Hue, IFTTT
Nest, Ecobee, SmartThings, Wink, Insteon,
Belkin WeMo, Philips Hue, Lifx, Big Ass Fans,
IFTTT, other devices via "skills"
Customizable
appearance
Yes No
Output to stereo
system
Yes, via Chromecast No (yes with Amazon Dot)
Synced audio playback
to multiple devices
Yes, to any Google Cast device No
Personal assistant
highlights
Search Google, get a personalized daily briefing, check
traffic, add items to calendar, make a shopping list,
make a to do list, check flight status, track a package
Add items to calendar, make a shopping list,
make a to do list, check flight status, track a
package
Other features
Cast to your TV with Chromecast, launch and control
Netflix and YouTube via Chromecast, send photos to
your TV via Chromecast
Order a pizza, play a game, arrange an Uber
pickup. Echo has an ever-growing list of 900+
skills and counting
https://www.cnet.com/news/google-home-vs-amazon-echo/
40. 40
Industrial Internet of Things (IIoT)
• The Industrial Internet of Things (IIoT)
represents industry-oriented applications
where:
– Devices are machines operating in industrial,
transportation, energy or medical
environment
– Data volumes and rates tend to be from
sustained to relatively high
– Applications are mission and or safety
critical, e.g. the failure of a smart grid has
severe impact on our life and economy, the
misbehaving of a smart traffic system can
threaten drivers
– IIoT applications tend to be “system centric”
41. 41
Differences among IoT, M2M & CPS
• Not clear cut distinction, these terms are often used
interchangeably;
– M2M– Machine-to-Machine
• TelCo world origins, tied to the network implications of connecting
machines rather than people, explosion of # of connections with limited
bit-rate, ETSI is the main standardisation body; think of telemetry
applications
– M2M is the glue of the IoT
– CPS – Cyber Physical Systems
• Merging real and virtual (cyber) worlds, focusing on systems that based
on duly sampled representation of the physical world can intervene
through digitized actuators to change behaviours in the physical world;
think of car ABS
– CPS is the science bricks behind IoT
– IoT hailed as a broader concept, where the focus is more on wide
applications
42. 42
Smart Grid
• A Smart Grid is an
electrical grid which
includes a variety of
operational and
energy measures
including smart
meters, smart
appliances,
renewable energy
resources, and
energy efficiency
resources.
45. 45
Industry 4.0
• Industry 4.0, Industrie 4.0 or the fourth industrial revolution,
is the current trend of automation and data exchange in
manufacturing technologies.
– It includes cyber-physical systems, the Internet of Things and Cloud
Computing.
– Industry 4.0 creates what has been called a "smart factory".
47. 47
Industry 4.0: Features
• Ingredients for paradigm shift in manufacturing: autonomous robotics, additive
manufacturing (3D printing), cloud computing and sensor technology (IoT)
• Opportunities for innovation in terms of:
– Smarter industrial processes
– New business models and
– Customised products
• The new technological wave builds on the concept of cyber-physical systems:
profound interaction of the real and virtual worlds in the manufacturing process
48. 48
Top 5 IoT Trends to Look Forward
to in 20181. Trend #1 Digital Twin
– Virtual clone of the real-world thing. It is a looking glass into what’s happening within physical assets.
Allows product developers to create, test, build, monitor, maintain and service products in a virtual
environment
2. Trend #2 Blockchain
– Blockchain for IoT can transform the way business transactions are conducted globally by providing a
trustworthy environment. Advantages: a) build trust; b) reduce costs; and c) accelerate transactions.
3. Trend #3 Security
– As we rely on connected devices to make our lives better and easier, security is a must. All participants
in the IoT ecosystem are responsible for the security of the devices, data and solutions.
4. Trend #4 SaaS
– Many IoT implementations still require on-prem implementations. There will be more (and very clear)
instances where Software as a Service (SaaS) is a viable option.
5. Trend #5 Cognitive Computing
– For over a decade we’ve connected things with unique IP addresses. But the commoditization of
sensors, processors and memory now make it possible to makes everyday things more than just
connected … they can be intelligent. It increases the possibilities of what can be done with edge
analytics – making sensors capable of diagnosing and adapting to their environment without the need
for human intervention.
49. 49
Blockchain in a nutshell 101
• A blockchain is a decentralized, distributed and incorruptible digital ledger that is used to
record transactions across many computers.
– Distributed network of computers (nodes)
– where each node contains a chain-of-blocks
– where each block contains a ledger with a list of transactions
– where each transaction is incorruptible (i.e. cryptographically secure)
– & is linked to the previous transactions for the resource it is representing.
• Exemplary use cases:
– Record exchange of money;
– Document the way goods move through a supply chain;
– Create and store contractual agreements.
• Main features:
– Distributed – the record is shared, and cannot be controlled by any single person.
– Permissioned – each participant has secure access to the record
– Secure (incorruptible) – records are safe from manipulation; consensus is required. Everything
stored on the blockchain is encrypted.
• H(this-block) = H(H(previous-block) + data-in-this-block)
54. 54
Blockchain: IoT example (I)
• Imagine the journey a perishable foodstuff (say milk) takes from farm to consumer
– The dairy farm: milking and initial storage;
– Processing: transportation to a dairy processor for testing, pasteurizing and packaging;
– Transportation: shipping in refrigerated trucks to retailers like supermarkets or convenience stores;
– Retail: storage in a refrigerated display unit;
– Consumption: customer purchase and consumption.
• The difficulty with a supply chain like this one is that there isn’t a single,
synchronized record of the transaction from beginning to end.
– Blockchain is a single, synchronized, immutable record of every transaction, visible to everyone in the
supply chain.
– The blockchain ledger records the sequence of transactions from the beginning to the end of the
supply chain.
• URL: very interesting infographics about IoT and Blockchain at:
http://www.sepaforcorporates.com/payments-news-2/what-is-blockchain-5-
awesome-infographics/
55. 55
• Example: instrumenting the supply-chain
– “transport of perishable food stuffs (such as milk) is regulated by specific
conditions that ensure it arrives at the point of purchase safely”
• IoT & Blockchain solution: Connected sensors for data transmission
– Individual packages containing milk are instrumented with an IoT-enabled
temperature sensor
– The sensor stores temperature data locally and sends it via an IoT Platform
to the blockchain
– The blockchain stores the temperature data, where it can be viewed by each
party to the transaction
• IoT with blockchain can help businesses keep tabs on the health of their
products at every stage of their journey through Smart Contracts.
– Those contracts stored on the blockchain could specify certain conditions that must be
met. Controlled temperature might be one of these.
• Video: https://www.youtube.com/watch?v=HJ1W4vHPDFY
Blockchain: IoT example (II)
56. 56
Internet of Things: Challenges
1. To process huge amounts of data supplied by “connected
things” and to offer services as response
2. To research in new methods and mechanisms to find,
retrieve, transmit and process data dynamically
– Discovery of sensor data — both in time and space
– Communication of sensor data: complex queries (synchronous),
publish/subscribe (asynchronous)
– Processing of great variety of sensor data time-series and streams:
correlation, aggregation and filtering
3. Ethical and social dimension: to keep the balance between
personalization, privacy and security
57. 57
La Ecuación de IoT
• Conexión en red de cosas aumentadas da lugar a
agregación de datos y orquestación de servicios
para mejorar procesos
THING IT
[HW | SW]
THING-BASED
FUNCTION
[Local | Business
models known]
IT-BASED
SERVICE
[Global | Business
models required]
Example SERVICE: Send ambulance
in case of accident (detected by sensors)
Example FUNCTION:
Drive from A to B
A B
Source: University of St. Gallen, Prof. Dr. Elgar Fleisch
58. 58
Information flow in IoT
• Information within the Internet of Things creates value in a
never-ending value loop consisting of 5 stages (CREATE … to ACT):
72. 72
IoT Enablers (I)
RFID Sensor Smart Tech Nano Tech
To identify
and track
the data of
things
To collect
and process
the data to
detect the
changes in
the physical
status of
things
To enhance the
power of the
network by
devolving
processing
capabilities to
different part of
the network.
To make the
smaller and
smaller things
have the
ability to
connect and
interact.
73. 73
IoT Enablers (II)
Networked
heating systems
Networked
surveillance systems
Connected
vehicles
Smart sensor
platforms
Network
capability of
devices
Low power
consumption
Small form
factor
Energy
harvesting
capability
Wireless
technologies
Applications
Appropriate
cost
Enablers
74. 74
IoT Enabling Technologies
• Low-cost embedded computing and communication
platforms, e.g. Arduino or Rapsberry PI
• Wide availability of low-cost sensors and networks
• Cloud-based Sensor Data Management Frameworks:
Xively, Sen.se
Democratization of Internet-connected Physical Objects
75. 75
IoT Hardware prototyping platforms
– Self-contained
– Cheap
– Easy to program and extend
– Often under Open Source and/or Open
Hardware license
– Self-contained
– Strong online community for learning and
support
– Focus on easy onboarding for non-experts
– Strong success in hobbyist / maker /
education areas
• An electronic board and associated software for easily connecting electronics
to software and the Cloud which differs from professional electronics
development kits:
79. 79
IPv6 a key IoT enabler (I)
• Latest revision of the Internet Protocol (IP), provides an identification
and location system for computers on networks and routes traffic across
the Internet.
– Developed by the Internet Engineering Task Force (IETF) to deal with the long-
anticipated problem of IPv4 address exhaustion
• IPv6 is intended to replace IPv4, which still carries the vast majority of Internet
traffic.
– As of May 2018, the percentage of users reaching Google over IPv6 surpassed 22%:
https://www.google.com/intl/en/ipv6/statistics.html#tab=ipv6-adoption&tab=ipv6-
adoption
• To make the switch, software and routers will have to be changed
• IPv6 uses a 128-bit address, allowing 2128, or approximately 3.4×1038
addresses, or more than 7.9×1028 times as many as IPv4, which uses 32-bit
addresses.
• IPv6 addresses are represented as eight groups of four hexadecimal digits
separated by colons
– E.g. 2001:0db8:85a3:0042:1000:8a2e:0370:7334
80. 80
IPv6 a key IoT enabler (II)
• The future of IoT will not be possible without the support of IPv6
– The global adoption of IPv6 in the coming years will be critical for the successful
development of the IoT in the future
• The ability to network embedded devices with limited CPU, memory and
power resources means that IoT finds applications in nearly every field
– IoT systems could also be responsible for performing actions, not just sensing
things
• 6LoWPAN is an acronym of IPv6 over Low power Wireless Personal Area
Networks
– The 6LoWPAN concept originated from the idea that "the Internet Protocol could and
should be applied even to the smallest devices“ and that low-power devices with
limited processing capabilities should be able to participate in the Internet of Things.
– The 6LoWPAN group has defined encapsulation and header compression mechanisms
that allow IPv6 packets to be sent and received over IEEE 802.15.4 (Zigbee) based
networks.
81. 81
IPv6 vs. IPv4
• Other important changes:
• No more NAT (Network Address Translation), Auto-configuration, no
more private address collisions, better multicast routing, simpler header
format, simplified, more efficient routing, true quality of service (QoS), also
called "flow labeling“, built-in authentication and privacy support, flexible
options and extensions, easier administration (say good-bye to DHCP)
83. 83
HTTP 2.0
• HTTP 2.0 is the next planned version of the HTTP network protocol used
by the World Wide Web.
– HTTP 2.0 is being developed by the Hypertext Transfer Protocol Bis (httpbis)
working group of the IETF.
– Based on Google's SPDY protocol, Microsoft's HTTP Speed+Mobility proposal
(SPDY based)
• HTTP 2.0 would be the first new version of the HTTP protocol since HTTP
1.1 was described by RFC 2616 in 1999.
– In May 2015 it was published as HTTP/2 as RFC 7540
• Goals:
– Include asynchronous connection multiplexing, header compression, and
request-response pipelining, while maintaining full backwards compatibility
with the transaction semantics of HTTP 1.1
– Enable Server-Push
• Documentation:
– http://chimera.labs.oreilly.com/books/1230000000545/ch12.html
84. 84
HTTP 2.0 streams, messages and frames
Binary Framing Layer Stream, Messages & Frames
A connection carries any number of bidirectional
streams. In turn, each stream communicates in
messages, which consist of one or multiple frames,
each of which may be interleaved and then
reassembled via the embedded stream identifier in
the header of each individual frame
Request & Response Multiplexing
88. 88
Near Field Communication (NFC)
• Near field communication (NFC) is a set of standards for smartphones and
similar devices to establish radio communication with each other by touching
them together or bringing them into close proximity, usually no more than a few
centimeters
– Operates at 13.56 MHz, has data transfer rate ranging from 106 kbit/s to 424 kbit/s
– NFC tags contain data and are typically read-only, but may be rewriteable
• Uses RFID (Radio Frequency Communication) chips that enable devices to
communicate between them, bi-directionally.
– Application examples:
• NFC headsets and electronic wallets, eliminates the need to pair devices in Bluetooth
or WiFi Direct (e.g. Android Beam / S-Beam), data exchange through NFC tags
• Wider availability of NFC-enabled SmartPhones is propelling its usage:
http://www.nfcworld.com/nfc-phones-list/
– Apple iPhone 6 to 8s supports NFC as part of Apple Pay
89. 89
NFC in Use
• Get info from posters,
make payments,
exchange connections
90. 90
Bluetooth Low Energy (BLE)
• Bluetooth low energy (BLE) is a wireless computer network technology which
is aimed at novel applications in the healthcare, fitness, security, and home
entertainment industries.
– Compared to "Classic" Bluetooth, it is intended to provide considerably reduced
power consumption and lower cost, while maintaining a similar communication
range
• Power consumption is drastically reduced via a low pulsing method that keeps devices
connected without the need of a continuous information stream
• Features:
– Operates in the same spectrum range (the 2.400 GHz-2.4835 GHz ISM band) as
Classic Bluetooth technology, but uses a different set of channels.
– Uses a star topology
– Nodes act as presence/state indicators
– Internet enabled devices as Gateways
• Available devices supporting BLE (most of the new SmartPhones feature it)
91. 91
• In the market, we can encounter two types of BLE devices:
– Bluetooth Smart Ready refers to devices that use a dual-mode radios, which
can handle both the 4.0 technology, as well as classic Bluetooth abilities, such
as transferring files, or connecting to a hands-free device.
– Bluetooth Smart represents a new breed of Bluetooth 4.0 peripherals: sensor-
type devices like heart-rate monitors or pedometers that run on small
batteries and are designed to collect specific pieces of information.
• Only connect to BT Smart Ready devices
92. 92
iBeacon – a class of BLE devices that broadcast their
identifier to nearby portable electronic devices (I)
93. 93
iBeacon – a class of BLE devices that broadcast their
identifier to nearby portable electronic devices (II)
96. 96
• Sigfox, is a French company that builds wireless networks to connect low-energy objects such as electricity
meters, smartwatches, and washing machines, which need to be continuously on and emitting small
amounts of data
• Employs "a cellular style system that enables remote devices to connect using ultra-narrow band (UNB)
technology", the same used for submarine communications during World War I.
• The Sigfox network and technology is aimed at the low cost machine to machine application areas where
wide area coverage is required
• Its network costs are reduced and it requires little energy, being termed Low-power Wide-area network
(LPWAN)
– Sigfox uses long waves transmitting small amounts of data very far being able to handle approximately 12 bytes per
message, and at the same time no more than 140 messages per device per day
• With 12 bytes one can represent any number between 1 and 79 octillion, which translates as a myriad control codes
• According to Machina Research, in 2024 there were a total of 27 billion M2M connections or 80 billion
connected objects, 14% of which will represent LPWA connections like those offered by Sigfox and its
competitors (LoRa and Neul (Huawei))
98. 98
Web of Things (I)
• The Web of Things (WoT) is a computing concept that
describes a future where everyday objects are fully
integrated with the Web.
– The prerequisite for WoT is for the "things" to have embedded
computer systems that enable communication with the Web, i.e. HTTP
microserver
– Such smart devices would then be able to communicate with each
other using existing Web standards: HTTP & REST
– http://www.webofthings.org/
99. 99
Web of Things (II)
• Term used to describe approaches, software architectural
styles and programming patterns that allow real-world
objects to be part of the World Wide Web
– Similarly to what the Web (Application Layer) is to the Internet
(Network Layer) the Web of Things provides an Application Layer that
simplifies the creation of Internet of Things applications
– Rather than re-inventing completely new standards, the Web of Things
reuses existing and well-known Web standards used in the
programmable Web (e.g., REST, HTTP, JSON), semantic Web (e.g.,
JSON-LD, Microdata, etc.), the real-time Web (e.g., Websockets) and
the social Web (e.g., oauth or social networks).
100. 100
Web of Things Architecture
• The following layers compose WoT:
– Layer 1 (ACCESS): ensures things
have a Web accessible API,
transforming them into
programmable things
– Layer 2 (FIND): reuses Web
semantic standards to describe
things and their services
– Layer 3 (SHARE): data generated by
things can be shared in an efficient
and secure manner
– Layer 4 (COMPOSE): integrates the
services and data offered by things
into higher level Web tools
101. 101
The Programmable World
• Los siguientes pasos para alcanzar la quimera de
Programmable World:
1. Transformar los objetos cotidianos en inteligentes
2. Conectar estos objetos entre ellos y hacer que
“conversen”, algo de lo que productos como SmartThings
están tratando
3. Construir aplicaciones basadas en esta conectividad,
interconectándolas con datos externos para predecir, por
ejemplo, patrones de tiempo o consumo eléctrico
• Soluciones como IFTTT facilitan esa conectividad
entre diferentes canales de datos
102. 102
IFTTT
• IFTTT is a service that lets you create powerful connections
with one simple statement:
– IFTTT is pronounced like “gift” without the “g”
• Channels are the basic building blocks of IFTTT: Facebook,
Evernote, Email, Weather, LinkedIn
• Each channel has its own Triggers and Actions:
– The this part of a Recipe is a Trigger, e.g. “I’m tagged in a photo on
Facebook”
– The that part of a Recipe is an Action, e.g. “send me a text message”
– Pieces of data from a Trigger are called Ingredients
• Demos: https://ifttt.com/myrecipes/personal
103. 103
Atooma
• Es como un IFTTT pero para
SmartPhones
• Permite definir eventos
condicionales (IF) que lanzan
automáticamente tareas (DO)
asociadas actividades que pueden
ser detectadas por tu móvil (hora,
localización, estado de la batería,
etc.)
– URL: http://www.atooma.com/
104. 104
IoT & Cloud Computing
Interdependency
• Cloud computing and IoT are tightly coupled
– The growth of IoT and the rapid development of
associated technologies create a widespread connection of
“things.”
• Leads to production of large amounts of data, which needs
to be stored, processed and accessed
– Cloud computing as a paradigm for big data storage and
analytics
• The combination of cloud computing and IoT will
enable new monitoring services and powerful
processing of sensory data streams.
105. 105
Infraestructura Virtualizada:
Cloud Computing
Un paradigma de computación emergente donde los datos y servicios
residen en centros de datos muy escalables que pueden ser accedidos
ubicuamente desde cualquier dispositivo conectado a Internet.
106. 106
Cloud Computing es …
• … capacidad computacional y
almacenamiento virtualizada expuesta
mediante infraestructura agnóstica a la
plataforma y accedida por Internet
– Recursos IT compartidos en demanda, creados y
eliminados eficientemente y de modo escalable a
través de una variedad de interfaces programáticos
facturados en base a su uso
109. 109
Cloud Computing Limitations for IoT
• Connectivity to the Cloud is a MUST but …
– Some IoT systems need to be able to work even when connection is
temporarily unavailable or under degraded connection
• Cloud Computing assumes that there is enough bandwidth to
collect the data
– That can become an overly strong assumptions for Industrial Internet
of Things applications
• Cloud Computing centralises the analytics thus defining the
lower bound reaction time of the system
– Some IoT applications won’t be able to wait for the data to get to the
cloud, be analysed and for insights to get back
110. 110
Edge Computing
• Pushing the frontier of computing applications,
data, and services away from centralized nodes to
the logical extremes of a network.
– It enables analytics and knowledge generation to occur at
the source of the data.
111. 111
Edge Computing: Benefits
• Locally confines regional data processing of M2M/big data applications
that incur large data traffic to edge-servers, and reduces network
bandwidth.
– Executes real-time applications that require high-speed response at the
nearer edge-servers which will satisfy the severe real-time requirement.
• Offloads some of the computation intensive processing on the user’s
device to edge servers and makes application processing less dependent
on the device’s capability.
112. 112
Fog Computing = IoT + Cloud Computing (I)
• The software industry’s three building blocks, subject to Moore’s law, are:
storage, computing and network
– The problem is, right now everything is sorted in the cloud, which means you
have to push all this data up, just to get the distilled big data feedback down.
• Fog computing is a decentralized computing infrastructure in which
computing resources and application services are distributed in the most
logical, efficient place at any point along the continuum from the data
source to the cloud
o improve efficiency and reduce the amount of data
that needs to be transported to the cloud for data
processing, analysis and storage.
o done for efficiency reasons, but it may also be
carried out for security and compliance reasons.
114. 114
Web Semántica
• Problema de la Web Actual:
– El significado de la web no es comprensible por máquinas
• Web Semántica crea un medio universal de
intercambio de información, aportando semántica a
los documentos en la web
– Añade significado comprensible por ordenadores a la Web
– Usa técnicas inteligentes que explotan esa semántica
– Liderada por Tim Berners-Lee del W3C
• Misión “turning existing web content into
machine-readable content“
115. 115
Web of Data: Limitaciones de la Web
de Documentos
• Demasiada información con muy poca estructura y
hecha además para consumo humano
– Es una web sintáctica no semántica
– La búsqueda de contenidos es muy simplista
• Se requieren mejores métodos
• Los contenidos web son heterogéneos
– En términos de contenido
– En términos de estructura
– En términos de codificación de caracteres
• El futuro requiere integración de información inteligente
116. 116
Linked Data
• “A term used to describe a recommended best practice for
exposing, sharing, and connecting pieces of data, information,
and knowledge on the Semantic Web using URIs and RDF.“
• Allows to discover, connect, describe and reuse all sorts of data
– Fosters passing from a Web of Documents to a Web of Data
• In September 2011, it had 31 billion RDF triples linked through 504 millions of
links
• Thought to open and connect diverse vocabularies and semantic
instances, to be used by the Semantic community
• URL: http://linkeddata.org/
117. 117
Linked Data Principles
1. Uses URIs to identify things
2. Uses HTTP URIs to enable those
things to be dereferenced by both
people and user agents
3. Provides useful info (structured
description and metadata) about a
thing/concept referenced by an URI
4. Includes links to other URIs to
improve related information
discovery in the web
118. 118
Linked Data Example
http://…/isb
n978
Programming the
Semantic Web
978-0-596-15381-6
Toby Segaran
http://…/publi
sher1
O’Reilly
title
name
author
publisher
isbn
http://…/isb
n978
sameAs
http://…/rev
iew1
Awesome
Book
http://…/rev
iewer
Juan
Sequeda
http://juanseque
da.com/id
hasReview
hasReviewer
description
name
sameAs
livesIn
Juan Sequedaname
http://dbpedia.org/Austin
119. 119
Linked Data Life Cycle
• Linked Data must go through several stages (several
iterations on Linkage) before are ready for exploitation:
120. 120
Schema.org
• Initiative launched in 2011 by Bing, Google, Yahoo and then Yandex
• Objective: “create and support a common set of schemas for structured data
mark-up on web pages.”
– Propose to use their schemas to annotate contents in a web page with metadata
• Metadata are recognized by search engines and other parsers, thus accessing to the
“meaning” of portals
• Their vocabularies were inspired by earlier formats like Microformats, FOAF,
GoodRelations and OpenCyc
• Offer schemas in the following domains
(http://schema.org/docs/schemas.html):
– Events, health, organization, person, place, product, offer, revisión and so on.
• To map declarations in microdata to RDF the following tools can be used:
http://tools.seochat.com/category/schema-generators
• More info at: http://schema.org/
• Examples:
– http://schema.org/CreativeWork
– http://paginaspersonales.deusto.es/dipina/ (microdata.reveal Chrome plugin)
121. 121
Avoiding Data Silos through
Semantics in IoT
• Cut-down semantics is applied to enable machine-
interpretable and self-descriptive interlinked data
– Integration – heterogeneous data can be integrated or one
type of data combined with other
– Abstraction and access – semantic descriptions are
provided on well accepted ontologies such as SSN
– Search and discovery – resulting Linked Data facilitates
publishing and discovery of related data
– Reasoning and interpretation –new knowledge can be
inferred from existing assertions and rules
122. 122
Actionable Knowledge from
Linked Data
• Don’t care about the data sources (sensors) care about
knowledge extracted from their data correlation &
interpretation!
– Data is captured, communicated, stored, accessed and shared
from the physical world to better understand the surroundings
– Sensory data related to different events can be analysed,
correlated and turned into actionable knowledge
– Application domains: e-health, retail, green energy,
manufacturing, smart cities/houses
124. 124
Bringing together IoT and Linked Data:
Sustainable Linked Data Coffee Maker
• Hypothesis: “the active collaboration of people and
Eco-aware everyday objects will enable a more
sustainable/energy efficient use of the shared
appliances within public spaces”
• Contribution: An augmented capsule-based coffee
machine placed in a public spaces, e.g. research
laboratory
– Continuously collects usage patterns to offer
feedback to coffee consumers about the energy
wasting and also, to intelligently adapt its
operation to reduce wasted energy
• http://socialcoffee.morelab.deusto.es/
125. 125
Social + Sustainable + Persuasive +
Cooperative + Linked Data Device
1. Social since it reports its energy consumptions via social
networks, i.e. Twitter
2. Sustainable since it intelligently foresees when it should be
switched on or off
3. Persuasive since it does not stay still, it reports misuse and
motivates seductively usage corrections
4. Cooperative since it cooperates with other devices in order
to accelerate the learning process
5. Linked Data Device, since it generates reusable energy
consumption-related linked data interlinked with data from
other domains that facilitates their exploitation
127. 127
Linked Data by IoT Devices
• Modelling not only the sensors but also their features of
interest: spatial and temporal attributes, resources that
provide their data, who operated on it, provenance and so on
– With SSN, SWEET, SWRC, GeoNames, PROV-O, … vocabularies
128. 128
Knowledge graphs:
Encyclopaedias for machines
• It consists of a formal description of certain knowledge that can be accessed and reasoned
about by computers
– fundamental to empower intelligent systems
• Apple’s Siri, Microsoft’s Cortana, Amazon Echo, or Google Now, for example, heavily rely on knowledge graphs
to fulfill your requests.
– a representation based on entities, relations, and facts.
• For example, the IMDb knowledge graph, meant to be used by both people and computers.
– Actors, directors, writers or films, are the entities while <acted_in> or <writer_of> some of
the relations. You can see the facts in each entity page.
• https://www.imdb.com/name/nm0424060/
• The range of questions (usually referred as queries) that can be asked to a knowledge graph
is broad. It can involve any combination of relations, entities, classes or facts.
– If the knowledge graph is relatively complete, it is guaranteed to provide high-quality answers in a
minuscule amount of time.
• The three most prominent general knowledge graphs to date: YAGO, DBpedia, and WikiData.
• More at: https://www.ambiverse.com/knowledge-graphs-encyclopaedias-for-machines/
132. 132
IoT Platforms
• Allow to manage remote devices and exchange messages to enable
building IoT applications
– Remote Device Management
• Manage the device life cycle from onboarding till decommissioning
• Receive device information
• Configure devices remotely
• Send commands to devices
– Message Management
• Collect sensor data and store it in the HCP persistence layer
• Supports various transport protocols and message formats
– Application Enablement
• Use Device Management and Message Management functionality in your
applications
• IoT software platform can be classified according to the following criteria:
device management, integration, security, protocols for data collection,
types of analytics, and support for visualizations
133. 133
IoT Platforms
IoT Software
Platform
Device
management?
Integration Security
Protocols for data
collection
Types of analytics
Support for
visualizations?
2lemetry - IoT
Analytics Platform**
Yes
Salesforce, Heroku,
ThingWorx APIs
Link Encryption (SSL),
Standards ( ISO 27001,
SAS70 Type II audit)
MQTT, CoAP,
STOMP,M3DA
Real-time analytics
(Apache Storm)
No
Appcelerator No REST API
Link Encryption (SSL,
IPsec, AES-256)
MQTT, HTTP
Real-time analytics
(Titanium [1])
Yes (Titanium UI
Dashboard)
AWS IoT platform Yes REST API
Link Encryption
(TLS), Authentication
(SigV4, X.509)
MQTT, HTTP1.1
Real-time analytics
(Rules Engine, Amazon
Kinesis, AWS Lambda)
Yes (AWS IoT
Dashboard)
Bosch IoT Suite - MDM
IoT Platform
Yes REST API *Unknown
MQTT, CoAP,
AMQP,STOMP
*Unknown
Yes (User Interface
Integrator)
Ericsson Device
Connection Platform
(DCP) - MDM IoT
Platform
Yes REST API
Link Encryption
(SSL/TSL),Authenticati
on (SIM based)
CoAP *Unknown No
EVRYTHNG - IoT
Smart Products
Platform
No REST API Link Encryption (SSL)
MQTT,CoAP,
WebSockets
Real-time analytics
(Rules Engine)
Yes (EVRYTHNG IoT
Dashboard)
IBM IoT Foundation
Device Cloud
Yes
REST and Real-time
APIs
Link Encryption ( TLS),
Authentication (IBM
Cloud SSO), Identity
management (LDAP)
MQTT, HTTPS
Real-time analytics
(IBM IoT Real-Time
Insights)
Yes (Web portal)
ParStream - IoT
Analytics Platform***
No R, UDX API *Unknown MQTT
Real-time analytics,
Batch analytics
(ParStream DB)
Yes (ParStream
Management Console)
PLAT.ONE - end-to-
end IoT and M2M
application platform
Yes REST API
Link Encryption (SSL),
Identity Management
(LDAP)
MQTT, SNMP *Unknown
Yes (Management
Console for application
enablement, data
management, and
device management)
ThingWorx - MDM IoT
Platform
Yes REST API
Standards (ISO 27001),
Identity Management
(LDAP)
MQTT, AMQP, XMPP,
CoAP, DDS,
WebSockets
Predictive
analytics(ThingWorx
Machine Learning),
Real-time analytics
(ParStream DB)
Yes (ThingWorx
SQUEAL)
Xively- PaaS enterprise
IoT platform
No REST API
Link Encryption
(SSL/TSL)
HTTP, HTTPS,
Sockets/ Websocket,
MQTT
*Unknown
Yes (Management
console)
Source: https://dzone.com/articles/iot-software-platform-comparison
134. 134
IoT como habilitador de las
Ciudades Inteligentes
• IoT allows for the pervasive interaction
with/between the smart things leading to an
effective integration of information into the digital
world.
– Smart things - instrumented with sensing, actuation, and
interaction capabilities - have the means to exchange
information and influence the real world entities and
other actors of a smart city eco-system in real time,
forming a smart pervasive computing environment to
achieve a more livable city
135. 135
The need for Smart Cities
• Challenges cities face today:
– Growing population
• Traffic congestion
• Space – homes and public space
– Resource management (water and energy use)
– Global warming (carbon emissions)
– Tighter city budgets
– Aging infrastructure and population
136. 136
What is a Smart City?
• Smart Cities improve the efficiency and
quality of the services provided by governing
entities and business and (are supposed to)
increase citizens’ quality of life within a city
– This view can be achieved by leveraging:
• Available infrastructure such as Open Government
Data and deployed sensor networks (IoT) in cities
• Citizens’ participation through apps in their
smartphones
– Or go for big companies’ “smart city in a box”
solutions
137. 137
What is a Smart Sustainable City?
A smart sustainable city is an innovative city that uses
information and communication technologies and
other means to improve quality of life, efficiency of
urban operation and services, and competitiveness,
while ensuring that it meets the needs of present and
future generations with respect to economic, social and
environmental aspects
https://itunews.itu.int/en/5215-What-is-a-smart-sustainable-city.note.aspx
139. 139
• Smart Cities seek the participation of citizens:
– To enrich the knowledge gathered about a city
not only with government-provided or networked
sensors' provided data, but also with highly
dynamic user-generated data
• BUT, how can we ensure that users and their
generated data can be trusted and has enough
quality?
– W3C has created the PROV Data Model, for provenance
interchange
Citizen Participation
140. 140
User-generated Data: Google Maps vs.
Open Street Map
• OSM is an excellent cartographic product driven by user contributions
• Google Maps has progressed from mapping for the world to mapping from the world,
where cartography is not the end product, but rather the necessary means for:
– Google’s autonomous car initiative, combine sensors, GPS and 3D maps for self-driving cars.
– Google’s Project Wing: a drone-based delivery systems to make use of a detailed 3D model
of the world to quickly link supply to demand
• By connecting the geometrical content of its Google Maps databases to digital traces
that it collects, Google can assign meaning to space, transforming it into place.
– Mapping by machines if not about “you are here”, but to understand who you are, where
you should be heading, what you could be doing there!
141. 141
CrowdSensing
• Individuals with sensing and computing devices collectively
share data and extract information to measure and map
phenomena of common interest
142. 142
Personal Data
• Defined as "any information
relating to an identified or
identifiable natural person
("data subject")”
143. 143
Urban Intelligence / Analytics
• Broad Data aggregates data from heterogeneous sources:
– Open Government Data repositories and IoT deployments
– User-supplied data through social networks or apps
– Public private sector data or
– End-user private data
• Humongous potential on correlating and analysing Broad
Data in the city context:
– Leverage digital traces left by citizens in their daily interactions
with the city to gain insights about why, how and when they do
things
– We can progress from Open City Data to Open Data Knowledge
• Energy saving, improve health monitoring, optimized transport
system, filtering and recommendation of contents and services
144. 144
Smarter Cities
• Smarter Cities cities that do not only manage their
resources more efficiently but also are aware of the
citizens’ needs.
– Human/city interactions leave digital traces that can be
compiled into comprehensive pictures of human daily facets
– Analysis and discovery of the information behind the big
amount of Broad Data captured on these smart cities
deployment
Smarter Cities= Internet of Things + Broad Data + Citizen
Participation through Smartphones + Urban Analytics
147. 147
Perspectivas de crecimiento de
IoT: realidad o promesa
• Success stories in the following domains:
– Intelligent Waste Management
– Animals and Environment Monitoring
– Smart Grids: IoT and knowledge based control for energy
efficiency
– Comprehensive system for agriculture intelligence
• Internet of Things Success Stories #1 to #3:
– https://www.smart-
action.eu/publications/archive/2015/10/55099c948b1ac6
826c142aa6fcd402e4/
148. 148
IoT & Big Data
• IoT is also expected to generate large
amounts of data from diverse locations, with
the consequent necessity for quick
aggregation of the data, and an increase in
the need to index, store, and process such
data more effectively
149. 149
IoT & Big DataTensHundredsThousandsMillionsBillionsConnections
Internet of Things
Machine-to-Machine
Isolated
(autonomous, disconnected)
Monitored
Smart Systems
(Intelligence in Subnets of Things )
Telemetry
and
Telematics
Smart Homes
Connected Cars
Intelligent Buildings
Intelligent Transport
Systems
Smart Meters and Grids
Smart Retailing
Smart Enterprise
Management
Remotely controlled
and managed
Building
automation
Manufacturing
Security
Utilities
Internet of Things
Sensors
Devices
Systems
Things
Processes
People
Industries
Products
Services
Growth in connections generates
an unparalleled scale of data
Source: Machina Research 2014
150. 150
From M2M to IoT towards Big Data
Data
Big data
Changing data
models
Real-time Processing
Aggregation
Internet of Things
Large estates of devices
Evolving applications
All forms of data
Data streaming and
processing
Pre-IoT (M2M)
Limited estate of
devices
Single purpose
applications
Structured / Semi-
structured
Data transfers
(sensors and actuators)
Source: Machina Research 2014
151. 151
Data has changed
• 90% of the world’s data
was created in the last two
years
• 80% of enterprise data is
unstructured
• Unstructured data growing
2x faster than structured
152. 152
Nature of Data in IoT
• Heterogeneity makes IoT devices hardly interoperable
• Data collected is multi-modal, diverse, voluminous
and often supplied at high speed
• IoT data management imposes heavy challenges on
information systems
153. 153
¿Qué es Big Data?
• "Big Data are high-volume, high-velocity, and/or high-variety
information assets that require new forms of processing to
enable enhanced decision making, insight discovery and
process optimization“ Gartner, 2012
– El término “Big Data” se originó dentro de la comunidad open source,
donde hubo un esfuerzo por desarrollar procesos de análisis que
fueran más rápidos y escalables que el data warehousing tradicional,
y pudieran extraer valor de los inmensos volúmenes de datos no
estructurados producidos a diario por usuarios web
• Es una oportunidad para encontrar percepciones en nuevos y
tipos emergentes de datos y contenidos, para hacer a tu
negocio más ágil, y para responder preguntas que fueron
consideradas con anterioridad fuera de tu alcance.
154. 154
Big Data Evolution
• Data explosion!!
– 48 hours of data from stock market ~ 5 TB
– Semi and non-structured data provided in real-time through social networks
– Google processes PB/hour
• Bioinformatics – huge datasets about genetics and drugs
• Money whitening / terrorist funding, Spatial Data
• 85% of Fortune 500 organizations are not able to process Big Data to gain
competitive advantage – Gartner
• Currently more than 1.9 zettabytes of data are being produced
155. 155
Necesidad de Big Data Analytics
• La percepción de los procesos de Data Warehousing es que
son lentos y limitados en escalabilidad
• La necesidad de converger datos de varias fuentes, tanto
estructuradas como no estructuradas
• Es crítico el acceso a la información para extraer valor de las
fuentes de datos incluyendo dispositivos móviles, RFID, la web
y otro largo listado de tecnologías sensoriales automatizadas.
165. 165
Apache Hadoop
• Hadoop es una framework gratuita en Java para procesar grandes
volúmenes de datos en un entorno de computación distribuido
– Hace posible la ejecución de aplicaciones sobre sistemas con miles de nodos
que procesan miles de terabytes
– Su sistema de ficheros distribuido facilita la rápida transferencia de datos
entro nodos y permite al sistema seguir operando ininterrumpidamente en
caso de fallo de un nodo
– Inspirado por Google MapReduce, un modelo de computación donde una
aplicación se divide en varias partes
• Cada una de esas partes (fragmentos o bloques) puede ser ejecutada en cualquier
nodo de un clúster
– El ecositema actual de Apache Hadoop consiste de:
• Hadoop kernel, MapReduce, el sistema de ficheros distribuido de Hadoop (HDFS) y
otros proyectos relacionados como Apache Hive, HBase and Zookeeper.
– Usado por los grandes agentes de la industria Google, Yahoo and IBM
166. 166
Apache Spark
• Apache Spark provides programmers with an application programming
interface centered on a data structure called the resilient distributed
dataset (RDD), a read-only multiset of data items distributed over a cluster
of machines, that is maintained in a fault-tolerant way.
– It was developed in response to limitations in the MapReduce cluster
computing paradigm, which forces a particular linear dataflow structure on
distributed programs
– Oriented to stream data processing allowing for CEP (Complex Event
Processing)
170. 170
IoT Market
• The global IoT market will grow from $157B in
2016 to $457B by 2020, attaining a Compound
Annual Growth Rate (CAGR) of 28.5%
171. 171
Summary: Challenges of IoT (I)
• Platform : form and design of the products (UI and UX) , analytics tools
used to deal with the massive data streaming from all products in a secure
way , and scalability which means wide adoption of protocols like IPv6 in
all vertical and horizontal markets .
• Connectivity: Connectivity includes all parts of the consumer’s day and
night using wearables, smart cars, smart homes, and in the big scheme
smart cities.
• Business Model: The bottom line is a big motivation for starting, investing
in, and operating any business, without a sound and solid business models
for IoT we will have another bubble , this model must satisfied all the
requirements for all kinds of e-commerce; vertical markets, horizontal
markets and consumer markets.
• Killer Applications: Three functions needed in any killer applications,
control “things”, collect “data”, analyze “data”.
• Security: The IoT introduces unique physical security concerns implying
that IoT privacy concerns are complex and not always readily evident.
172. 172
Summary: Challenges of IoT (II)
• Learn how to make money with it – make it
sustainable
– Finding meaningful use cases is key to success
– Visions are allowed, but first bills have to be paid
– New business models are key to making money with IoT
– Business models will have an impact on the architecture of
solutions!
• IoT can be complex!
– Keep it simple by structured data models and good scale
– Keep it understandable for customers and consumers
173. 173
Summary: Challenges of IoT (III)
• Society: People, security, privacy
– A policy for people in the Internet of Things: Legislation (GDPR)
– Decisions – do not delegate too much of our decision making and
freedom of choice to things and machines
– Privacy and Security will distinguish between success and failure
– Managing one’s own privacy will become a complex task – and needs
to be kept simple
– Historical personal data availability – who will delete the data?
• Environmental aspects
– Resource efficiency
– Pollution and disaster avoidance
174. 174
Summary: Challenges of IoT (IV)
• Technological
– Architecture (edge devices, servers, discovery services, security, etc.)
– Governance, naming, identity, interfaces
– Service openness, interoperability
– Connections of real and virtual world
– Standards
• Establishing a common set of standards
– The same type of cabling,
– The same applications or programming
– The same protocol or set of rules that will apply to all
• Energy sources for millions -even billions - of sensors
– Wind
– Solar,
– Hydro-electric
175. 175
Conclusión
• Internet de las Cosas al Servicio de las Personas:
– https://www.youtube.com/watch?v=Ge0q7jJuvbs
176. 176
Conclusión
• Internet de las Cosas al Servicio de las Personas:
– https://www.youtube.com/watch?v=Ge0q7jJuvbs
177. 177
Internet de las Cosas: del Concepto a la
Realidad
CETIC (Centro de Tecnologías de la Información y Comunicación), Vitoria-Gasteiz
29 de Mayo de 2018, 18:00-20:30
Dr. Diego López-de-Ipiña González-de-Artaza
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina
http://www.morelab.deusto.es
@dipina
178. 178
References
• Internet of Things towards Ubiquitous and Mobile Computing
– http://research.microsoft.com/en-
us/UM/redmond/events/asiafacsum2010/presentations/Guihai-
Chen_Oct19.pdf
• 5 key questions to ask about the Internet of Things
– http://www.slideshare.net/DeloitteUS/5-questions-the-iot-internet-of-things
• Internet Connected Objects for Reconfigurable Eco-systems
– https://docbox.etsi.org/workshop/2012/201210_M2MWORKSHOP/zz_POSTE
RS/iCore.pdf
• Internet of Things and Big Data – Bosch, August 2015
– https://www.bosch-
si.com/media/bosch_software_innovations/media_landingpages/connectedw
orld_1/bcw_2016/bcw_1/download_page_1/download_page/bcw16_mongo
db_collateral_followup_sponsor.pdf
• The internet of things and big data: Unlocking the power
– http://www.zdnet.com/article/the-internet-of-things-and-big-data-unlocking-
the-power/
179. 179
References
• Deconstructing the Internet of Things
– https://jenson.org/deconstructing-the-iot/
• Mobile in IoT Context ? Mobile Applications in "Industry 4.0“
– http://www.slideshare.net/MobileTrendsConference/karol-kalisz-vitaliy-rudnytskiy-
mobile-in-iot-context-mobile-applications-in-industry-40
• Inside the Internet of Things (IoT) – A primer on the technologies building
the IoT – Deloitte
– http://dupress.com/articles/iot-primer-iot-technologies-applications/
• Internet of Things (IoT) - We Are at the Tip of An Iceberg – Dr. Mazlan
Abbas
– http://www.slideshare.net/mazlan1/internet-of-things-iot-we-are-at-the-tip-of-an-
iceberg
• Infographic: What are Beacons and What Do They Do?
– https://kontakt.io/blog/infographic-beacons/
• iBeacon
– https://en.wikipedia.org/wiki/IBeacon
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References
• ITU News – What is a smart sustainable city?,
– https://itunews.itu.int/en/5215-What-is-a-smart-sustainable-
city.note.aspx
• Frost & Sullivan's Predictions for the Global Energy and
Environment Market,
– http://www.slideshare.net/FrostandSullivan/frost-sullivans-
predictions-for-the-global-energy-and-environment-market
• Fog Computing with VORTEX
– http://www.slideshare.net/Angelo.Corsaro/20141210-fog
• What Exactly Is The "Internet of Things"? – A graphic primer
behind the term & technologies
– http://postscapes.com/what-exactly-is-the-internet-of-things-
infographic
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References
• Innovating the Smart Cities, Syam Madanapalli | IEEE Smart Tech
Workshop 2015, http://www.slideshare.net/smadanapalli/innovating-the-
smart-cities
• Kitchin, R., Lauriault, T. and McArdle, G. (2015) Knowing and governing
cities through urban indicators, city benchmarking and real-time
dashboards. Regional Studies, Regional Science 2: 1-28,
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• Towards Smart City: Making Government Data Work with Big Data
Analysis, Charles Mok, 24 September 2015,
http://www.slideshare.net/mok/towards-smart-city-making-government-
data-work-with-big-data-analysis-53176591
• Mining in the Middle of the City: The needs of Big Data for Smart Cities, Dr.
Antonio Jara, http://www.slideshare.net/IIG_HES/mining-in-the-middle-
of-the-city-the-needs-of-big-data-for-smart-cities
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References
• The Big 'Big Data' Question: Hadoop or Spark?
– http://www.datasciencecentral.com/profiles/blogs/the-big-big-data-question-
hadoop-or-spark
• Hadoop vs. Spark: The New Age of Big Data
– http://www.datamation.com/data-center/hadoop-vs.-spark-the-new-age-of-
big-data.html
• Comparing 11 IoT Development Platforms
– https://dzone.com/articles/iot-software-platform-comparison
• IOT Networks
– http://www.slideshare.net/mourcous/iot-networks?qid=77283add-1ef8-438b-
a2b1-18908d4777ea&v=&b=&from_search=2
• 2017 Roundup Of Internet Of Things Forecasts
– https://www.forbes.com/sites/louiscolumbus/2017/12/10/2017-roundup-of-
internet-of-things-forecasts/#55d0f0611480