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.
Automating Google Workspace (GWS) & more with Apps Script
Bringing together smart things and people to realize smarter environments shortened
1. 1
Bringing together Smart Things and People to
realize Smarter Environments
Villanova University, Philadelphia, 9 November 2017, 11:30-12:30
Dr. Diego López-de-Ipiña González-de-Artaza
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina
http://www.morelab.deusto.es
3. 3
From UbiComp … to Smarter
Environments (1998-2017)
• UbiComp
– Context-aware Computing
– Sentient Computing
• AmI: Human-centred UbiComp
• AAL: Ambient Assisted Living
• Internet of Everything
• Human-empowered Smarter Environments
– Smart offices, Industry 4.0, Smart Cities and so on
4. 4
Towards Smarter Environments
• A Smarter Environment is an ecosystem
where “augmented things” and better
informed empowered people
collaborate and adapt their behaviour to
address the environments and their
occupants’ objectives
–They are instances of what could be termed
as Human-centred Ubiquitous Computing
5. 5
Smart Environments
enabling Equation
• Bringing together Smart Things and
People to realize Smarter Environments
–BUT, how do we build Smart Environments?
• Mainly applying three steps which assemble
the UbiComp-enabling equation always
mediated by People:
SENSE + PROCESS = ACT
sense & interact
process/analyse data, intentions
reacting/anticipating
6. 6
Barriers for Smarter Environments
• What are the endemic problem(s) of Smart
Environments (SEs) precluding their wider deployment?
– Many factors but 2 very remarkable ones are ...
• “unfortunate” high demand on infrastructural support!!!
– Sensors & Actuators
– Automation buses and protocols
– Wireless communication links
– Middleware
– Context modelling and Reasoning engines
– And so on and so forth ...
• Lower than needed involvement of users!!!
– Traditionally too centred on technology, i.e. devices before people
– SEs are impossible without better informed more engaged users
7. 7
Research Motivation
• Given that Smart Environments are not possible without infrastructure &
empowered people ...
– How do we alleviate these “unfortunate” needs?
• Our approach/research aim:
– Use and adapt low-cost off-the-shelf hardware infrastructure and combine it
with intelligent middleware and interaction (persuasion) techniques to make
“any” environment and their inhabitants appear “intelligent”
• This talk describes several iterative research efforts towards
democratization of Smarter Environments:
– Iteration 1: Build your own sensing and reasoning infrastructure
– Iteration 2: Concentrate on explicit user-environment interaction
– Iteration 3: Leverage from Web technologies and map them to AmI
– Iteration 4: Enable Dynamic, Flexible & Affordable Smart Environments applied to AAL
– Iteration 5: Towards Smart Cities through Web of Data and IoT
– Iteration 6: Exploring Smarter Sustainable People-empowered environments
9. 9
Internet of Things (IoT)
• 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
11. 11
• 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
Quantified Self & Life
Logging
13. 13
Visual Computing:
Google Glass
• It aimed to produce a mass selling Ubiquitous
Computer
– It was launched in 2013 for a price around 1500$
• It shows available info without using hands
– Accesses Internet through voice commands in a
comparable manner to Google Now
14. 14
Audible Computing
• Configuring as default Interface for the IoT
– Underlying virtual assistants might be the average
user’s primary interface with the IoT
• Amazon Echo
– Alexa API • Google Home
– Features
• Apple AirPods
– Comparison
• Google Pixel Buds
– Features
15. 15
Touch & Proximity Computing:
From NFC to beacons
• NFC enabled Touch Computing but with slow adoption rate
– Solved by its integration into Android devices
• Beacons did not match the high initial expectations but
streamlined proximity computing
• There is the chance to mix both approaches
– Some providers, e.g Estimote, have updated their Bluetooth proximity
beacons by adding programmable NFC
• NFC & Beacons make identification and discovery of Smart
Objects possible to enable Real-world Internet
17. 17
Personal Data
• Defined as "any information
relating to an identified or
identifiable natural person
("data subject")”
18. 18
PROCESS part
• Typically knowledge-based vs. data-based analytics
approaches for sensing and context data have been
confronted
• Simply explained:
– Knowledge-based models use rules to model behaviour with the
support of an expert
• Effective but inflexible
– Somehow alleviated by using probability and fuzzy logic supporting DSS
– Data-driven models use different techniques, e.g. statistical
methods to correlate in time and space events to determine
activities
• Flexible but sometimes hard to explain results
– Hybrid-analytical approaches has been the approach followed to
tackle the INTELLIGENCE, i.e. PROCESS part of UbiComp
20. 20
Location-sensing and Middleware support
for Sentient Computing
• Goals:
– build Sentient Spaces = computerised environments that sense & react
– close gap between user and computer by using context
– make ubiquitous computing reality through Sentient Computing
• by building your own low cost easily deployable infrastructure to make it
feasible!!!
• Developed during PhD research in University of Cambridge
– http://www.cl.cam.ac.uk/research/dtg/
– Supervised by Prof. Andy Hopper
Laboratory for Communications Engineering (LCE)
Cambridge University Engineering Department
England, UK
AT&T Laboratories
Cambridge
Basque Government
Education Department
21. 21
Sentient Computing
• Sentient Computing = computers + sensors + rules:
– distributed sensors capture context, e.g. temperature, identity,
location, etc
– rules model how computers react to the stimuli provided by sensors
– 3 phases: (1) context capture, (2) context interpretation and (3) action
triggering
• To make viable widespread adoption of Sentient Computing
through:
– location sensor deployable everywhere and for everyone
– middleware support for easier sentient application development:
• rule-based monitoring of contextual events and associated reactions
• user-bound service lifecycle control to assist in action triggering
22. 22
TRIP: a Vision-based Location
Sensor
• TRIP (Target Recognition using Image Processing):
– identifies and locates tagged objects in the field of view of a camera
• Requires:
– off-the-shelf technology: cameras+PC+printer
– specially designed 2-D circular markers
– use of well-known Image Processing and Computer Vision algorithms
• Cheap, easily deployable can tag everything:
– e.g. people, computers, books, stapler, etc
• Provides accurate 3-D pose of objects within 3 cm and 2° error
“Develop an easily-deployable location sensor technology with
minimum hardware requirements and a low price”
23. 23
TRIPcode 2-D Marker
• 2-D barcode with ternary code
• Easy to identify bull’s-eye:
– invariant with respect to:
• Rotation
• Perspective
– high contrast
• 2 16 bit code encoding rings:
– 1 sector synchronisation
– 2 for even parity checking
– 4 for bull’s-eye radius encoding
– 39 = 19,683 valid codes
* 10 2011 221210001
TRIPcode of radius 58mm and ID
18,795
1
2 0
sync sector
radius encoding sectors
even-parity sectors
25. 25
A Rule Paradigm for Sentient
Computing
• Sentient systems are reactive systems that perform actions
in response to contextual events
– Respond to the stimuli provided by distributed sensors by triggering
actions to satisfy the user’s expectations based on their current
context, e.g. their identity, location or current activity
• Issues:
– Development of even simple sentient application usually involves the
correlation of inputs provided from diverse context sources
• Observation:
– Modus operandi of sentient applications: Wait until a pre-defined
situation (a composite event pattern) is matched to trigger an action
26. 26
ECA Rule Matching Engine
• Sentient Applications respond to an ECA model:
– monitor contextual events coming from diverse sources
– correlate events to determine when a contextual situation occurs:
• e.g. IF two or more people in meeting room + sound level high THEN
meeting on
– ineffective to force every app to handle same behaviour separately
• Solution ECA Rule Matching Service:
– accepts rules specified by the user in the ECA language
<rule> ::= {<event-pattern-list> => <action-list> }
– automatically registers with the necessary event sources
– notifies clients with aggregated or composite events or executes
actions when rules fire:
• aggregated event = new event summarizing a situation
• composite event = batch of events corresponding to a situation
27. 27
Building a Sentient Jukebox with
ECA Service
within 15000 {/* Enforce events occur in 15 secs time span*/
query PCMonitor$logged_in(user ?userID, host ?hostID) and
test(dayofweek = "Monday") and
Location$presence(user ?userID) before
/* a presence event must occur before any event on its RHS */
((PCMonitor$keyboard_activity(host ?hostID, intensity ?i) and
test(?i > 0.3)) or
(query WeatherMonitor$report(raining ?rainIntensity) and
test(?rainIntensity > 0.2)))
=>
notifyEvent(Jukebox$play_music(?userID, ?hostID, "ROCK"));
}
“If it is Monday, a lab member is logged in and either he is working or it is
raining outside, then play some cheerful music to raise the user’s spirits”
28. 28
LCE Active TRIPboard
• Augments whiteboard with interactive commands issued by placing special
ringcodes in view of a camera observing whiteboard
• Activated by LocALE when person enters room or through web interface
• Registers rules with the ECA Rule Matching Server:
Location$TRIPevent(TRIPcode 52491, cameraID
“MeetingRoomCam”) and
Location$presence(user ?userID, room “LCE Meeting Room”)
=> notifyEvent(CaptureSnapshotEvent(“MeetingRoomCam”,
?userID))
• By means of LocALE, application’s TRIParser component is:
– created in a load-balanced way by randomly selecting one host in a hostGroup
– fault-tolerance by recreation of failed recogniser in another host
30. 30
Mobile-mediated Human Environment
Interaction
• Mobile devices were mainly used for communication,
entertainment or as electronic assistants
• However, their increasing …
– Computational power
– Storage
– Communications (Wi-Fi, Bluetooth, GPRS)
– Multimedia capabilities (Camera, RFID reader)
• Has made them ideal to act as intermediaries between us and
environment:
– Aware (Sentient) Devices
– Powerful devices
– Always with us anywhere at anytime
• Our mobile devices can turn into our UbiComp wand!!!
31. 31
EMI2lets Platform I
• EMI2lets is a middleware to facilitate the development
and deployment of mobile context-aware applications
for AmI spaces.
• Software platform to:
– convert physical environments into Smart Environments (SEs)
• augment daily life objects with computational services
– transform mobile devices into Smart Object remote
controllers
Presented in
UCAmI 2005
32. 32
EMI2lets Platform II
• EMI2lets is an SE-enabling middleware
– addresses the service discovery and interaction aspects
required for active influence on EMI2Objects
• Follows a Jini-like mechanism and Smart Client
paradigm
– once an object is discovered, a proxy of it (an EMI2let) is
downloaded into the user’s device (EMI2Proxy).
– An EMI2let is a mobile component transferred from a
Smart Object to a nearby handheld device, which offers a
graphical interface for the user to interact over that Smart
Object
33. 33
EMI2lets DeploymentEMI2letFramework
Handheld device
(PDA,mobile phone)
EMI2let
EMI2let runtime
EMI2let…
EMI2let
Player
Handheld device
(PDA,mobile phone)
EMI2let runtime
EMI2let…
EMI2let
Player
Smart Object
EMI2let
EMI2let
back-end
EMI2let ServerSmart Object
EMI2let
EMI2let
back-end
EMI2let Server
…
EMI2let
EMI2let
back-end
EMI2let
EMI2let
back-end
…
EMI2let Server
EMI2let
EMI2let
back-end
EMI2let
EMI2let
back-end
…
EMI2let Server
…
EMI2let transfer
EMI2let transfer
EMI2let to back-end
communication
…
EMI2letDesignerEMI2letDesigner
EMI2let
34. 34
EMI2lets Internal Architecture
EMI2let Abstract Programming Model API
Abstract-to-Concrete Mapping
EMI2Protocol over
Bluetooth RFCOMM
SOAP over Wi-Fi,
GPRS/UMTS or
Internet
TRIP-based Service
Discovery
UPnP Service
Discovery
RFID-based Service
Discovery
Bluetooth Service
Discovery (SDP)
Interaction
Mapping
Discovery
Mapping
Presentation
Mapping
Persistence
Mapping
…
35. 35
• We created EMI2lets for different application
domains:
– Accessibility: blind (bus stop), deaf (conference)
– Home/office automation: comfort (lights),
entertainment (WMP), surveillance (camera)
– Industry: robot
– Public spaces: restaurant, parking, airport
EMI2lets Applications
37. 37
Why to reinvent the wheel? Can UbiComp be
enabled through Internet technologies?
• Issues impending Smart Environments wide
deployment remain:
– SEs are possible if and only if:
• Environments are heavily instrumented with sensors and actuators
– Besides, to develop UbiComp apps still very hard!
• Still, mobile devices enable interaction anywhere at
anytime
– User-controlled (explicit) & system-controlled (implicit)
• Is SEs possible without heavy and difficult
instrumentation (or infrastructure-less)?
– YES, IT SHOULD if we want to increase SE adoption!!!
38. 38
Research Aim
• Aim
– Lower the barrier of developing and deploying context-
aware applications in uncontrolled global environments
• Not only my office, home, but what about my city, other
companies, shopping centres, and so on
• HOW?
– Converging mobile and ubiquitous computing with Web
2.0 into Mobile Ubiquitous Physical Web
• Adding context-aware social annotation to physical objects and
locations in order to achieve Smart Environments
39. 39
• What does it do?
– Annotate every physical object or spatial region with info
or services
• Both indoors and outdoors
– Filter annotations associated to surrounding resources
based on user context and keyword filtering
– Enable user interaction with the smart object and spatial
regions both in a PUSH and PULL manner
• Requirement
– Participation in a community of users interested in
publishing and consuming context-aware empowered
annotations and services
• It is not only necessary that technically is viable, engagement of
wide number of users needed!
Sentient Graffiti
41. 41
Multi-modal Interaction
• Sentient Graffiti simplifies human-to-environment interaction
through four mobile mediated interaction modes:
– Pointing – the user points his camera phone to a bi-dimensional visual
marker and obtains all the graffitis associated with it
– Touching – the user touches an RFID tag with a mobile RFID reader
bound to a mobile through Bluetooth (or NFC mobile) and obtains the
relevant graffitis
– Location-aware – mobiles equipped with a GPS in outdoor
environments obtain the relevant nearby graffitis in a certain location
range
– Proximity-aware –the device retrieves all the graffitis published in
nearby accessible Bluetooth servers when it is in Bluetooth range
42. 42
• Available prototypes:
– Marker-associated Graffitis: Virtual Notice Board
• Public/private graffitis, expiration time, remote review, user participation
– Bluetooth-range Graffitis: University Services Booth
• Individual, group and private graffitis, tag-based (OPEN_DAY)
– Location-range Graffitis: Bus Alerter
• Third-party SG clients
• Other possible applications:
– City Tour: Bilbao_tourism Graffiti Domain
– Conference: AmI-07 feedback, expiration after conference
– Publicity: Graffiti expiration after N times
– Friend meetings
– Disco/stadium/office blogs
Application Types & Examples
47. 47
Context Management
• Context information modelled with an ontology
– Base core
– Time and space relations
– Events
• New services might extend the knowledge base
– Classes and instances
– Behaviour rules
• Converts inferred information into OSGi events to which the
different services can register.
– React accordingly to specific events.
48. 48
Context Management
• Two knowledge generation methods in SmartLab:
– Ontological reasoning
• Makes use of RDF (rdf:domain), RFS (rdfs:subPropertyOf) and
OWL (owl:TransitiveProperty) predicates
• Allows to infer implicit knowledge
– Rule-based reasoning
• Allows defining relationship among entities in ontology
• Three types of inference:
– Semantic rules – enable making ontological reasoning based on RDF
and OWL theoretical models
– Knowledge extraction rules – extract new knowledge from ontology’s
implicit one
– Event-inferring rules – generate aggregated events from the context in
the knowledge base
49. 49
Dynamic Affordable AAL
Environments
• AAL offers ICT support towards a more autonomous living of
elderly and dependant people
• However, there are several issues preventing a wider
adoption of AAL:
– ICT support is usually expensive and too complex to deploy
– Collectives such as care staff and relatives have often been neglected
– Care data management is often inadequate and out of time
– Offered interfaces are not suitable for elderly people
• TV is the most universal and accessible device to any elderly person!!
• Our goal:
– Devise a low-cost, easily deployable, usable, evolvable
ICT infrastructure leading towards AAL for All
50. 50
ElderCare Platform
• So, are we ready to provide the AAL Kit?
– ElderCare = a minimum but sufficient set of off-the-shelf
hardware and software infrastructure, which is:
• Affordable: uses mass produced hardware. Our kit costs around
250€
• Unobtrusive: seamlessly integrated with furniture, elderly people
are only required to wear silicon RFID tags
• Easily deployable both at homes and residences
• Usable and accessible by any user collective through iTV, RIA, NFC
• Evolvable – thanks to the adoption of OSGi, it copes with sensing
and acting infrastructure and protocols (Zigbee, ANT, KNX and so
on).
Presented in
IWAAL 2010
51. 51
Interfaces
• ElderCare offers interfaces for three core collectives
in AAL:
– Elderly people – by means of an interactive TV interface, a
remote control or seamlessly integrated web objects
– Caretaking staff – request and register info through NFC
mobiles and touch screens and access a RIA interface
– Relatives – follow elderly people’s life logs through RSS
and microblogging, or access it through a RIA interface
52. 52
ElderCare Architecture
• Presents a distributed architecture with the
following three types of components:
1. Local Systems – AAL Kit instances deployed in
residence rooms or houses
2. Mobile Clients – allow recording care logs on
RFID wristbands through NFC mobiles
3. Central Server for remote management and
service provisioning of remote local systems
54. 54
ElderCare’s Local Systems
• Governed by an Equinox OSGi server managing
services such as:
– TV tuner and widget manager (based on Mplayer)
– Home automation manager
– Alert manager
– Elderly vital sign monitor (Zephyr HxM biometric vest)
– Service Manager on top of BundleContext class
• Offers TV, IoT and RIA interfaces to control and
manage accessibly services
56. 56
Mobile Client
• Care data management is inadequate:
– Relatives often do not have Internet access
– Staff report care details off-line, late and incompletely
– Residents do not always stay at the care centre
• We propose to record care logs in situ through an
NFC mobile on an RFID tag
– The most recent and relevant care information, and
medical profile remains with the patient at all time
• 164 messages can be stored in an 4K RFID wristband which may be
enough for storing logs in a day
58. 58
Publishing Care Logs
• The ElderCare platform does not only record
custom data to enhance the daily activities in
a care centre but ...
– It also exports non privacy-invasive data to
external services such as Twitter from which
authorised followers can follow the lifelog of
residents
60. 60
Towards Smarter Environments: iteration 5
Towards Smart Cities/Things mixing Web of Data and IoT (2010-13)
IES Cities: Internet Enabled Services for cities across Europe
Social Coffee Machine (http://socialcoffee.morelab.deusto.es/)
61. 61
Society estimations by 2050
• Urban populations will grow by 2.3
billion
–70% of world’s population will live in cities
–People with disabilities make up about
15% (≃ 1 billion people), according to the
Wold Health Organization
• People over the age of 60 is expected to triple,
outnumbering children under 15 for the first
time in human history
62. 62
What is a Smart City?
• A means of making available all the services
and applications enabled by ICT to citizens,
companies and authorities that are part of a
city’s system.
– Not only enable more efficient and effective
management of the city resources but increase
comfort and satisfaction from all population
sectors
• Enablers: Open Data + sensor networks + smartphones
63. 63
IES Cities Project
• The IES Cities project promotes user-centric
mobile micro-services that exploit open data
and generate user-supplied data
– Hypothesis: Users may help on improving, extending
and enriching the open data in which micro-services
are based
• Its platform aims to:
– Enable user supplied data to complement, enrich and
enhance existing datasets about a city
– Facilitate the generation of citizen-centric apps that
exploit urban data in different domains
European CIP project
2013-2016
http://iescities.eu
64. 64
IES Cities Stakeholders
• Citizens:
– Users collaborate in the definition of the digital entity of the city.
– Citizen produce and consumes contents (super-prosumer concept).
• SMEs:
– IES Cities will allow the creation of services benefiting the local
businesses.
• ICT-developing companies:
– The platform will enable the chance to create new apps and services
based on user needs, bringing new possibilities and added value.
• Public administration:
– The interaction with the users will enable them to improve and foster the
use of their deployed sensors in urban areas and open databases
65. 65
IES Cities Objectives
• To create a new open-platform adapting the technologies and over taking
the knowledge from previous initiatives.
• To validate and test a set of predefined urban apps across the cities.
• To validate, analyse and retrieve technical feedback from the different
pilots in order to detect and solve the major incidences of the technical
solutions used in the cities.
• To adequately achieve engagement of users in the pilots and measure
their acceptability during the validations.
• To maximize the impact of the project through adequate dissemination
activities and publication of solutions upon a Dual-license model.
Presented in
UCAmI 2015
68. 68
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/
69. 69
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
71. 71
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
73. 73
Collective-awareness for Sustainability
and Social Innovation
• Aims at designing and piloting online platforms creating
awareness of sustainability problems and offering
collaborative solutions based on networks (of people, of
ideas, of sensors), enabling new forms of social innovation.
• Examples:
– Open Democracy, Open Policy Making
– Collaborative/Shared Economy
– Collaborative making co-creation
74. 74
The need for Participative Cities
• Not enough with the traditional resource efficiency
approach of Smart City initiatives
• “City appeal and dynamicity” will be key to attract and
retain citizens, companies and tourists
• Only possible by user-driven and centric innovation:
– The citizen should be heard, EMPOWERED!
» Urban apps to enhance the experience and interactions of the
citizen, by taking advantage of the city infrastructure
– The information generated by cities and citizens must be linked
and processed
» How do we correlate, link and exploit such humongous data for all
stakeholders’ benefit?
• We should start talking about Big (Linked) Data
76. 76
What´s WeLive (I)
A novel We-Government ecosystem of tools (Live) that is
easily deployable in different PA and which promotes co-
innovation and co-creation of personalised public services
through public-private partnerships and the
empowerment of all stakeholders to actively take part in
the value-chain of a municipality or a territory
Open Data Open Services Open Innovation
H2020 project
2015-2017
http://welive.eu
77. 77
What´s WeLive (II)
Stakeholder Collaboration + Public-private Partnership
IDEAS >> APPLICATIONS >> MARKETPLACE
WeLive offers tools to transform the needs into ideas
Tools to select the best Ideas and create the B. Blocks
A way to compose the
Building Blocks into mass
market Applications which
can be exploited through
the marketplace
79. 79
What is Co-Creation? In the
context of Open Government
• Co-creation is a management initiative, or form of economic
strategy, that brings different parties together (for instance, a
company and a group of customers), in order to jointly
produce a mutually valued outcome
– Seeks a consumer-centric view
• In the context of Open Government:
– Co-Creation means that “government and citizens initiate,
design, or implement programs, projects, or activities
together”
80. 80
Co-creation assets in WeLive
The methodological approach is based on four main concepts:
an emerging or existing NEED that a citizen submits to
the PA.
an open CHALLENGE call launched by the PA to involve
the users to participate to solve the reported need.
a possible solution IDEA proposed by a stakeholder to
solve a pending need or to address a challenge.
Resource /
Artefact
ARTEFACT: useful web service (Building Block), open
data, web/mobile app, new policies, new docs published
addressing the challenge to be consumed by the users
WeLive platform
81. 81
CO-IDEATION
CO-
IMPLEMENTATION
CO-EXPLOITATION
URBAN APPS CO-
CREATION
WeLive Co-creation Approach
• In WeLive, a three-step CO-CREATION approach is proposed
where:
– Diverse stakeholders participate in distinct collaborative activities and
events
– The whole process is assisted by https://dev.welive.eu/ platform and
guided through diverse engagement activities
– NEEDs are mapped into IDEAS which are realized into ARTEFACTS:
Mobile or Web Urban Apps or new policies or decisions
82. 82
WeLive Co-creation Process: CO-
IDEATION
Ideation Board:
Collaborative tool to
map NEEDS into
CHALLENGES giving
place to IDEAS
CO-IDEATION
Council CHALLENGES +
Stakeholders’ NEEDs and
comments
Refined Selected IDEAS
83. 83
CO-IDEATION can not be
only techology driven,
supported by Game
Designs, questionnaries,
focus groups
WeLive Co-creation Process: CO-
IDEATION
84. 84
WeLive Co-creation Process: CO-
IMPLEMENTATION
CO-IMPLEMENTATION
Artefacts Available in Service
Catalogue(BBs, mashups, datasets) +
Ideas specification from Ideation
Board
New Artefacts (BBs (Mashups),
datasets, Apps + Mockups) published
in Services Catalogue
Service Composer:
Facilitates creation of
mash-ups (BBs)
WeLive RESTful API &
Developer’s documentation:
Programming API to access
WeLive capabilities
88. 88
WeLive: Open Government
Enabling Infrastructure
PARTICIPATION
• Goes beyond co-Ideation enabling also
co-creation
• Provides distinct interfaces to different
stakeholders, i.e. civil servants, citizens,
SMEs, entrepreneurs/developers
• User and programming interface
• Marketplace to foster public/private
partnerships
ACCOUNTABILITY
• Allows tracing journey from NEEDs to
IDEAS into APPs composed of DATASETS
and BUILDING BLOCKS
• Analytics dashboard enables to
understand impact of platform and apps
• Integration with CNS Marketplace
enables artefacts business model
INCLUSION
• Multilingual interfaces
• Wizard to post new ideas
• Drag and drop interface to enable non-
programmers to assemble simple apps
• CDV component enables to reuse
personal data across apps
TRANSPARENCY
• Goes beyond Open Data portals
• User-generated is also allowed to
complement public open data
• From raw datasets into well-document
easy to consumed micro-services
89. 89
SIMPATICO
• Addresses the need to offer a
more efficient and more effective
experience to companies and
citizens in their daily interaction
with Public Administration (PA)
– Providing a personalized delivery of
e-services based on advanced
cognitive system technologies and by
promoting an active engagement of
people for the continuous
improvement of the interaction with
these services.
H2020 project
2016-2018, EURO6
90. 90
SIMPATICO Project Goal
E-services
Public
Administration
Citizens, Civil
ServantsImproves the dialogue between
citizens & public administration
Adapt the dialogue knowing the
citizen better
• Through their profile
• Adapting the contents to an specific
language
• Hiding form fields whose contents
are known
Take advantage of the wisdom of
the crowd
• So that citizens can ask and answer
questions
• Where citizens can create their own
complex terms glosary which can
help them undertanding the public
procedures
93. 93
GreenSoul: Smart Building Technology for
Persuasive Eco-Awareness
• Aims to achieve higher energy efficiency in public
buildings by altering the way people use energy
consuming shared and personal devices.
– A two-fold strategy:
• Persuade users to increase their energy-awareness and change
their e-consumption habits through a variety of techniques
(persuasive and physical interaction)
• Embed intelligence into the networked devices to allow them
autonomously decide about their operational mode for energy
efficiency purposes.
95. 95
GreenSoul: Contributions & Impact
• Contributions:
– Smart analysers that monitor, incentivize and persuade users
– ‘Green-Souled’ things that turn everyday appliances into smart,
energy aware devices
– Social, mobile apps that engage and create communities of
energy users
– Decision-support system: for automation and persuasion
• Impact: 6. Intelligent control at device level (+5%)
5. Manual control due to behavior change (+4%)
4. Awareness through GreenSoul platform (+3%)
3. Energy awareness spread to personnel (+4%)
2. Awareness of building energy manager (+2%)
1. Smart monitoring (+2%)
97. 97
GreenSoul (GS)-ed Things
• GS-ed Things should fulfil a three-fold purpose:
– Provide energy monitoring capabilities to gather electrical data in real
time and send them to the middleware
– Provide users with feedback and cues that help them understand and
learn how to optimise interaction with devices, appliances and
systems in an energy-wise manner
– Provide to devices control to enable and optimise agreed convenient
energy-modes and practices, e.g. remote switching off/on, reaching
ideal temperatures, etc.
• Defined as pluggable embedded devices which can be
integrated with, and adapted to, different electrical
equipment.
100. 100
I have a dream … people-empowered
Smarter Environments
• Smarter Environments must ensure inclusiveness, economic
viability and environmental sustainability, enabled by:
– Smart Things, e.g. enabling technology for inclusive spaces which
allows to collect data, e.g. people transiting through a given area
– Open Data linked to real-time data gathered by sensor data (physical)
and prosumed data by users (virtual sensors) BROAD DATA
analytics
– User/Thing collaboration: user-conscious apps/things should adapt
to the capabilities of different users, their devices and current context
and influence users’ behaviour
101. 101
Bringing together Smart Things and People to
realize Smarter Environments
Villanova University, Philadelphia, 9 November 2017, 11:30-12:30
Dr. Diego López-de-Ipiña González-de-Artaza
dipina@deusto.es
http://paginaspersonales.deusto.es/dipina
http://www.morelab.deusto.es
102. 102
Abstract
“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.”