Presentatie Deusto TEch on Appsforenergy 2013, Take the challenge

1. Promoting Sustainability through
Energy-aware Linked Data Devices
Dr. Diego López-de-Ipiña
16:00-16:30, 18 October 2013, Essent.be, Veldkant 7, Kontich, Belgium
dipina@deusto.es
http://www.morelab.deusto.es
http://paginaspersonales.deusto.es/dipina
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2. Agenda
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IoT need for Linked Data
Energy-aware devices: why and what for?
Energy-aware Linked Data Devices
A practical case: Sustainable Linked Data
Coffee Maker
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3. 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 contextaware, are able to configure themselves and exchange
information, and show “intelligence/cognitive” behaviour
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4. IoT Enabling Technologies
• Low-cost embedded computing platforms, e.g. Arduino or
Rapsberry PI
• Wide availability of low-cost sensors and sensor networks
• Cloud-based Sensor Data Management Frameworks:
Xively, Sense.se
 Democratization of Internet-connected Physical Objects
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5. IoT impulse: Smart Cities, consumer
objects, mobile sensing, smart metering
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6. Current Hype: Healthpromoting Personal Devices
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7. 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
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8. Avoiding Data Silos through
Semantics
• Cut-down semantics is applied to enable machineinterpretable 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
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9. Actionable Knowledge from
Sensorial Data
• Don’t care about the sensors, care about knowledge
extracted from data correlation and 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
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10. Example: Waste-related
LinkedStats
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11. Linked Data Devices
• Devices that apply the Linked Data principles to publish information:
– Use URIs as names for things
– Use HTTP URIs so that people can look up those names
– When someone looks up a URI, provide useful information, using the
standard (RDF, SPARQL)
– Include links to other URIs, so that they can discover more things
• Devices can become big prosumers of Linked Data:
– Progressively more dynamic data coming from increasing amounts of
Internet-connected devices
– About the environment but also about the people themselves, due to
trend towards continuous people-centric enriched data
• Personal Linked Data Cloud vs. Space’s Linked Data Clouds vs. LOD Cloud
• Humongous potential on correlating all these data: energy saving, improve
health monitoring, better human energy balance
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12. Where do we spend Energy?
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13. Eco-Aware Devices
• Society wastes much more energy than it should  tons of
unnecessary CO2 emissions
• Due to inadequate use of electrical devices given the
intangible and invisible nature of energy
– Particularly in shared spaces, e.g. workplaces, where occupants do
not pay the bills directly
• Some studies reveal the enterprises could easily save 20% of
energy waste if measures were taken
• Solution: Eco-aware Devices
– Technological approach: Embedding intelligence within shared
appliances so that they react and adapt upon energy wasting
– Human behavioral change: Team-up with users to reduce
unnecessary energy consumption through feedback and persuasion
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14. Eco-Aware Devices in Action
• They help and motivate people to reduce energy waste by:
– Informing persuasively to concerned users about the misuse of
electronic appliances
– Customizing the operating mode of everyday electrical
appliances as a function of their real usage pattern
– Enabling behaviour export by enabling cooperation among
devices
• How do we ally devices and humans?
– Giving a voice to smart everyday objects to participate in the
energy conservation
• Promoting a sustainable behaviour change publishing info in
Social Networks and LOD Cloud and through seductive interfaces
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15. The 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/
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16. 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
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17. Step 1: Social
• Making it report energy consumptions into
Twitter account: @Social_Coffee
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18. Step 2: Sustainable
• Adding a new state to the coffee machine: auto switchoff which intelligently switches the machine off when it
will not be used (ARIMA time series)
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19. Step 3: Persuasive
• Applying diverse persuasive interfaces to motivate
its users to make a more responsible use
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20. Step 3: Evaluating Persuasiveness
• The impact of eco-feedback was assessed in
an experiment with 3 coffee machines:
– Energy reduction was best in the device that was
instrumented with more suggestive interfaces
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21. Step 4: Cooperative
• Newly deployed coffee makers import intelligence
from others deployed in similar public environments
to avoid cold-start problem
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22. Step 5: Linked Data Device
• Modeling 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
– SSN, SWEET, SWRC, GeoNames, PROV-O vocabularies
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23. Step 5: Linked Data Device
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24. Linked Data Life Cycle
• Linked Data generated by devices passes
through several stages to enhance exploitation:
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25. Conclusion: Energy-aware
Linked Data Devices
• Linked Data Devices allow us to intelligently combine their
machine interpretable data with domain-specific knowledge
• Eco-aware Devices persuade users and adapt upon energy
consumption
• Eco-aware Linked Data Devices communicate reports on energy
consumption to datasets to enable higher level abstractions
meaningful for human or automated decision making
– Our proof of concept, the Sustainable Linked Data Coffee
Maker reduces energy wasting and encourages a better ecobehaviour
• Future work: exploiting energy-consumption datasets, personal
and environmental LOD Clouds
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26. Promoting Sustainability through
Energy-aware Linked Data Devices
Dr. Diego López-de-Ipiña
16:00-16:30, 18 October 2013, Essent.be, Veldkant 7, Kontich, Belgium
dipina@deusto.es
http://www.morelab.deusto.es
http://paginaspersonales.deusto.es/dipina
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27. Acknowledgments
• Thanks to Diego Casado (@dieguich) and Juan López-de-Armentia
(@juanarmentia) for giving birth to the Social Sustainable
Persuasive Cooperative Linked Data-generating Coffee Maker !!!
– http://socialcoffee.morelab.deusto.es/
• Thanks to Mikel Emaldi (@memaldi) & Jon Lázaro (@jon_lazaro) for
the Linked Data support
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28. References
• Energy efficiency in the workplace: the solutions and the users that
advocate them
– http://bit.ly/17OHeMy
• Linked Open Data as the fuel for Smarter Cities. Mikel Emaldi, Oscar Peña,
Jon Lázaro, Diego López-de-Ipiña, book chapter under revision
• Reducing energy waste through eco-aware everyday things. Juan Lópezde-Armentia, Diego Casado-Mansilla, Sergio López-Pérez, Diego López-deIpiña, Mobile Information Systems, vol., no., pp.;
http://dx.doi.org/10.3233/MIS-130172, ISSN 1574-017x, July 2013.
• Semantics for the Internet of Things: Early Progress and Back to the Future.
Barnaghi, P., Wang, W., Henson, C., & Taylor, K. (2012). International
Journal on Semantic Web and Information Systems (IJSWIS), 8(1), 1-21.
doi:10.4018/jswis.2012010101
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