ISCC 2013 Conference Keynote on Internet of Things scope and requirements, illustrations and specific use case energy efficiency in office buildings with personal eco-feedback application POEM (Personal Office Energy Monitor)

1. 1
Pervasive Sensing and IoT
Cooking Recipe: Just Add People
and Applications
Milan Milenkovic,
Intel Corporation (Intel Labs),
Santa Clara, CA, USA
milan@intel.com

2. 2
Outline
• The Big Picture
• Pervasive sensing on Internet: ICT transformational and inflection point
• Why that matters and what needs to be built to make it work?
• Reduce to Practice (and learn something while you do it)
• Smart-building use case, prototype and deployment
• Sensors and people and applications (and web technologies)
• Insights and learnings
• Call to action: let’s collaborate on building and deploying (IoT) systems

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The Big Picture: Add Sensors to get
Internet of Everything, Why and How?

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Sensors and Internet (“of things, of everything”)
• Growing number and variety of physical-world sensors are connected to the
Internet
• Recent smart phone sensors: light, Hall, barometer, temperature, humidity,
geomagnetic, accelerometer, gyro, proximity, gesture, GPS, wifi and radios
• Smart cities: air quality, traffic, people, water, road conditions, hazards
• Manufacturing, buildings, home, agriculture, health and fitness, buildings, cars IVI
• (research) WSNs galore
• Why is that important or interesting?
• Everything you know and love on the Internet +
• Transformational change: sensory/sensing Internet, real-world “aware” ICT
• New applications, services, user benefits, business opportunities

5. 5
IoT System View
16 B 50 B

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Need Universal (Pervasive) Sensing Platform: Reqs
• Goal: pervasive sensing fabric for smart cities, IoT
• Facilitate new uses and applications across devices and domains
• Support variety of sensors and sources
• Wireless, embedded anywhere, e.g. agriculture, fitness
• Built-in, legacy: e.g. building-management systems (BMS), traffic
• Built into devices: Phones, tablets, laptops, PCs, STBs, cars
• Software sensors, e.g. user activity, energy monitor, weather svc
• People as sensors: direct feedback, preferences (control, actuation)
• Common: naming, data formats and protocols, storage & access, meta-data
• No big data or analytics on fragmented, undecipherable data
• Also security, manageability, discovery <tackled elsewhere>

7. 7
Reduce to practice: Smart Buildings and
POEM (Personal Office Energy Manager)
project

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Use Case Smart Buildings: Reimagined IT
 Buildings consume 40% of energy, 72% of electricity
 Regulatory and social pressure to reduce consumption
 Efficient energy use = savings & user comfort
 Our approach: enhance IT by
• Adding sensors to ICT, holistic building control
• Engaging users via eco-feedback app (POEM)
 Result
• Energy efficient new and legacy buildings
• Increased occupant comfort, participation

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Personal sensing and UI, POEM notifications, comfort

10. 10
Personal UI: POEM usage comparison screen

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Client integrated sensors: enterprise ready
Smart-Building Sensing Platform Prototype (IT, wireless)

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POEM Pilot Tests
4 months, 40 “real” office users, Paris
5 months, 50 “real” office users, Tokyo
239 sensor boards prepared for
firmware flash and packaging
Sensor kit with USB cable attached to
the back of laptop
User Experience, POEM UI
http://youtu.be/nKS45p5cjd0
Managing Director in end-
user baseline interviews
in France

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“Novel” Sensor Addition: Platform-Integrated Sensors
• Sensors built into or attached to platforms, such as laptops and printers
• energy (sw), temperature, humidity, light, location (including indoor)
• Key advantages:
• Low cost, x10: (re)use host’s processor, power, storage, connectivity
• Ease of enterprise deployment
• Use existing IT infrastructure (WiFi), deployment processes
• … custom WSN have no existing deployment path, battery issues
• Personalization – proximity to user, data from where I am now

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Pilots: Platform-Integrated Sensor Accuracy
Platform sensor 24.28 C +/- 1.35 C
NIST Reference 24.04 C +/- 1.56 C
Difference in the mean <1%
Off-hour Office Temperature Lab Tests
Difference <0.2%
Difference <0.7%
Gradual temperature drop at night
Fast temperature rise in the morning

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Pilots: Temperature Ambient Data
Temperature across hours for user 49 for 3 months
Temperature mean for 45 users

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Initial Learnings and Insights
• Engaging end-users both as consumers and sources of information is vital
• User participation is fun and changes behaviors, impact (e.g. energy)
• Application/service has to be useful and meaningful to the end user to
keep attention and interest
• Proper visualization and data representation, easy to use is hard to do
• People are great sensors, data aggregators/analyzers
• Use of web technologies is the right approach
• Availability, connectivity, tooling, scalability
• Rapid prototype, test, revise and repeat cycle (x long-lead IT approach)

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What’s Next: Expand (sensors, scale, uses),
Build, Deploy, Test & Repeat

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Universal Sensing Prototype and Design (“web-age SCADA”)
• Web-compliant sensor data format, sMAP (UCB)
• HTTP protocol, interoperability, familiarity, tools, extensible
• Web technologies, middleware (rant!!), and programming style
• RESTful web services, sensor publish-subscribe
• Sensor database for the web
• Archival storage, searching and queries, analytics, reports
• Scalability, throughput (ours is NoSQL, document based)
• Run locally or as a cloud service
• Meta-data, personalization, manageability

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Summary and Call to Action
• IoT is here! (also useful and fun)
• Design feasibility and business value test: smart-building and POEM
• Demonstrate usefulness: increase building energy efficiency and user comfort
• Benefits of end-user engagement
• Platform-integrated sensors, sensor-enhanced IT on internet edge
• Benefits: cost, enterprise deployability, personalization
• Universal sensing platform, IoT : call to action, collaboration
• Inclusive and interoperable, across devices and domains
• User-centered: personalization and visualization
• Collaboration opportunity for industry and academia: naming, formats, meta-data
• Build-Test-Deploy-Evaluate and REPEAT

20. POEM team [in order of appearance]: Milan Milenkovic, Scott Shull, Yves Aillerie, Ulf
Hanebutte, Sylvain Sauty, Thanh Dang, Mark Chang, Catherine Huang, Sailaja
Parthasarathy and BLR team, Jun Takei, David Prendergast, Han Pham, Kiyoshi Sakon,
Kazuhide Yamamoto, Wei Thomson
Questions?