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MetroSense
People-Centric Urban Sensing
Andrew T. Campbell, Shane B. Einseman, Nicholas D. Lane, Emiliano Miluzzo, Ronald Perterson
Dartmouth College/ Columbia University
Focus of Sensor Network Research
• Industrial, structural, environmental monitoring systems, military systems, etc.
Characteristics of Existing Systems
• Small-scale, short-lived, mostly-static
• Application-specific
• Multi-hop wireless
• Very energy-constrained
• Mobility not an issues of driving factor
• People out of the loop
Sensor networks at cross roads?
They don’t impact our everyday lives, why?
Follow the people. Follow the money.
New Frontier for Sensing: Urban Timescape
Ron Fricke, timescape is a day in the life of a city (edited version)
QuickTime™ and aYUV420 codec decompressor
are needed to see this picture.
People-centric, mobility counts, scale matters.
Urban Sensing Apps.
• Noise mapping• http://www.noisemapping.org/
• Emotion mapping• http://biomapping.net
• Congestion charging• http://www.cclondon.com/
Congestion Map London
London Noise Map
Emotion Maps of London
Downing Street Noise Map
People-Centric Sensing Apps.
• Heath care applications• Emergency care (Codeblue), assited
living (AlarmNet)
• Recreational applications• Running (Nikeplus), dancing
(interactive dance ensembles)
• Urban gaming • http://www.comeoutandplay.org/
index.php
Emerging Urban Sensing Classes
• “Personal Sensing” for individuals• e.g., nikeplus, sensor-enabled cellphone apps., health care• Great potent for commercial success (catch the ipod generation) -
youthful early adopters
• “Peer Sensing” for groups• e.g., urban gaming, peers apps. • Could be an explosive growth because of existing gaming users
• “Utility Sensing” (system-wide) provides utility to a large population of potential users
• e.g., noisemapping, others• Providers (e.g., towns, organizations, enterprises) will have to
invest in build out - costly
Need to exploit existing computing, sensing, wireless breakthroughs and infrastructure to support these emerging urban sensing classes
What is MetroSense?
Architecture for large-scale sensing based on mobile sensors.
Captures interaction between people, and, between people and their surroundings.
Enables general purpose programming of the infrastructure.
Based on three design principles that promote low cost, scalability, and performance.
Importantly, mobile people-centric sensors run their own apps. (i.e., personal sensing, peer sensing), and, in parallel support “symbiotic sensing” (i.e., utility sensing, peer sensing) of other users in a transparent manner.
Gains scalability and sensing coverage via people-centric mobility, and its adaptive “sphere of interaction” design.
Goal is to study and evaluate an “opportunistic sensor network” paradigm
Characteristics of Existing Systems
• Small-scale, short-lived, mostly-static
• Application-specific
• Multi-hop wireless
• Very energy-constrained
• Mobility not an issues of driving factor
• People out of the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-specific
• Multi-hop wireless
• Very energy-constrained
• Mobility not an issues of driving factor
• People out of the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-agnostic
• Multi-hop wireless
• Very energy-constrained
• Mobility not an issues of driving factor
• People out of the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-agnostic
• Very limited multi-hop wireless
• Very energy-constrained
• Mobility not an issues of driving factor
• People out of the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-agnostic
• Very limited multi-hop wireless
• Not energy-constrained
• Mobility not an issues of driving factor
• People out of the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-agnostic
• Very limited multi-hop wireless
• Not energy-constrained
• Mobility is a driving factor
• People out of the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-agnostic
• Very limited multi-hop wireless
• Not energy-constrained
• Mobility is a driving factor
• People in the loop
Characteristics of MetroSense
• Large-scale, long-lived, mostly-mobile
• Application-agnostic
• Very limited multi-hop wireless
• Not energy-constrained
• Mobility is a driving factor
• People in the loop
• Security, trust, and privacy important
My sense of “urban” has changed … from here
.. to here
Sensing across a Large Area is Challenging
Sensing across a Large Area is Challenging Imagine the
Green Is Time Square ;-)
Sensing across a Large Area is Challenging• Some simple questions
one might ask• How many people are
sitting, running, walking on the Green?
• Where is Andrew on the Green?
• Noise, temperature, allergies distribution across the Green [now, 10AM-10PM, etc.]
• Others
Sensing across a Large Area is Challenging - what scales?
Ubisense
Tiered
Mesh
MetroSense
Building Campus Town City Scale
Co
st (
$)
Ubisense
Tiered
Mesh
MetroSense
Building Campus Town City Scale
Fid
elit
y (S
amp
les/
Are
a)
What is MetroSense?• Relies on the random or not so random
mobility of people• Task sensors to “collect” sensor data
and deliver it opportunistically• Offers in delay-tolerant sensing• Infrastructure
• Sensor Access Points (SAPs)• Mobile Sensors (MSs)• Static Sensors (SSs)
• Operations• Opportunistic Tasking, Sensing,
Collection
• Opportunistic Delegation Model (ODM)
Sensing across a Large Area is Challenging - a proposed Campus-wide Sensor Network
SAP locations - Aruba APs
Sensing Coverage using MetroSense
MetroSense InfrastructureSensor Access Point (SAP) People-centric sensing apps
Dartmouth Pulse BikeNetSensor devices
Interacts with static sensor clouds
MetroSense Operations
opportunistictasking
opportunisticcollection
opportunisticsensing
limitedpeering
comms & ground-truthsensing
Opportunistic Delegation Model (ODM)
sensing “space” of interest
• Goal is to extend sensing coverage• Application requires sensed modality ß from
“space” during [t1, t2]• Delegate “limited” responsibility for “limited” time• Direct and indirect delegation of roles
• Sensing, tasking, collection and “data muling”
• Enables new services (ODM Primitives)• Virtual sensing range, virtual collection range,
virtual static sensor, virtual mobile network
• Design challenges• Sensing range is dependent on modality• Limited comms. “rendezvous” time • Candidate sensor selection is challenging• Likelihood of a mobile reaching a targeted sensing
space is probabilistic in nature• Delay tolerant characteristics of sensing and
collection processes
TX range
sensing range
direct delegation
indirect delegation
Data mule
Virtual Sensing Range - an ODM Primitive/Service
Area of Interest - “sensing space”
Virtual Sensing Range
TX range
sensing range
Virtual Sensing Range - Experimental Result
Virtual Sensing Range
New Transports for Opportunistic Tasking and Collection
• Reliable, secure needs• Limited “rendezvous” time,
mobility, probabilistic sensing/collection, delay tolerant collection
• New transport needs• Lazy uploading• Lazy tasking• Direction-based muling
• Adaptive multihop
Mote broadcasting syncmsgs from GPS unit
GPS Unit
Measuring terrain slope
Measuring pedal speed
Measuring how fast i kick the assof inconsiderate motorists
Bikenet Road Warrior
Skiscape - @ Dartmouth Skiway
Existing Urban Sensing Initiatives
• Nokia’s SensorPlanet• http://www.sensorplanet.org/
• CENS Urban Sensing Summit (May 2006)• http://bigriver.remap.ucla.edu/remap/index.php/
Urban_Sensing_Summit
• CitySense (BBN/Harvard)• MetroSense (Dartmouth/ Columbia)• Others?
Conclusion
• Next wave in sensor networks is “people in the loop and not out of loop” sensor networks
• Scale and mobility matters and are challenging in terms of architectural design
• Didn’t talk about security, privacy, and trust that are central to this effort
What is MetroSense?
Ultimately, its about a new wireless sensor edge for Internet
Thanks for listening!