9Urban Sensing Apps. Noise mapping Emotion mapping Congestion charging Emotion mappingCongestion chargingLondon Noise MapThe Bio Mapping tool allows the wearer to record their Galvanic Skin Response (GSR), which is a simple indicator of emotional arousal in conjunction with their geographical location. This can be used to plot a map that highlights point of high and low arousal. By sharing this data we can construct maps that visualise where we as a community feel stressed and excitedNoise - unwanted sound - is a universal problem and most of us have been affected by it at some point in our lives.The Noise Mapping England project is the first stage in the development of a National Ambient Noise Strategy for England. The project aims to establish the environmental noise climate across England.Defra (Department for Environment, Food and Rural Affairs) has now launched the London Road Traffic Noise Map, which is fundamental to the Noise Mapping England project.To view the maps, click on the London areaDowning Street Noise MapEmotion Maps of LondonCongestion Map London
10People-Centric Sensing Apps. Heath care applicationsEmergency care (Codeblue), assited living (AlarmNet)Recreational applicationsRunning (Nikeplus), dancing (interactive dance ensembles)Urban gaming
11Emerging Urban Sensing Classes “Personal Sensing” for individualse.g., nikeplus, sensor-enabled cellphone apps., health careGreat potent for commercial success (catch the ipod generation) - youthful early adopters“Peer Sensing” for groupse.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 userse.g., noisemapping, othersProviders (e.g., towns, organizations, enterprises) will have to invest in build out - costly
12Need to exploit existing computing, sensing, wireless breakthroughs and infrastructure to support these emerging urban sensing classes
14Architecture for large-scale sensing based on mobile sensors. Architecture for large-scale sensing based on mobile sensors (most people, but also vehicle mobility - cars, buses, bikes)+ also interaction with static sensor webs
15Captures interaction between people, and, between people and their surroundings.
16Enables general purpose programming of the infrastructure.
17Based on three design principles that promote low cost, scalability, and performance.
18Importantly, mobile people-centric sensors run their own apps. (i. e 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.
19Gains scalability and sensing coverage via people-centric mobility, and its adaptive “sphere of interaction” design.
20Goal is to study and evaluate an “opportunistic sensor network” paradigm
21Characteristics of Existing Systems Small-scale, short-lived, mostly-staticApplication-specificMulti-hop wirelessVery energy-constrainedMobility not an issues of driving factorPeople out of the loop
22Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-specificMulti-hop wirelessVery energy-constrainedMobility not an issues of driving factorPeople out of the loop
23Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-agnosticMulti-hop wirelessVery energy-constrainedMobility not an issues of driving factorPeople out of the loop
24Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-agnosticVery limited multi-hop wirelessVery energy-constrainedMobility not an issues of driving factorPeople out of the loop
25Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-agnosticVery limited multi-hop wirelessNot energy-constrainedMobility not an issues of driving factorPeople out of the loop
26Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-agnosticVery limited multi-hop wirelessNot energy-constrainedMobility is a driving factorPeople out of the loop
27Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-agnosticVery limited multi-hop wirelessNot energy-constrainedMobility is a driving factorPeople in the loop
28Characteristics of MetroSense Large-scale, long-lived, mostly-mobileApplication-agnosticVery limited multi-hop wirelessNot energy-constrainedMobility is a driving factorPeople in the loopSecurity, trust, and privacy important
29My sense of “urban” has changed … from here .. to here
31Sensing across a Large Area is Challenging Imagine theGreen IsTime Square ;-)
32Sensing across a Large Area is Challenging Some simple questions one might askHow 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
33Sensing across a Large Area is Challenging - what scales? Fidelity (Samples/Area)UbisenseCost ($)UbisenseTieredMeshTieredMeshMetroSenseMetroSenseBuildingCampusTownCityScaleBuildingCampusTownCityScale
34What is MetroSense?Relies on the random or not so random mobility of peopleTask sensors to “collect” sensor data and deliver it opportunisticallyOffers in delay-tolerant sensingInfrastructureSensor Access Points (SAPs)Mobile Sensors (MSs)Static Sensors (SSs)OperationsOpportunistic Tasking, Sensing, CollectionOpportunistic Delegation Model (ODM)
35Sensing across a Large Area is Challenging - a proposed Campus-wide Sensor Network SAP locations - Aruba APs
39Opportunistic Delegation Model (ODM) TX rangesensing rangedirect delegationindirect delegationData muleGoal is to extend sensing coverageApplication requires sensed modality ß from “space” during [t1, t2]Delegate “limited” responsibility for “limited” timeDirect and indirect delegation of rolesSensing, tasking, collection and “data muling”Enables new services (ODM Primitives)Virtual sensing range, virtual collection range, virtual static sensor, virtual mobile networkDesign challengesSensing range is dependent on modalityLimited comms. “rendezvous” timeCandidate sensor selection is challengingLikelihood of a mobile reaching a targeted sensing space is probabilistic in natureDelay tolerant characteristics of sensing and collection processessensing “space” of interest
40Virtual Sensing Range - an ODM Primitive/Service TX rangesensing rangeArea of Interest - “sensing space”
46ConclusionNext wave in sensor networks is “people in the loop and not out of loop” sensor networksScale and mobility matters and are challenging in terms of architectural designDidn’t talk about security, privacy, and trust that are central to this effort