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EXPOSURESENSE: INTEGRATING
DAILY ACTIVITIES WITH AIR
QUALITY USING MOBILE
PARTICIPATORY SENSING
Bratislav Predic*, Zhixian...
Sensors and smartphones
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
2
...
Smartphones and air quality
monitoring
MOVE COST Final Conference, Technical University of Vienna, September 30th – Octobe...
Activity/air quality correlation
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st,...
ExposureSense
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
5
 Provides...
System architecture
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
6
 Th...
User activities recognition
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013...
User activities recognition
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013...
User activities recognition
engine
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1s...
Acquisition of air quality from
pluggable sensors
MOVE COST Final Conference, Technical University of Vienna, September 30...
Acquisition of air quality from
external sensor network
MOVE COST Final Conference, Technical University of Vienna, Septem...
Daily exposure estimation
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
...
Mobile client front-end
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
13...
Mobile client demonstration
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013...
Mobile client demonstration
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013...
Video demonstrations
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
16
Ex...
Conclusion and future work
MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013....
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ExposureSense Demo

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ExposureSense Demo interactive presentation for MOVE COST Final Conference

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  • Transcript of "ExposureSense Demo"

    1. 1. EXPOSURESENSE: INTEGRATING DAILY ACTIVITIES WITH AIR QUALITY USING MOBILE PARTICIPATORY SENSING Bratislav Predic*, Zhixian Yan† , Julien Eberle‡ , Dragan Stojanovic*, Karl Aberer‡ * University of Nis, Serbia † Samsung Research, USA ‡ EPFL, Switzerland MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013.
    2. 2. Sensors and smartphones MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 2  Modern smartphones accompany users 24/7 and have  Increasing number of integrated sensors (accelerometer, gyroscope, sound/light sensor, camera, compas,...)  Continuously increasing processing and storage capacity  Powerfull sensor platforms  Sensor commonly used in research  Accelerometer : detecting user activity accept/reject call, initiate file transfer, snooze alarm…  Using data mining techniques to infer more complex user physical activities
    3. 3. Smartphones and air quality monitoring MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 3  Air quality monitoring – traditional approach  Fixed or mobile sensing nodes  OpenSense project in Switzerland - sensors on top of public transport vehicles  Smartphones and pollution sensing  Integrated audio analysis as noise pollution indicator  Beyond embedded sensors USB pluggable air quality sensors (ozone O3 sensor)
    4. 4. Activity/air quality correlation MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 4  User’s activity and air quality measurements  Usually treated as fairly independent  ExposureSense  Correlation of activity and air quality data  Bridges the gap and estimates user’s exposure to air pollution  Combination of air quality sensing modes  PM10 monitoring stations on public transport vehicles  Pluggable O3 sensor for smartphones
    5. 5. ExposureSense MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 5  Provides additional knowledge from correlation of data from different sensors  Technical challenges  Develop uniform interface for sensor access  Important for “virtual” sensors capturing phone states  Sensor adapter/wrapper middle layer
    6. 6. System architecture MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 6  The abstraction layer was implemented using sensor probe approach and software components of the Funf – open sensing framework  Main components  User activities recognition  Acquisition of air quality from pluggable sensors  Acquisition of air quality from external sensor network  Daily exposure estimation  Mobile front-end interface
    7. 7. User activities recognition MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 7  Implemented by extended accelerometer probe  Encapsulates inference engine for activity recognition through:  Sampling  Extracting features  Building classification model  Classifying unknown accelerometer streams  J48 classification decision tree used in experiments
    8. 8. User activities recognition MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 8  Accelerometer data features used  Mean value  Standard deviation  Correlation  Acceleration vector intensity mean value  Energy  Entropy  Time and frequency domain
    9. 9. User activities recognition engine MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 9  Features calculated per accelerometer axis in time and frequency domain  J48 decision tree classifier || || || 1     i ix Energy   n i ii xpxpEntropy 1 2 )(log)(
    10. 10. Acquisition of air quality from pluggable sensors MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 10  Participatory air quality sensing complements external sensor networks  Example: OpenSense deploys rich set of air quality sensors on top of public transport vehicles  Smartphones can act as both consumer and contributor to sensing network  As a client of Global Sensor Network
    11. 11. Acquisition of air quality from external sensor network MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 11  Smartphone acts as a contributor to Global Sensor Network (GSN)  Current smartphones lack integrated air quality sensors  USB pluggable sensor platform  Local storage and publish data to GSN  Interpolation with external sensor nodes network data to estimate exposure
    12. 12. Daily exposure estimation MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 12  Correlating inferred activity data with air quality data acquired from pluggable and external sensors  Exposure intensity is estimated based on activity type detected and burned calories per acitivity according to MET research
    13. 13. Mobile client front-end MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 13  Tabbed view system  Raw sensor data view  Frequency domain accelerometer data view  Activity/air quality timeline data view  Map data view  Android broadcast communication mechanism  Service front-end
    14. 14. Mobile client demonstration MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 14  Calories burn MET based calculation  Activity history on timeline and map view CB = (BMR/24) * MET * T BMRmale = (13.75*WKG) + (5*HC) - 6.76*AGE + 66 BMRfemale = (9.56*WKG) + (1.85*HC) - 4.68*AGE +655 CB - calories burnt BMR - basic metabological rate WKG - weight in kg HC - height in cm T - time in h
    15. 15. Mobile client demonstration MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 15  Air quality parameter chooser  Timeline view of chosen air quality parameter  Air quality readings map view  Diary-type calendar history overview  Daily activity and estimated exposure
    16. 16. Video demonstrations MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 16 ExposureSense Android Client Demo
    17. 17. Conclusion and future work MOVE COST Final Conference, Technical University of Vienna, September 30th – October 1st, 2013. 17  Personalized daily diary integrating user activities and air quality  A building block for next generation personalized healthcare applications based on smartphones  Future research directions  Analysis and mining of stored data about user activities, calories burnt and pollution exposure, detecting interesting patterns, providing recommendations  Integrate more sensor inputs and virtual sensors: user interaction, profile, social network activities, etc.
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