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ParticipatorySensingfor urbanpolllution<br />a new role for citizens<br />a  new instrument to observe population/local co...
Data gathering: a generalproblem<br />Water: “U.N. has a limited success to get accurate information on water infrastructu...
Noise/air pollution monitoring<br />Air pollution- Los Angeles<br />Noise pollution in Mumbai<br /><ul><li>Important envir...
(long term) health, social and economic impacts
An increasing problem, especially in developing countries
Growing public concern & effort (European Directive  -2002)
but limited success of environmental policies
Complexity of monitoring the real exposure of the population</li></li></ul><li>Noise/air pollution monitoring<br />#1 issu...
 Location-based exposure (not population)
Cost
 Modeling emission (not exposure)
 Uncertainty of the results
 Real-time: hazard detection?
 Cost</li></li></ul><li>Noise/air pollution monitoring<br />#2 issue: Limited role of citizens in pollution management<br ...
 No real citizen participation despite international agreements</li></ul>“Environmental issues are best handled with the p...
What if every mobile device <br />had an noise (air) sensor? <br />NoiseTube Project: Newgreen user experience<br /><ul><l...
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NoiseTube: Participatory sensing for noise pollution via mobile phones

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Participatory sensing for urban pollution
Research on a participatory approach empowering people in the monitoring of noise pollution via their mobile phones to collect their environmental conditions and cartography their collective exposure
http://noiseTube.net

Veröffentlicht in: Technologie
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NoiseTube: Participatory sensing for noise pollution via mobile phones

  1. 1. ParticipatorySensingfor urbanpolllution<br />a new role for citizens<br />a new instrument to observe population/local communitiesexposure<br />Nicolas Maisonneuve – Associate Researcher <br />SONY Computer science Laboratory Paris <br />Sep - 2009<br />
  2. 2. Data gathering: a generalproblem<br />Water: “U.N. has a limited success to get accurate information on water infrastructure and treatment systems”<br />[Poor data, weak agencies hamstring U.N. environmental oversight, NY Times, 2009]<br />Food: “Agricultural statistics has deteriorated over time” - weak estimation of globalrice/wheat productions<br />- fisheries data outdated<br />[Food and Agriculture Organization, Audit 2009]<br />Health: ”Exposure measures are sometimes completely lacking, frequently incomplete or otherwise uncertain”. <br />[Uncertainty and Data Quality in Exposure Assessment, Wolrd Health Organization, 2008]<br />
  3. 3. Noise/air pollution monitoring<br />Air pollution- Los Angeles<br />Noise pollution in Mumbai<br /><ul><li>Important environmental issues in cities
  4. 4. (long term) health, social and economic impacts
  5. 5. An increasing problem, especially in developing countries
  6. 6. Growing public concern & effort (European Directive -2002)
  7. 7. but limited success of environmental policies
  8. 8. Complexity of monitoring the real exposure of the population</li></li></ul><li>Noise/air pollution monitoring<br />#1 issue: Lack of real exposure data of people<br />Emission modeling + Sensor network<br />Few sensors in Paris<br /> noise map of Paris<br /><ul><li>Sparsity (Paris: 6 sensors for noise, 10 sensors for air quality)
  9. 9. Location-based exposure (not population)
  10. 10. Cost
  11. 11. Modeling emission (not exposure)
  12. 12. Uncertainty of the results
  13. 13. Real-time: hazard detection?
  14. 14. Cost</li></li></ul><li>Noise/air pollution monitoring<br />#2 issue: Limited role of citizens in pollution management<br /><ul><li> Urban pollution = anthropogenic effect
  15. 15. No real citizen participation despite international agreements</li></ul>“Environmental issues are best handled with the participation of all concerned citizens..” [Principle 10, Rio Declaration, 1992]<br />Needing to involve the public in the debate :<br /> to get a better representation of their environmental conditions<br /> To interact in a more direct and powerful way<br />
  16. 16. What if every mobile device <br />had an noise (air) sensor? <br />NoiseTube Project: Newgreen user experience<br /><ul><li> Phone = lowcostmeasurementdevice
  17. 17. Personalizedenvironmental information (healthdevice) </li></ul>Issue #2 - Social/political sciences <br /> Citizen empowerment<br /><ul><li> Citizens in the loop: reporting directly their environmental conditions
  18. 18. Building collective maps of their shared exposure to noise </li></ul>Issue #1 - Environmental/ health Sciences<br /> Supplying real exposure data<br /><ul><li> Low cost adaptive sensor network
  19. 19. Collecting fine-grained real data</li></li></ul><li>Why now?Opportunity of P.S. in environmental context<br />+<br />+<br /> Democratization of powerful & rich-sensor phones<br />Transferring production & collaboration practices from the digital world (web2.0) into the physical world by providing simple tools to observe environmental issues using today mobile devices<br />Growing public concern<br />Cultural shift in digital world (Web 2.0)<br /><ul><li>Autonomy/freedom (no need to wait official/expert)
  20. 20. New opportunities for public discourse</li></li></ul><li>How does it works?<br />
  21. 21. Challenge 1: accuracy<br />Signal processing algorithm to compute Leq(A)<br />+<br />+<br />Phone in hand <br />Handsfree kit <br />Phone in pocket<br />Phone as noise sensor<br />Leq<br />A-weighted filter <br />Phone specific correction function<br />± 6.5 dB <br />± 2.5 dB <br />± 4.5 dB <br />Experiments to evaluate accuracy<br />
  22. 22. Challenge 2: Contextualizing environmental data<br />Why do we need the context? add meaning to raw data <br />1- Hard to search in numericaldatasets for humans<br /> Meaning of 75 dB(A): bad /good? Lat,Lng={2.34, 12.5}: which street?<br />2- Hard to identify the source of pollution with only numerical data <br />Only measurements, No semantic information <br />Measurement done by real sensors<br />Simulated map<br />
  23. 23. Challenge 2: Contextualizing environmental data<br /> New tagging usage: People as semantic sensors for pollution <br />Great but limited (amount of) contextual information<br />
  24. 24. Challenge 2: Contextualizing environmental data<br /> Machine tagging: Enriching the context with classifiers<br />Roadwork<br />Neighbors<br />Loudness <br />Noise Exposure<br />Signal Pattern<br />Location type<br />Location<br />Street name<br />City Name<br />Day<br />Week <br />Time<br />Season<br />Type<br />Winds<br />Weather<br />Temperature<br />Mobility<br />User Activity<br />
  25. 25. Challenge 3: visualisation <br /><ul><li>Exposure layer
  26. 26. Semantic layer
  27. 27. Contextual information
  28. 28. Contribution layer </li></ul>Google Earth<br />+ Web-based<br />Real-time collective exposure <br />
  29. 29. Challenge 4: Sharing<br />Connected to the people <br /><ul><li>ELog: Environmental log “See the digital traces of my exposure to pollution“
  30. 30. New Grid for personal environmental information: Sprending environmental information through Social Network (Twitter) </li></ul>Widget on blog<br />
  31. 31. Citizens empowerment<br />Case study: Exposure to noise in mass transit system<br />“recent [US] public health studies have identified several sources of environmental hazards associated with mass transit, including excessive noise, a large and growing problem in urban settings” ( Science daily June 2009)<br />Paris Subway - 2008<br /><ul><li>No public information about exposure to noise
  32. 32. Building exposure map of 2 lines</li></li></ul><li>Conclusion<br /> NoiseTube: Participatory model to monitor noise pollution using mobile phones <br />Newgreen user experience<br />“Elog” (Exposure log): Reporting and sharing personal exposure to the community<br />Low cost adaptive sensor network supplying real exposure data<br />Future work <br /><ul><li>Experimentation: BruitParif, open Lab , Brussels, India, Italy)
  33. 33. Data quality of peer production system in the physical world
  34. 34. Injectingsemantics to transform large raw data intoactionableknowledge
  35. 35. Mechanism to support cooperation / collective action</li>

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