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Environmental tagging

a short presentation about Environmental tagging

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Environmental tagging

  1. 1. WP2: SONY CSL Contribution<br />Delivrables2.4, 2.5<br />Tagging in the Real World<br />Study of sustainability-related issues<br />NicolasMaisonneuve<br />
  2. 2. Outline<br />Tagging usage in theartisticcommunity<br />Tagging usage for sustainability- related issues<br />Zexe.net <br />(2nd year)<br />Ikoru: Armin Linke’s Installation <br />(during the 3 years<br />NoiseTube.net <br />(3rd Year)<br />
  3. 3. Tagging usage in the real world<br />Social<br />
  4. 4. Tagging the user experience (in the real world)<br />Social<br />Location <br />(GeoTagging)<br />
  5. 5. Tagging the user experience (in the real world)<br /> Social<br />Location <br />(GeoTagging)<br />Sustainability<br />Pollution exposure<br />Social justice <br />CarbonFootprint<br />…<br />
  6. 6. Social Justice: Zexe.net (Eugenio Tisseli) <br /><ul><li> Zexe.net = a community memory for representing daily experiences using Folksonomies (via pictures and sound files)
  7. 7. Several campaigns for un(der)-represented communities (Taxi drivers Mexico, Disabled people Geneva, MotoboysBrazil)
  8. 8. Tagging « slices of life ».</li></ul>2008 - Campaign in Geneva about the life of handicapped people<br />
  9. 9. Noise Pollution: NoiseTube.net<br />NoiseTube Participatory approach to monitor noise pollution using mobile phones<br />- Raising awareness (extension of zexe.net principles)- Scientific issue: lack of real data<br />Collective Level<br />- Adaptive sensor network at a low cost<br />- Living map showing the shared experience to noise<br />Green user experience<br />- Phone = environmental instrument<br />- Autonomy to measure noise pollution<br />
  10. 10. Accuracy of the phone<br />?=<br />Virtual noise sensor =microphone + software<br />Sound LevelMeter<br />Real-world experiment<br />Experiment In lab<br />Collaboration with<br />Park<br />Person equippedwithsensors<br />After correction: error 2 db<br />Phone + hand free kit<br />Professional sensors<br />
  11. 11. Issue 1: Hazard identification<br />Only measurements, No semantic information <br />Measurement done by real sensors<br />Simulated map<br />
  12. 12. Issue 1: Hazard identification<br />Only measurements, No semantic information <br />Measurement done by real sensors<br />Simulated map<br /> New tagging usage:Use people as semantic sensors <br />
  13. 13. Issue 1: Hazard identification<br />Contextual Tag cloud<br />
  14. 14. Issue 2: <br />Searching/navigating in a large dataset of environmental data<br />Searching by value = Hard for non-experts <br />Example: meaning of 75 dB(A) ? , lat,lng={2.34,12.5} ?<br />Numerical space<br />Geographical space<br />
  15. 15. Issue 2: <br />Searching/navigating in a large dataset of environmental data<br /> Searching by value = Hard for non-experts<br />Numerical space<br />Semantic space<br />Geographical space<br />Semantic exploration of measurements<br />via rich context<br />Limitation of social tagging (not enough data)<br /> Enriching the context via automatic generation of contextual tags<br />
  16. 16. Automatic generation of contextual Tags<br />Neighbors<br />Roadwork<br />Social tagging<br />
  17. 17. Automatic generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />>85 dB “risky”<br />[75, 85] “noisy”<br />[50, 75] “Annoying”<br /><50 dB “Quiet”<br />Machine Tagging = set of classifiers<br />Example : Loudness Classifier <br />
  18. 18. Automatic generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Pattern<br />“High variation” <br />“short-term risky exposure”<br />
  19. 19. Automatic generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Pattern<br />Location type<br />Street name<br />City Name<br />Type: <br />“indoor” <br />“outdoor” (with gps)<br />Location <br />Street name: “rue Amyot” (Google Map API) <br />City Name: “Paris”<br />
  20. 20. Automatic generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Pattern<br />Location<br />Day<br />Week <br />Season<br />Day: <br />“Morning” , “afternoon”, “evening”,”night”<br />Time<br />Week: “working day” , “weekend”<br />Season (+ GPS sensor): “summer”, “spring” <br />
  21. 21. Automatic generation of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Temperature: <br />Loudness <br />Signal Pattern<br />Location<br />Time<br />Temperature<br />Winds<br />type<br />Weather Conditions<br />Temperature: <br /> “freezing” , “fair”, “hot”<br />Winds: “calm”, breeze” , “storm”<br />type: “Cloudy”, “raining”,etc..<br />(At the city level)<br />
  22. 22. Automatic generation of contextual Tags<br />User-generated tags<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Pattern<br />Location<br />Time<br />Weather<br />Machine-generated tags<br />Semantic profile of the context<br />
  23. 23. Automatic generation of contextual Tags<br />Semantic exploration<br />
  24. 24. Participatory monitoring of noise pollution using mobile phones<br />Demo<br />

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