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WP2: SONY CSL Contribution<br />Delivrables2.4, 2.5<br />Tagging in the Real World<br />Study of sustainability-related is...
Outline<br />Tagging usage in theartisticcommunity<br />Tagging usage for sustainability- related issues<br />Zexe.net <br...
Tagging usage in the real world<br />Social<br />
Tagging the user experience (in the real world)<br />Social<br />Location <br />(GeoTagging)<br />
Tagging the user experience (in the real world)<br /> Social<br />Location <br />(GeoTagging)<br />Sustainability<br />Pol...
Social Justice: Zexe.net (Eugenio Tisseli) <br /><ul><li> Zexe.net = a community memory for representing daily experiences...
 Several campaigns for un(der)-represented communities (Taxi drivers Mexico,  Disabled people Geneva,  MotoboysBrazil)
Tagging  « slices of life ».</li></ul>2008 - Campaign in Geneva about the life of handicapped people<br />
Noise Pollution: NoiseTube.net<br />NoiseTube Participatory approach to monitor noise pollution using mobile phones<br />-...
Accuracy of the phone<br />?=<br />Virtual noise sensor =microphone + software<br />Sound LevelMeter<br />Real-world exper...
Issue 1: Hazard identification<br />Only measurements, No semantic information <br />Measurement done by real sensors<br /...
Issue 1: Hazard identification<br />Only measurements, No semantic information <br />Measurement done by real sensors<br /...
Issue 1: Hazard identification<br />Contextual Tag cloud<br />
Issue 2: <br />Searching/navigating in a large dataset of environmental data<br />Searching by value = Hard for non-expert...
Issue 2: <br />Searching/navigating in  a large dataset of environmental data<br /> Searching by value = Hard for non-expe...
Automatic  generation of contextual Tags<br />Neighbors<br />Roadwork<br />Social tagging<br />
Automatic  generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />>85 dB “risky”<br />[75, 85...
Automatic  generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Patte...
Automatic  generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Patte...
Automatic  generating of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Loudness <br />Signal Patte...
Automatic  generation of contextual Tags<br />Social tagging<br />Roadwork<br />Neighbors<br />Temperature: <br />Loudness...
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Environmental tagging

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a short presentation about Environmental tagging

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  • Geotagging of photos Unrepresented Tagging to representing theirGenivaTagging approachsecondat the level of the individual
  • Wewanted to explore novelapproaches to use tagging in real world situations. web documents. evolution
  • Zexe.netis a set of tools for small communities having social troubles.Zexeallowscommunities to represent and raiseawareness about theirdailyexperiences via taggedpicture and sounds.Tagging was used as a bottom-up way for representing dailyissues and views of the involved groups in a much more accurate way than before. taxi drivers in Mexico City, gypsies in Lleida and León (Spain), prostitutes in Madrid, handicapped people in Barcelona and Geneva, and motorcyclemessengers (calledmotoboys) in Sao Paulo, Brazil.
  • Collecting and representing the collective exposure to noise pollution using mobile phonesInforming the community by
  • skip
  • are excellent at recognizing noise sources&gt; What causes theselevels of pollution?Automatic identificaton = Hard problem Diversity?, anormal sources?
  • are excellent at recognizing noise sources&gt; What causes theselevels of pollution?Automatic identificaton = Hard problem Diversity?, anormal sources?
  • Enrich
  • geocoder
  • The future of tagging
  • Transcript of "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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