Environmental tagging

Tagging in the Real WorldStudy of sustainability-related issues

Nicolas Maisonneuve

WP2: SONY CSL ContributionDelivrables 2.4, 2.5

Outline

NoiseTube.net (3rd Year)

Zexe.net (2nd year)

Ikoru: Armin Linke’s Installation (during the 3 years

Tagging usage in theartistic community

Tagging usage for sustainability- related issues

Tagging usage in the real world

Social

Location (GeoTagging)

Social

Tagging the user experience (in the real world)

Location (GeoTagging)

Social

Sustainability

Pollution exposureSocial justice Carbon Footprint…

Tagging the user experience (in the real world)

Social Justice: Zexe.net (Eugenio Tisseli)

2008 - Campaign in Geneva about the life of handicapped people

Zexe.net = a community memory for representing daily experiences using Folksonomies (via pictures and sound files)

Several campaigns for un(der)-represented communities (Taxi drivers Mexico, Disabled people Geneva, Motoboys Brazil)

Tagging « slices of life ».

Collective Level - Adaptive sensor network at a low cost- Living map showing the shared experience to noise

Green user experience- Phone = environmental instrument- Autonomy to measure noise pollution

Noise Pollution: NoiseTube.netNoiseTube Participatory approach to monitor noise pollution using mobile phones

- Raising awareness (extension of zexe.net principles)- Scientific issue: lack of real data

Issue 1: Hazard identification

Only measurements, No semantic information

Simulated mapMeasurement done by real sensors

New tagging usage: Use people as semantic sensors

Issue 1: Hazard identification

Only measurements, No semantic information

Simulated mapMeasurement done by real sensors

Issue 1: Hazard identification

Contextual Tag cloud

Searching by value = Hard for non-experts Example: meaning of 75 dB(A) ? , lat,lng={2.34,12.5} ?

Issue 2: Searching/navigating in a large dataset of environmental data

Geographical space

Numerical space

Searching by value = Hard for non-experts

Issue 2: Searching/navigating in a large dataset of environmental data

Geographical spaceSemantic space

Numerical space

Semantic exploration of measurementsvia rich context

Limitation of social tagging (not enough data) Enriching the context via automatic generation of contextual tags

Automatic generation of contextual Tags

Social tagging

Roadwork Neighbors

Automatic generating of contextual Tags

Social tagging

Roadwork Neighbors

Machine Tagging = set of classifiers Example : Loudness Classifier

<50 dB “Quiet”

[50, 75] “Annoying”

>85 dB “risky”

[75, 85] “noisy”

Automatic generating of contextual Tags

Social tagging

Roadwork Neighbors

“High variation”

Loudness Signal Pattern

“short-term risky exposure”

Automatic generating of contextual Tags

Social tagging

Roadwork Neighbors

Loudness Signal Pattern

Location

Location type

“outdoor” (with gps)

Street name: “rue Amyot” (Google Map API)

Type: “indoor”

Street name

City Name: “Paris”

City Name

Automatic generating of contextual Tags

Social tagging

Roadwork Neighbors

Loudness Signal Pattern

Time Week: “working day” , “weekend”

Day: “Morning” , “afternoon”, “evening”,”night”

Season (+ GPS sensor): “summer”, “spring”

LocationDay

Week Season

Automatic generation of contextual Tags

Social tagging

Roadwork Neighbors

Loudness Signal Pattern

Weather Conditions Winds: “calm”, breeze” , “storm”

Temperature: “freezing” , “fair”, “hot”

type: “Cloudy”, “raining”,etc..

LocationTime

(At the city level)

Temperature:

TemperatureWinds

type

User-generated tags

Roadwork Neighbors

Loudness Signal Pattern

LocationTime

Weather

Machine-generated tags

Automatic generation of contextual Tags

Semantic profile of the context

Semantic exploration

Automatic generation of contextual Tags

Participatory monitoring of noise pollution using mobile phones

Demo