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Low-Power Ambient Sensing in Smartphones for Continuous Semantic Localization
Sinziana Mazilu, Alberto Calatroni, Ulf Blanke, Gerhard Tröster
Wearable Computing Lab
Swiss Federal Institute of Technology (ETH) Zürich
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Where (Usually) Am I?
GPS: Latitude, Longitude Google Maps: Gloriastrasse 12, Zürich Google Services: IfE, ETH, GloriaBar
Physical Location
Logical Location
Office
Cafeteria
Semantic Location
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Routinely Visited Semantic Locations
Why Semantic Localization?
• Location is a powerful cue for daily-life habits [Patridge et al. - On using existing time-use study data for ubiquitous computing applications - Ubicomp08]
• Activity recognition [Liao et al. - Location-based activity recognition – NIPS05]
• Learning daily routines automatically [Liao et al. - Learning and inferring transportation routines – Artif. Intellig. 2007]
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Data for Semantic Localization?
GPS/WiFi/GSM - GPS does not work all the time (e.g., indoors, or phone in the pocket) - Energy expensive
I am actually in the Restaurant B.
Restaurant A, GPS says I am here.
I am here.
Where WiFi/GSM
locates me.
I am in the car, tram, or
outside?
+ Accelerometer, Gyroscope
WiFi/GSM very coarse
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Data for Semantic Localization?
Audio
- Energy expensive - Complex processing algorithms - No privacy regarding activities
Ambient data?
Temperature, humidity, pressure and light
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Ambient Sensors in Smartphones
http://blog.gsmarena.com/samsung-describes-what-each-of-the-nine-sensors-on-the-galaxy-s4-does/ 7
Two Research Questions:
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Is ambient sensing informative for continuous sematic localization?
Is it energy efficient?
Data gathering app
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Does It Look Promising?
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5 days of data collection with the smartphone
Does It Look Promising?
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More Users, More Data
250 hours of collected data 49 days
Does It Still Look Promising?
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Does It Still Look Promising?
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Evaluation
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10s
Mean Std Min Max
Latitude Longitude Velocity …
13 MFCC Mean Std
Supervised Classifier
Detected Location
Labeled Location
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Average accuracies (%) over all categories for each subject dataset, for semantic-location detection
Is Ambient Sensing Data Working?
Is It Energy-Efficient?
Is It Energy-Efficient?
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Theory ...
Is It Energy-Efficient?
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... versus practice
80% battery saving with THPL
Two Research Questions:
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Is ambient sensing informative for continuous sematic localization?
Is it energy efficient?
Routinely visited places
Is That Enough? - Few users?
- Season dependent?
- Labels given by the users (not robust at all)
Label transfer from GPS/WiFi to other sensors
Use additional meteo station data
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