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Towards Mobile Phone Localization without War-Driving Ionut Constandache , Romit Roy Choudhury , Injong Rhee. Location is an IP address. for content delivery. Location-Based Applications (LBAs). Examples: Location-based recommendations, geo-tagging - PowerPoint PPT Presentation
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Towards Mobile Phone Localization without War-Driving
Ionut Constandache, Romit Roy Choudhury, Injong Rhee
Location is an IP addressLocation is an IP addressfor content delivery
Location-Based Applications Location-Based Applications (LBAs)(LBAs)
Examples:
Location-based recommendations, geo-tagging
GeoLife: shopping list when near a grocery store
TrafficSense: real-time traffic conditions
Location expresses context of user◦Facilitates content delivery
Is GPS the solution?
Pros: Good accuracy Cons: Poor battery lifetime
Is GSM the solution?
Pros: Long battery lifetime Cons: Poor accuracy
What about WiFi Localization?
E.g., SkyHook:
Basic Idea:1. Several trucks war-drive a place2. Create Radio map = <Location: WiFi IDs>3. Distribute map to phones4. Phone user goes to war-driven region, overhears
WiFi IDs5. Reverse Look Up IDs against radio map6. Obtains location
Basic Idea:1. Several trucks war-drive a place2. Create Radio map = <Location: WiFi IDs>3. Distribute map to phones4. Phone user goes to war-driven region, overhears
WiFi IDs5. Reverse Look Up IDs against radio map6. Obtains location
Is Skyhook the solution?
Middle GroundLower Accuracy than GPS, Longer
Battery lifetime Better Accuracy than GSM, Shorter
Battery lifetimebut …
Is Skyhook the solution?
Middle GroundLower Accuracy than GPS, Longer Battery
lifetime Better Accuracy than GSM, Shorter Battery
lifetimebut …
At the cost of: Degraded location accuracy: walking paths ~
60m Reliance on infrastructure (APs) War-driving ($$ + carbon footprint) “NYTimes: Skyhook fleet 500 trucks/drivers”
ContentsContentsCompAcc
Evaluation
Limitations and Future Work
Conclusion
ContentsContentsCompAcc
Evaluation
Limitations and Future Work
Conclusion
GoalsGoals No War-Driving
Cannot drive walking paths (campus, parks, …)
Expensive / Environment unfriendly
No reliance on WiFi infrastructure Rural regions / developing countries
Good accuracy (~GPS)
Improve energy-efficiency Better than Skyhook, GPS
CompAcc: Basic IdeaCompAcc: Basic Idea Direction(compass) +
Displacement(accelerometer) = User’s directional trailDirectional Trail
CompAcc: Basic IdeaCompAcc: Basic Idea Direction(compass) +
Displacement(accelerometer) = User’s directional trail
Compute path signatures ◦ Derived from a local electronic map (Google Maps)
Path Signature …
CompAcc: Basic IdeaCompAcc: Basic Idea Direction(compass) + Displacement(accelerometer) =
User’s directional trail
Compute path signatures ◦ Derived from a local electronic map (Google Maps)
Compare directional trail with path signatures◦ Best match provides the user location
Directional Trail
Path Signature …
Path Signature … Directional Trail
Correct location errors at turns
Path Signature … Directional Trail
Correct location errors at turns
Directional Trail
Path Signature …
ArchitectureArchitectureTile
DatabaseTile
Database
6. Current location(lat A, long B)
2. Report initial location(lat X, long Y)
Tile
4. Direction(Compass)
5. Displacement(Accelerometer)
1. Initial location GPS:(lat X, long Y)
CompAcc
Initial location Directional trail Current location
3. Obtain paths in the user vicinity
Sample Tile:Sample Tile:
Directional trail: Directional trail: displacementdisplacementAccelerometer based step countdisplacement = step_count *
step_size
Directional trail: Directional trail: displacementdisplacementAccelerometer based step countdisplacement = step_count *
step_size
Directional trail: directionDirectional trail: direction
Directional trail: directionDirectional trail: direction
Path SignaturePath SignatureExtract from Google MapsGeodesic formulas
Matching Directional Trail Matching Directional Trail with Path Signatureswith Path Signatures
Dissimilarity Metric:
ci = compass readingspi = path computed directionN = directional trail size
Directional Trail
Path Signature
Fallback Mechanism: A-Fallback Mechanism: A-GPSGPSWhat if the dissimilarity metric is
large?◦Trigger A-GPS
Fallback MechanismFallback Mechanism
Estimated Location
7th Street
5th Street
Main
St.
AA
EE
Fallback MechanismFallback Mechanism
Estimated Location
7th Street
5th Street
Main
St.
AA
EE
ContentsContentsCompAcc
Evaluation
Limitations and Future Work
Conclusion
ResultsResultsCompared 3 localization schemes
◦CompAcc◦Skyhook◦Wifi-War-Walk (We war-droved walking
paths in campus)Metrics Instantaneous Error = distance(estimated, real)
Average Localization Error (ALE) = Average Instantaneous Error
CompAcc Instantaneous CompAcc Instantaneous ErrorError
ResultsResults Average ALE
GPS: 10mCompAcc: 11m
WiFi-War-Walk: 30mSkyhook: 70m
Energy GPS: 10h
CompAcc: 23hWiFi-War-Walk:16h
Skyhook:16h
Directional trail: Directional trail: displacementdisplacementStep count/displacement
accuracy
Trail/Path SizeTrail/Path Size
ContentsContentsCompAcc
Evaluation
Limitations and Future Work
Conclusion
Limitations and Future Limitations and Future WorkWork
Map Generation Manually mark footpaths
User Position Estimated along the Path Apply particle filters to accommodate wide
roads
Multiplexing between Localization Methods Hand-off to Skyhook/GPS when driving Extend to vehicular movement
ContentsContentsCompAcc
Evaluation
Limitations and Future Work
Conclusion
CompAccCompAccToday’s localization technologies
limited Energy- Efficiency Coverage/Accuracy
Rely on simple localization mechanism Need: Compass, Accelerometer and Maps
Evaluation results: ALE: 11m Battery: 23h
CompAcc scales to any mapped part of the world
AdvantagesAdvantages No war-driving No reliance on WiFi infrastructure
Maps available ubiquitously
Improves battery lifetime GPS ~10h Skyhook ~16h Accelerometer ~ 39h Compass ~48h
