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The Place Lab Location Enhanced Computing Project

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  1. The Place Lab Location Enhanced Computing Project Jeffrey Hightower, University of Washington Anthony LaMarca, Anand Balachandran, Yatin Chawathe, Sunny Consolvo, Bill Schilit, Ian SmithIntel Research Seattle Gaetano Borriello, David McDonald, Ed Lazowska, James LandayUniversity of Washington Bill GriswoldUC San Diego Jason HongUC Berkeley

  2. Now, where’s the nearest place I can buy shoulder pads?! …and quickly wants location-enhanced computing. Man discovers mobile computing…

  3. A look back: PARCTab (c. 1993) For “physical world” computing, what’s different? Roy Want, Bill Schilit, Norman Adams, John Ellis, Karin Peterson, David Goldberg, Mark Weiser & Marvin Theimer

  4. PARCTab “Context-Aware” Computing Lessons learned: • Room level precision is “good enough” for a class of useful applications • Lack of ubiquity was a big problem • Privacy was a big concern Location-based File System Proximate Selection Widget

  5. Mobisaic Browser (c. 1994) • Mobile location-enhanced Mosaic • Dynamic URLshttp://places/$(Location).html • Directions to closest suitable bus stop • Active Documents • Scripting inside comments subscribes to “dynamic environment variables” • Reload page when location changes Geoff Voelker & Brian Bershad

  6. The problem is, 10 years later, location and computing have yet to converge. Automotive Marine Chartplotter Aviation GPS/VORTAC Fishfinder GPS Radio GPS handheld E911 cell phone Mapquest Yahoo yellow pages Target store locator Washington DOT Traffic Traffic Cams CompUSA in-store pick-upUW-ITS Busview

  7. I am here We want to drive the location-computing convergence by enabling: • Widely available location-enhanced computing on notebooks, PDAs, and smart phones • A positioning system that is: • Wide-scale, indoor & outdoor • Can be used everywhere • Privacy-observant, low barrier to entry • Can be used by everyone

  8. So how do we enable virtually free device positioning? • Exploit wide-scale WiFi deployment • Urban areas have dense WiFi coverage • WiFi access points beacon unique IDs • Position WiFi devices using a map of “base-station-IDs to location”

  9. Why not use GPS? • GPS is ineffective where most people spend most of their time. • GPS doesn’t work indoors • GPS works poorly in urban canyons • Far more computing devices have WiFi than GPS and this trend will continue. • Modern sensor fusion algorithms allow the use of WiFi and GPS when available.

  10. Seattle Wireless Club Intel Usage logs Sensor-fusion algorithms University of Washington War-drive logs ((( ((( ((( ))) ))) ))) Access points Place Lab architecture Location-enhanced [web] services RF beacon mapping service Location-enhanced requests Service data Data snapshots Client device

  11. What are some of the hard problems? • Building the world wide database of AP positions • Mapping RF beacons in the wild • Providing a privacy model acceptable to users • Who computes my location? • How do I control use of my location information? • Growing the user community

  12. Building the AP position databases • RF beacon map is “user-contributed” • Leverage “war drivers” and WiFi clubs • Collect usage logs from volunteers • Distributed data and reputation management • Distribution for trust: organizations want control over their own data • Distribution for integrity: making it harder to spoof a geo region Seattle Wireless Club Intel Anonymous trace data + reputations Traces Multi-server estimate University of Washington client

  13. Time stamped GPS readings and WiFi signal strengths Mapping RF beacons in the wild • Problem: Signal strength alone is not sufficient to accurately map base station locations • Solution: Add contextual information to improve accuracy • Apply techniques developed at IRS/UW for correcting GPS data and integrating multiple sensor readings over time* • Mine GIS maps for structural information e.g., roads, buildings • Learn simple models of AP antenna propagation t4 -56 db t3 -40 db t1 -95 db t2 -46 db * Don Patterson, Dieter Fox, Dirk Haenel

  14. Privacy-Friendliness • The computation trust problem is addressed by passive sensing RF beacons & client-side computation • War-drive and client log privacy assisted by segmentation and time shifting • Starting an Experience Sample Method (ESM) field study to take an in depth look at user’s privacy expectations

  15. Growing the user community • Project is open-source and collaborative • First beacon location database already live • Offer courseware for web programming classes • Mapping WiFi on campuses • Build a developer community for our new services Web, Ubicomp, Dist Sys, Networking Courses (CSE 590GB – Location Aware Computing)

  16. Summary Place Lab is a grassroots effort to create a global indoor/outdoor positioning system with a low barrier to participation