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“Did you see Bob?”: Human Localization using Mobile Phones Ionut Constandache

“Did you see Bob?”: Human Localization using Mobile Phones Ionut Constandache Co-authors: Xuan Bao , Martin Azizyan , and Romit Roy Choudhury. Localization Technologies. Outdoor Driving directions  GPS, Skyhook Indoor

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“Did you see Bob?”: Human Localization using Mobile Phones Ionut Constandache

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  1. “Did you see Bob?”: Human Localization using Mobile Phones IonutConstandache Co-authors: XuanBao, Martin Azizyan, and Romit Roy Choudhury

  2. Localization Technologies • Outdoor Driving directions  GPS, Skyhook • Indoor Localization in office  Cricket, Radar,BAT • Energy-Efficient Continuous localization  EnLoc, RAPS • Logical Context-aware ads  SurroundSense

  3. Localization Technologies • Outdoor Driving directions  GPS, Skyhook • Indoor Localization in office  Cricket, Radar,BAT • Energy-Efficient Continuous localization  EnLoc, RAPS • Logical Context-aware ads  SurroundSense Human Localization: Guiding a user to finding another person

  4. Usage Scenario Bob Alice

  5. Usage Scenario Where is Bob? Please escort me to Bob. Bob Alice

  6. Usage Scenario Where is Bob? Please escort me to Bob. Bob Alice

  7. Usage Scenario Where is Bob? Please escort me to Bob. Bob Alice Provide an electronic Escortsystem.

  8. Usage Scenario 20 steps North 5 steps East Bob N Alice’s Phone

  9. Usage Scenario Alice’s Phone

  10. Usage Scenario Bob Alice’s Phone

  11. Human Localization • Finding Bob in unfamiliar place (E.g. library, mall, engineering building)

  12. Human Localization • Finding Bob in unfamiliar place (E.g. library, mall, engineering building)

  13. Human Localization • Finding Bob in unfamiliar place (E.g. library, mall, engineering building) • Better for Alice to be escorted to Bob

  14. Human Localization • Finding Bob in unfamiliar place (E.g. library, mall, engineering building) • Better for Alice to be escorted to Bob Challenges: • Bob’s location unknown

  15. Human Localization • Finding Bob in unfamiliar place (E.g. library, mall, engineering building) • Better for Alice to be escorted to Bob Challenges: • Bob’s location unknown Even if known still require … • WALK-able routes to Bob

  16. Human Localization • Finding Bob in unfamiliar place (E.g. library, mall, engineering building) • Better for Alice to be escorted to Bob Challenges: • Bob’s location unknown Even if known still require … • WALK-able routes to Bob • Once in his vicinity, identify Bob

  17. Can current localization schemes help?

  18. Can current localization schemes help? too heavy on requirements … • Infrastructure: specialized hardware (e.g. Cricket, BAT, etc.) or • War-driving: build fingerprint DB (e.g. Radar, Skyhook, etc.)

  19. Can current localization schemes help? too heavy on requirements … • Infrastructure: specialized hardware (e.g. Cricket, BAT, etc.) or • War-driving: build fingerprint DB (e.g. Radar, Skyhook, etc.) … need lightweight localization solution

  20. Contents • Escort • Evaluation • Limitations and Future Work • Conclusion

  21. Contents • Escort • Evaluation • Limitations and Future Work • Conclusion

  22. Our Solution • Accelerometers/compasses track human movements • Standard sensors in mobile phones • Each user has a trail trail

  23. Our Solution • Accelerometers/compasses track human movements • Standard sensors in mobile phones • Each user has a trail trail stepi, directioni > = TRAIL <

  24. Our Solution • Accelerometers/compasses track human movements • Standard sensors in mobile phones • Each user has a trail trail

  25. Our Solution • Deploy coordinate system to localize users • Any (fixed) location can be the origin • N, E directions are the Y, X axises E Origin N

  26. Our Solution • Users join the coordinate system • When passing the origin • At encounters with users already in the system E (0,0) Origin N

  27. Our Solution • Users join the coordinate system • When passing the origin • At encounters with users already in the system (x,y) E Origin N

  28. Our Solution • Users join the coordinate system • When passing the origin • At encounters with users already in the system (x,y) (x,y) E Origin N

  29. How does Escorting work?

  30. How does Escorting work? C B A D

  31. Escort Service Cloud A’s Trail C B A D

  32. Escort Service Cloud A’s Trail C B A D

  33. Escort Service Cloud C B A D

  34. Escort Service Cloud C B A D

  35. Escort Service Cloud C B IBC A IBD D IAC

  36. Escort Service Cloud C B IBC A IBD D IAC

  37. Trail Graph Escort Service Cloud B C IBC A IBD IAC D C B IBC A IBD D IAC

  38. Trail Graph C B IBC IAC D A IBD

  39. Escort along the Trail Graph C IAC D Bob Alice B A IBC IBD

  40. Escort along the Trail Graph C IAC D Bob Alice B A IBC IBD

  41. Escort along the Trail Graph C IAC D Bob Alice B A IBC IBD

  42. Escort along the Trail Graph C IAC D Bob Alice Alice guided along user trails: Trails need to be accurate B A IBC IBD WALK-able routes

  43. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

  44. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

  45. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

  46. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

  47. Challenges • Trails drift: acc. missed steps, compass biases t2 θ Compass bias t1

  48. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

  49. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

  50. Challenges • Trails drift: acc. missed steps, compass biases t2 t1

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