ESE680: Wireless Sensor Networks Special Topics in Embedded Systems Localization - II Lecture #12

1. ESE680: Wireless Sensor Networks Special Topics in Embedded Systems Localization - II Lecture #12 Prof. Rahul Mangharam Wireless Sensor Networks

2. Previous Lecture • What is Localization? • Taxonomy • Applications Basic Approaches • Coarse localization • Fine-Grained Localization • Ranging techniques • Trilateration Wireless Sensor Networks

3. Outline • Interferometric localization (Vanderbilt) • Cricket (MIT) • Motetrack (Harvard) Wireless Sensor Networks

4. The Cricket Indoor Location System Courtesy of: Hari Balakrishnan Bodhi Priyantha, Allen Miu, Jorge Nogueras, John Ankcorn, Kalpak Kothari, Steve Garland, Seth Teller MIT Wireless Sensor Networks Laboratory for Computer Science http://nms.lcs.mit.edu/ Wireless Sensor Networks

5. Motivation • Location-awareness will be a key feature of many future mobile applications • Many scenarios in pervasive computing • Active maps • Resource discovery and interaction • Way-finding & navigation • Stream redirectors • Cricket focuses mainly on indoor deployment and applications Wireless Sensor Networks

6. Where am I?(Active map) Wireless Sensor Networks

7. What’s near me? Find this for me(Resource discovery) Wireless Sensor Networks

8. What’s in this direction?(Viewfinder) Wireless Sensor Networks

9. How do I get to Paja’s office?How do I get to Compaq’s booth at Comdex? Wireless Sensor Networks

10. Desired Functionality • What space am I in? • Room 317, reception area, Compaq’s booth,… • How do I learn more about what’s in this space? • An application-dependent notion • What are my (x,y,z) coordinates? • “Cricket GPS” • Which way am I pointing? • “Cricket compass” Wireless Sensor Networks

11. Design Goals for Cricket • Must determine: • Spaces: Good boundary detection is important • Position: With respect to arbitrary inertial frame • Orientation: Relative to fixed-point in frame • Must operate well indoors • Preserve user privacy: don’t track users • Must be easy to deploy and administer • Must facilitate innovation in applications • Low energy consumption Wireless Sensor Networks

12. System Components • Location inference modules • Hardware, software, algorithms for space, position coordinates, orientation • Programming (using) Cricket • API; language-independent “RPC” • Customized beaconing • Deploying and managing a Cricket deployment • Configuration, security, data management Wireless Sensor Networks

13. Cricket Architecture No central beacon control or location database Passive listeners + active beacons preserves privacy Straightforward deployment and programmability Wireless Sensor Networks

14. Machinery • Obtain linear distance estimates • Pick nearest to infer “space” • Solve for mobile’s (x, y, z) • Determine θ w.r.t. each beacon and deduce orientation vector Wireless Sensor Networks

15. Determining Distance • A beacon transmits an RF and an ultrasonic signal simultaneously • RF carries location data, ultrasound is a narrow pulse • The listener measures the time gap between the receipt of RF and ultrasonic signals • A time gap of x ms roughly corresponds to a distance of x feet from beacon • Velocity of ultra sound << velocity of RF Wireless Sensor Networks

16. Multiple Beacons CauseComplications • Beacon transmissions are uncoordinated • Ultrasonic signals reflect heavily • Ultrasonic signals are pulses (no data) These make the correlation problem hard and can lead to incorrect distance estimates Wireless Sensor Networks

17. Solution • Carrier-sense + randomized transmission • Reduce chances of concurrent beaconing • Bounding stray signal interference • Envelop all ultrasonic signals with RF • Listener inference algorithm • Processing distance samples to estimate location Wireless Sensor Networks

18. Bounding Stray Signal Interference • Engineer RF range to be larger than ultrasonic range • Ensures that if listener can hear ultrasound, corresponding RF will also be heard Wireless Sensor Networks

19. Bounding Stray Signal Interference No “naked” ultrasonic signal can be valid! Wireless Sensor Networks

20. Bounding stray signal interference • Envelop ultrasound by RF • Interfering ultrasound causes RF signals to collide • Listener does a block parity error check • The reading is discarded... Wireless Sensor Networks

21. Preventing repeated interactions • Randomize beacon transmissions: loop: pick r ~ Uniform[T1, T2]; delay(r); xmit_beacon(RF,US); • Optimal choice of T1 and T2 can be calculated analytically • Trade-off between latency and collision probability • Erroneous do Wireless Sensor Networks estimates not repeat Wireless Sensor Networks

22. Estimation AlgorithmWindowed MinMode Wireless Sensor Networks

23. Orientation Wireless Sensor Networks

24. Trigonometry 101 Wireless Sensor Networks

25. Differential Distance Estimation • Problem: for reasonable values of parameters (d, z), (d2 - d1) must have 5mm accuracy Wireless Sensor Networks

26. Making This Idea Work Wireless Sensor Networks

27. Coordinate Estimation Wireless Sensor Networks

28. Deployment: Beacon PlacementConsiderations • Placement should allow correct inference of space • Boundaries between spaces need to be detected • Placement should provide enough information for coordinate estimation • No 4 beacons on same circle on a ceiling • At least one beacon must have θ < 40 degrees Wireless Sensor Networks

29. Problem: Closest Beacon May NotReflect Correct Space Wireless Sensor Networks

30. Correct Beacon Placement • Position beacons to detect the boundary • Multiple beacons per space are possible Wireless Sensor Networks

31. System Administration • Password-based authentication for configuration • Currently, coordinates manually entered • Working on algorithm to deduce this from other beacons • MOREINFO database centrally managed with • Web front-end • Relational DBMS • Challenge: queries that don’t divulge device location, but yet are powerful Wireless Sensor Networks

32. Cricket v1 Prototype Wireless Sensor Networks

33. Deployment Wireless Sensor Networks

34. Some Results • Linear distances to within 6cm precision • Spatial resolution of about 30cm • Coordinate estimation to within 6cm in each dimension • Orientation to within 3-5 degrees when angle to some beacon < 45 degrees • Several applications (built, or being built) • Stream redirection, active maps, Viewfinder, Wayfinder, people locater, smart meeting notifier,… • Probably no single killer app, but a whole suite of apps that might change the way we do things Wireless Sensor Networks

35. Alternative Architecture(Active Badge, Bat Systems) Problems: Privacy; administration; scalability; deployment cost Wireless Sensor Networks

36. Comparisons Wireless Sensor Networks

37. Cricket - Summary • Cricket provides location information for mobile, pervasive computing applications • Space • Position • Orientation • Flexible and programmable infrastructure • Deployment and management facilities Wireless Sensor Networks

38. Summary of Lecture • Several localization implementations • They greatly vary with respect to: • Accuracy • Ease of computation/implementation • Coordination • Application specific • What’s your favorite? Wireless Sensor Networks