1. Pervasive Location-Aware Computing Hari Balakrishnan Networks and Mobile Systems Group MIT Laboratory for Computer Science http://nms.lcs.mit.edu/

2. Why you should care Location-awareness will be a key feature of many future mobile applications Many scenarios in pervasive computing –Navigation –Resource discovery –Embedded applications, sensor systems –Monitoring and control applications The design of good location-aware computing systems cuts across many areas of CS/EE –E.g., sensors, signal processing, networking, mobility, data management, graphics/visualization, planning, HCI, … –Most of the exciting stuff will happen in the next few years!

3. Computing Input Output Processing

4. Network Networked Computing Processing + communication Processing + communication Processing + communication Processing + communication

5. Networked, Context-Aware Computing Network Processing + communication Processing + communication Processing + communication Processing + communication Location information Sensors Actuators Resource information Environmental Context

6. Location-Aware Applications Human-centric –“Finding” applications Embedded –Sensors & actuators –Devices –Monitoring and control System should support both forms

7. This Talk Cricket location infrastructure Some applications System architecture Challenges for the future

8. Cricket Architecture for ubiquitous location-sensing –No single location-sensing technology works everywhere today, particularly indoors Integrates variety of sensory information –GPS: wide-open outdoors –Wireless access info: coarse-grained info –RF + ultrasonic trilateration: indoors and in urban areas Sensor-independent location API

9. Desired Functionality What space am I in? –Room 510, reception area, seminar room,… –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” Goal: Linear precision of a few centimeters, angular precision of a few degrees

10. Design Goals 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

11. Cricket Architecture Beacon Listener Autonomous: No central beacon control or tracking Passive listeners + active beacons facilitates privacy Straightforward deployment and programmability Autonomous: No central beacon control or tracking Passive listeners + active beacons facilitates privacy Straightforward deployment and programmability info = “a1” info = “a2” Estimate distances to infer location

12. Beacons on ceiling B  SPACE=NE43-510 ID=34 COORD=146 272 0 MOREINFO= http://cricket.lcs.mit.edu/ Obtain linear distance estimates Pick nearest to infer “space” Solve for mobile’s (x, y, z) Determine  w.r.t. each beacon and deduce orientation vector Obtain linear distance estimates Pick nearest to infer “space” Solve for mobile’s (x, y, z) Determine  w.r.t. each beacon and deduce orientation vector Machinery Mobile device Cricket listener

13. 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 ultrasound << velocity of RF 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 ultrasound << velocity of RF Determining Distance RF data (space name) Beacon Listener Ultrasound (pulse)

14. Multiple Beacons Cause Complications 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 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 Beacon A Beacon B t RF BRF AUS B US A Incorrect distance Listener

15. 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

16. 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 Engineer RF range to be larger than ultrasonic range –Ensures that if listener can hear ultrasound, corresponding RF will also be heard t RF AUS A

17. t S/b r/v (max) S = size of space advertisement b = RF bit rate r = ultrasound range v = velocity of ultrasound Bounding Stray Signal Interference (RF transmission time) (Max. RF-US separation at the listener) S r b v No “naked” ultrasonic signal can be valid!

18. 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... Envelop ultrasound by RF Interfering ultrasound causes RF signals to collide Listener does a block parity error check –The reading is discarded... t RF AUS A RF BUS B

19. Preventing repeated interactions Randomize beacon transmissions: loop: pick r ~ Uniform[T 1, T 2 ]; delay(r); xmit_beacon(RF,US); Optimal choice of T 1 and T 2 can be calculated analytically –Trade-off between latency and collision probability Erroneous estimates do not repeat

20. Estimation Algorithm Windowed MinMode Distance (feet) Frequency A B 510 5 9Majority 6.47.2Mean (feet) 86Mode (feet) 86Actual distance (feet) BA

21. Orientation relative to B on horizontal plane Mobile device (parallel to horizontal plane) Beacons on ceiling  B Cricket listener with compass hardware Orientation

22. Trigonometry 101 d1d2 z  sin  = (d2 - d1) / sqrt (1 - z 2 /d 2 ) where d = (d1+d2)/2 Heading Beacon Idea: Use multiple ultrasonic sensors and estimate differential distances Cricket Compass Two terms need to be estimated: 1. d2 – d1 2. z/d (by estimating coordinates)

23. Differential Distance Estimation Problem: for reasonable values of parameters (d, z), (d2 - d1) must have 5mm accuracy –Well beyond all current technologies! d2 d1  = 2  (d2 – d1)/ t L Beacon Estimate phase difference between ultrasonic waveforms!

24. Making This Idea Work d1 t 3  d2 d3 4  Estimate 2 phase differences to uniquely estimate d2-d1 Can do this when L 12 and L 23 are relatively-prime multiples of  L 12 L 23 Beacon

25. Beacons on ceiling at known coordinates  B Coordinate Estimation vt 1 vt 2 vt 3 vt 4 (x,y,z) Four equations, four unknowns Velocity of sound varies with temperature, humidity Can be “eliminated” (or calculated!)

26. Deployment: Beacon Placement Considerations 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  < 40 degrees –sin  = (d2 - d1) / sqrt (1 - z 2 /d 2 ), so  goes as tan 

27. Beacon Placement I am at B Room ARoom B Totally arbitrary beacon placement won’t demarcate spaces correctly

28. Correct Beacon Placement Room ARoom B xx I am at A Position beacons to detect the boundary Multiple beacons per space are possible

29. System Configuration & Administration Password-based authentication for configuration Currently, coordinates manually entered Auto-configuration algorithm being developed MOREINFO database centrally managed with Web front-end –Relational DBMS –Challenge: queries that don’t divulge device location, but yet are powerful

30. Ultrasonic sensor RF antenna Ultrasonic sensor RF module (rcv) Atmel processor ListenerBeacon RF module (xmit) RS232 i/f Cricket v1 Prototype Host software libraries in Java; Linux daemon (in C) for Oxygen BackPaq handhelds Several apps…

31. Deployment

32. 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 –Scalable location-aware monitoring (SLAM) apps: MIT library book tracking, asset management, MIT physical plant maintenance

33. Where am I? (Active map)

34. What’s near me? Find this for me (Resource discovery) “Print map on a color printer,” and system sends data to nearest available free color printer and tells you how to get there Location by “intent”

35. What’s in this direction? (Viewfinder) Point-and-use UIs

36. How do I get to Jorg’s office?

37. Large-Scale Monitoring Response time Scale (# sensors) Days/Hours MinutesSeconds Irrigation Physical plant Repair orders Library usage Power, thermal Monitoring & control Asset tracking Fire detection Assisted evacuation Cricket network auto-configuration HazMat response Local navigation Motion detection Leaks, floods Lab equipment monitoring Personal safety Traffic, parking 10 4 10 5 10 6 10 7

38. Requirements Ubiquitous location-sensing Heterogeneous sensor networking/comm. protocols Resource discovery Event handling Query processing Spatial databases Mapping and representation Navigation User interfaces

39. Cricket beacons (Pervasive) Fixed sensor proxy (sensor integration, pruning) Mobile sensor proxy Event-handling & resource discovery network Application event handlers (Distributed) Data stores Tag reader Sensors & actuators Actions Events Sensor Proxy Tagged books, equipment Strawman Architecture

40. Alternative Architecture (Active Badge, Bat Systems) Networked sensor grid Location DB ID = u ID = u? Responder Problems: privacy; administration; scalability; deployment cost Problems: privacy; administration; scalability; deployment cost

41. Comparisons Active Badge BatRADARCricket Tracking?Yes Depends (yes) No DeploymentCentral controller + wired IR sensors Central controller + wired RF /USsensors RF signal map; great radios Beacon placement; wireless Spatial resolution Room? (linear = few cm)Room20cm (linear 5cm) OrientationNo Yes; 3-5 degree prec. ScalabilityAll devices transmit periodically All devices must use same RF net Devices passive; distributed scheduling

42. Summary Location-aware computing poses numerous interesting challenges for CS –An important component of pervasive computing –Integrating real-world information –App spectrum from HCI  Embedded apps Cricket provides location information for mobile, pervasive computing applications –Space, position, orientation –Flexible and programmable infrastructure –Deployment and management facilities

43. Collaborators Bodhi Priyantha Allen Miu Ken Steele Rafael Nogueras Seth Teller Steve Garland Dorothy Curtis Omar Aftab Erik Demaine Mike Stonebraker http://nms.lcs.mit.edu/