Presentation is loading. Please wait.

Presentation is loading. Please wait.

Location in Pervasive Computing

Similar presentations

Presentation on theme: "Location in Pervasive Computing"— Presentation transcript:

1 Location in Pervasive Computing
Shwetak N. Patel University of Washington More info: Special thanks to Alex Varshavsky and Gaetano Borriello for their contribution to this content design: use: build: ubicomp lab university of washington Computer Science & Engineering Electrical Engineering university of washington

2 A form of contextual information Person’s physical position
Location A form of contextual information Person’s physical position Location of a device Device is a proxy of a person’s location Used to help derive activity information

3 Location Well studied topic (3,000+ PhD theses??)
Application dependent Research areas Technology Algorithms and data analysis Visualization Evaluation

4 Location Tracking

5 Representing Location Information
Absolute Geographic coordinates (Lat: , Long: ) Relative 1 block north of the main building Symbolic High-level description Home, bedroom, work

6 No one size fits all! Accurate Low-cost Easy-to-deploy Ubiquitous
Application needs determine technology

7 Consider for example… Motion capture Car navigation system
Finding a lost object Weather information Printing a document

8 Others aspects of location information
Indoor vs. outdoor Absolute vs. relative Representation of uncertainty Privacy model

9 Lots of technologies! GPS WiFi Beacons Ultrasound Floor pressure
Ad hoc signal strength Laser range-finding VHF Omni Ranging Stereo camera E-911 Array microphone Ultrasonic time of flight Physical contact Infrared proximity

10 Some outdoor applications
Bus view Car Navigation Child tracking

11 Some indoor applications
Elder care

12 Outline Defining location Methods for determining location Systems
Ex. Triangulation, trilateration, etc. Systems Challenges and Design Decisions Considerations

13 Approaches for determining location
Localization algorithms Proximity Lateration Hyperbolic Lateration Angulation Fingerprinting Distance estimates Time of Flight Signal Strength Attenuation

14 Proximity Simplest positioning technique Closeness to a reference point Based on loudness, physical contact, etc

15 Lateration Measure distance between device and reference points 3 reference points needed for 2D and 4 for 3D

16 Hyperbolic Lateration
Time difference of arrival (TDOA) Signal restricted to a hyperbola

17 Angulation Angle of the signals Directional antennas are usually needed

18 Determining Distance Time of flight Signal strength
Speed of light or sound Signal strength Known drop off characteristics 1/r^2-1/r^6 Problems: Multipath

19 Fingerprinting Mapping solution Address problems with multipath Better than modeling complex RF propagation pattern

20 Signal Strength (RSSI)
Fingerprinting SSID (Name) BSSID (MAC address) Signal Strength (RSSI) linksys 00:0F:66:2A:61:00 18 starbucks 00:0F:C8:00:15:13 15 newark wifi 00:06:25:98:7A:0C 23

21 Fingerprinting Easier than modeling Requires a dense site survey Usually better for symbolic localization Spatial differentiability Temporal stability

22 Reporting Error Precision vs. Accuracy

23 Reporting Error Cumulative distribution function (CDF)
Absolute location tracking systems Accuracy value and/or confusion matrix Symbolic systems

24 Location Systems Distinguished by their underlying signaling system
IR, RF, Ultrasonic, Vision, Audio, etc

25 GPS Use 24 satellites TDOA Hyperbolic lateration Civilian GPS
L1 (1575 MHZ) 10 meter acc.

26 Active Badge IR-based Proximity

27 Active Bat Ultrasonic Time of flight of ultrasonic pings
3cm resolution

28 Cricket Similar to Active Bat Decentralized compared to Active Bat

29 Cricket vs Active Bat Privacy preserving Scaling Client costs
Active Bat Cricket

30 Ubisense Ultra-wideband (UWB) 6-8 GHz
Time difference of arrival (TDOA) and Angle of arrival (AOA) 15-30 cm

31 RADAR WiFi-based localization Reduce need for new infrastructure

32 Place Lab “Beacons in the wild” Community authored databases
WiFi, Bluetooth, GSM, etc Community authored databases API for a variety of platforms RightSPOT (MSR) – FM towers

33 ROSUM Digital TV signals
Much stronger signals, well-placed cell towers, coverage over large range Requires TV signal receiver in each device Trilateration, 10-20m (worse where there are fewer transmitters)

34 Comparing Approaches Many types of solutions (both research and commercial) Install custom beacons in the environment Ultra-wideband (Ubisense), Ultrasonic (MIT Cricket, Active Bat), Bluetooth Use existing infrastructure GSM (Intel, Toronto), WiFi (RADAR, Ekahau, Place Lab), FM (MSR)

35 Limitations Beacon-based solutions Using existing infrastructure
Requires the deployment of many devices (typically at least one per room) Maintenance Using existing infrastructure WiFi and GSM Not always dense near some residential areas Little control over infrastructure (especially GSM)

36 Beacon-based localization

37 Wifi localization (ex. Ekahau)

38 Tower IDs and signals change over time!
GSM localization Coverage?

39 PowerLine Positioning
Indoor localization using standard household power lines

40 Signal Detection A tag detects these signals radiating from the electrical wiring at a given location

41 Signal Map 1st Floor nd Floor

42 Example

43 Passive location tracking
No need to carry a tag or device Hard to determine the identity of the person Requires more infrastructure (potentially)

44 Active Floor Instrument floor with load sensors
Footsteps and gait detection

45 Motion Detectors Low-cost Low-resolution

46 Computer Vision Leverage existing infrastructure
Requires significant communication and computational resources CCTV

47 Other systems? Inertial sensing HVACs Ambient RF etc.

48 Considerations Location type Resolution/Accuracy
Infrastructure requirements Data storage (local or central) System type (active, passive) Signaling system

Download ppt "Location in Pervasive Computing"

Similar presentations

Ads by Google