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Location in Pervasive Computing. Shwetak N. Patel University of Washington More info: shwetak.com Special thanks to Alex Varshavsky and Gaetano Borriello for their contribution to this content. design:. use:. ubi comp lab. build:. university of washington. university of washington.
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Location in Pervasive Computing Shwetak N. PatelUniversity of Washington More info: shwetak.com Special thanks to Alex Varshavsky and Gaetano Borriello for their contribution to this content design: use: ubicomp lab build: university of washington university of washington Computer Science & Engineering Electrical Engineering
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
Location • Well studied topic (3,000+ PhD theses??) • Application dependent • Research areas • Technology • Algorithms and data analysis • Visualization • Evaluation
Representing Location Information • Absolute • Geographic coordinates (Lat: 33.98333, Long: -86.22444) • Relative • 1 block north of the main building • Symbolic • High-level description • Home, bedroom, work
No one size fits all! • Accurate • Low-cost • Easy-to-deploy • Ubiquitous • Application needs determine technology
Consider for example… • Motion capture • Car navigation system • Finding a lost object • Weather information • Printing a document
Others aspects of location information • Indoor vs. outdoor • Absolute vs. relative • Representation of uncertainty • Privacy model
WiFi Beacons Ad hoc signal strength GPS Physical contact VHF Omni Ranging Ultrasonic time of flight Laser range-finding Array microphone Infrared proximity Stereo camera E-911 Lots of technologies! Ultrasound Floor pressure
Some outdoor applications E-911 Bus view Car Navigation Child tracking
Some indoor applications Elder care
Outline • Defining location • Methods for determining location • Ex. Triangulation, trilateration, etc. • Systems • Challenges and Design Decisions • Considerations
Approaches for determining location • Localization algorithms • Proximity • Lateration • Hyperbolic Lateration • Angulation • Fingerprinting • Distance estimates • Time of Flight • Signal Strength Attenuation
Proximity • Simplest positioning technique • Closeness to a reference point • Based on loudness, physical contact, etc
Lateration • Measure distance between device and reference points • 3 reference points needed for 2D and 4 for 3D
Hyperbolic Lateration • Time difference of arrival (TDOA) • Signal restricted to a hyperbola
Angulation • Angle of the signals • Directional antennas are usually needed
Determining Distance • Time of flight • Speed of light or sound • Signal strength • Known drop off characteristics 1/r^2-1/r^6 • Problems: Multipath
Fingerprinting • Mapping solution • Address problems with multipath • Better than modeling complex RF propagation pattern
Fingerprinting • Easier than modeling • Requires a dense site survey • Usually better for symbolic localization • Spatial differentiability • Temporal stability
Reporting Error • Precision vs. Accuracy
Reporting Error • Cumulative distribution function (CDF) • Absolute location tracking systems • Accuracy value and/or confusion matrix • Symbolic systems
Location Systems • Distinguished by their underlying signaling system • IR, RF, Ultrasonic, Vision, Audio, etc
GPS • Use 24 satellites • TDOA • Hyperbolic lateration • Civilian GPS • L1 (1575 MHZ) • 10 meter acc.
Active Badge • IR-based • Proximity
Active Bat • Ultrasonic • Time of flight of ultrasonic pings • 3cm resolution
Cricket • Similar to Active Bat • Decentralized compared to Active Bat
Cricket vs Active Bat • Privacy preserving • Scaling • Client costs Active Bat Cricket
Ubisense • Ultra-wideband (UWB) 6-8 GHz • Time difference of arrival (TDOA) and Angle of arrival (AOA) • 15-30 cm
RADAR • WiFi-based localization • Reduce need for new infrastructure • Fingerprinting
Place Lab • “Beacons in the wild” • WiFi, Bluetooth, GSM, etc • Community authored databases • API for a variety of platforms • RightSPOT (MSR) – FM towers
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)
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)
Limitations • Beacon-based solutions • 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)
Tower IDs and signals change over time! • GSM localization Coverage?
PowerLine Positioning • Indoor localization using standard household power lines
Signal Detection • A tag detects these signals radiating from the electrical wiring at a given location
Signal Map 1st Floor 2nd Floor
Passive location tracking • No need to carry a tag or device • Hard to determine the identity of the person • Requires more infrastructure (potentially)
Active Floor • Instrument floor with load sensors • Footsteps and gait detection
Motion Detectors • Low-cost • Low-resolution
Computer Vision • Leverage existing infrastructure • Requires significant communication and computational resources • CCTV
Other systems? • Inertial sensing • HVACs • Ambient RF • etc.
Considerations • Location type • Resolution/Accuracy • Infrastructure requirements • Data storage (local or central) • System type (active, passive) • Signaling system