PED - Microsoft Research
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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: build: university of washington
ubicomp lab 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
2
Location
Well studied topic (3,000+ PhD theses??)
Application dependent
Research areas
Technology
Algorithms and data analysis
Visualization
Evaluation 3
Location Tracking
4
Representing Location Information
Absolute
Relative
Geographic coordinates (Lat: 33.98333, Long: -86.22444)
1 block north of the main building
Symbolic
High-level description
Home, bedroom, work
5
No one size fits all!
Accurate
Low-cost
Easy-to-deploy
Ubiquitous
Application needs determine technology 6
Consider for example…
Motion capture
Car navigation system
Finding a lost object
Weather information
Printing a document
7
Others aspects of location information
Indoor vs. outdoor
Absolute vs. relative
Representation of uncertainty
Privacy model
8
Lots of technologies!
GPS
WiFi Beacons
VHF Omni Ranging
Ultrasound
Ad hoc signal strength
Floor pressure
Laser range-finding Stereo camera
Array microphone Ultrasonic time of flight
Infrared proximity
E-911 Physical contact 9
Some outdoor applications
E-911
Bus view
Car Navigation
Child tracking 10
Some indoor applications
Elder care
11
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
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Proximity
Simplest positioning technique
Closeness to a reference point
Based on loudness, physical contact, etc
14
Lateration
Measure distance between device and reference points
3 reference points needed for 2D and 4 for 3D
15
Hyperbolic Lateration
Time difference of arrival (TDOA)
Signal restricted to a hyperbola
16
Angulation
Angle of the signals
Directional antennas are usually needed
17
Determining Distance
Time of flight
Signal strength
Speed of light or sound
Known drop off characteristics 1/r^2-1/r^6
Problems: Multipath
18
Fingerprinting
Mapping solution
Address problems with multipath
Better than modeling complex RF propagation pattern
19
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
20
Fingerprinting
Easier than modeling
Requires a dense site survey
Usually better for symbolic localization
Spatial differentiability
Temporal stability 21
Reporting Error
Precision vs. Accuracy
22
Reporting Error
Cumulative distribution function (CDF)
Absolute location tracking systems CDF of Localization error 1 0.9
Percentage
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Error (m)
Accuracy value and/or confusion matrix
Symbolic systems 23
Location Systems
Distinguished by their underlying signaling system
IR, RF, Ultrasonic, Vision, Audio, etc
24
GPS
Use 24 satellites
TDOA
Hyperbolic lateration
Civilian GPS
L1 (1575 MHZ)
10 meter acc.
25
Active Badge
IR-based
Proximity
26
Active Bat
Ultrasonic
Time of flight of ultrasonic pings
3cm resolution
27
Cricket
Similar to Active Bat
Decentralized compared to Active Bat
28
Cricket vs Active Bat
Privacy preserving
Scaling
Client costs
Active Bat
Cricket 29
Ubisense
Ultra-wideband (UWB) 6-8 GHz
Time difference of arrival (TDOA) and Angle of arrival (AOA)
15-30 cm
30
RADAR
WiFi-based localization
Reduce need for new infrastructure
Fingerprinting
31
Place Lab
“Beacons in the wild”
WiFi, Bluetooth, GSM, etc
Community authored databases
API for a variety of platforms
RightSPOT (MSR) – FM towers
32
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)
33
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)
34
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) 35
Beacon-based localization
36
Wifi localization (ex. Ekahau)
37
GSM localization
Tower IDs and signals change Coverage? over time!
38
PowerLine Positioning
Indoor localization using standard household power lines
39
Signal Detection
A tag detects these signals radiating from the electrical wiring at a given location
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Signal Map
1st Floor
2nd Floor 41
2
d ( x, y ) ( ( xi yi ) 2 ) i 1
Example
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2
d ( x, y ) ( ( xi yi ) 2 ) i 1
Passive location tracking
No need to carry a tag or device
Hard to determine the identity of the person
Requires more infrastructure (potentially)
43
2
d ( x, y ) ( ( xi yi ) 2 ) i 1
Active Floor
Instrument floor with load sensors
Footsteps and gait detection
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2
d ( x, y ) ( ( xi yi ) 2 ) i 1
Motion Detectors
Low-cost
Low-resolution
45
2
d ( x, y ) ( ( xi yi ) 2 ) i 1
Computer Vision
Leverage existing infrastructure
Requires significant communication and computational resources
CCTV
46
2
d ( x, y ) ( ( xi yi ) 2 ) i 1
Other systems?
Inertial sensing
HVACs
Ambient RF
etc.
47
Considerations
Location type
Resolution/Accuracy
Infrastructure requirements
Data storage (local or central)
System type (active, passive)
Signaling system 48
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