The Cricket Location-Support System
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Transcript of The Cricket Location-Support System
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Nissanka B. Priyantha Anit ChakrabortyHari Balakrishnan
MIT Lab for Computer Sciencehttp://nms.lcs.mit.edu/
The Cricket Location-Support System
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Motivation
• Emergence of pervasive computing environments
• Context-aware applications– Location-dependent behavior
• User and service mobility– Navigation via active maps– Resource discovery
Cricket provides applications information about geographic spaces they are in
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Design Goals
• Preserve user privacy• Operate inside buildings• Recognize spaces, not just physical position
– Good boundary detection is important • Easy to administer and deploy
– Decentralized architecture and control• Low cost and power consumption
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Traditional Approach
Controller/Location database
Base stations
ID = u
Transceivers
• Centralized architecture• User-privacy issues• High deployment cost
ID = u ? ID = u ? ID = u ?
ID = u ?
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Cricket Architecture
Beacon
Listener
SpaceA
SpaceB
SpaceC
I am atC
• Decentralized, no tracking, low cost• Think of it as an “inverted BAT”!
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Determining Distance
• A beacon transmits an RF and an ultrasonic signal simultaneously– RF carries location data, ultrasound is a narrow
pulse– Velocity of ultra sound << velocity of RF
RF data(location name)
Beacon
Listener
Ultrasound(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
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Uncoordinated Beacons
• Multiple beacon transmissions are uncoordinated
• Different beacon transmissions can interfere– Causing inaccurate distance measurements at
the listener
Beacon A Beacon B
timeRF B RF A US B US A
Incorrect distance
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Handling Spurious Interactions
• Combination of three different techniques:– Bounding stray signal interference– Preventing repeated interactions via
randomization– Listener inference algorithms
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Bounding Stray Signal Interference
• RF range > ultrasonic range– Ensures an accompanied RF signal with
ultrasound
tRF A US A
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t
S/b
r/v (max)
S - size of space stringb - RF bit rater - ultrasound rangev - velocity of ultrasound
Bounding Stray Signal Interference
(RF transmission time) (Max. RF US separation at the listener)
S rb v
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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
tRF A US A
RF B US B
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Preventing Repeated Interactions
• Randomize beacon transmissions: loop:
pick r ~ Uniform[T1, T2];delay(r);xmit_beacon(RF,US);
• Erroneous estimates do not repeat• Optimal choice of T1 and T2 can be calculated
analytically – Trade-off between latency and collision probability
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Inference Algorithms
• MinMode– Determine mode for each beacon– Select the one with the minimum mode
• MinMean– Calculate the mean distance for each beacon– Select the one with the minimum value
• Majority (actually, “plurality”)– Select the beacon with most number of readings– Roughly corresponds to strongest radio signal
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Inference Algorithms
Distance(feet)
Frequency A B
5 10
5
A B
Actual distance (feet) 6 8
Mode (feet) 6 8
Mean (feet) 6.14 6.4
Number of samples 7 10
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Closest Beacon May Not Reflect Correct Space
I am atB
Room A Room B
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Correct Beacon Positioning
Room A Room B
x x
I am atA
• Position beacons to detect the boundary
• Multiple beacons per space are possible
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Implementation• Cricket beacon and listener
• LocationManager provides an API to applications
• Integrated with intentional naming system for resource discovery
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Implementation• Cricket beacon and listener
• LocationManager provides an API to applications
• Integrated with intentional naming system for resource discovery
Micro-controller
RF
US
Micro-controller
RF
USRS232
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Static listener performance
Interference
L2
L1
• Immunity to interference– Four beacons within
each others range– Two RF interference
sources• Boundary detection
ability– L1 only two feet
away from boundary
I1 I2
L1 0.0% 0.0%
L2 0.3% 0.4%
I1
I2
% readings due to interference of RF from I1
and I2 with ultrasound from beacons
Room B
Room C
Room A
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Inference Algorithm Error Rates
Error Rates Measured With Listener At L1
0
5
10
15
20
25
30
35
40
45
10 20 30 40 50 60 70 80 90 100
Number of readings
Erro
r Rat
e (%
)
MinMeanMinModeMajority
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Mobile listener performance
Location Algorithm Error Rates
024
68
101214
161820
2 3 4 5 6
Sampling Interval
Erro
r Rat
e (%
)
MinMeanMinModeMajority
Room A Room B
Room C
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ComparisonsBat Active
badgeRADAR Cricket
Track user location?
Yes Yes No, if client has signal map
No
Deploymentconsiderations
Centralized controller +matrix ofsensors
Centralized database + wired IR sensors
RF signal mapping and good radios
Spacenamingconvention
Position accuracy
Few cm Room-wide Room-wide ~2 feet forspatialresolution
Attribute
System
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Summary
• Cricket provides information about geographic spaces to applications– Location-support, not tracking– Decentralized operation and administration
• Passive listeners and no explicit beacon coordination– Requires distributed algorithms for beacon
transmission and listener inference• Implemented and works!
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– Decentralized
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– Preserves user privacy– Good granularity– Component cost U.S. $10
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Beacon positioning
• Imaginary boundaries
• Multiple beacons per location
Location X
X1 X2
X3
ImaginaryBoundary
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Future work
• Dynamic transmission rate with carrier-sense for collision avoidance.
• Dynamic ultrasonic sensitivity.• Improved location accuracy.• Integration with other technologies such as
Blue Tooth.
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Inference algorithms
• Compared three algorithms– Minimum mode– Minimum arithmetic mean – Majority
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Minimizing errors.
• Proper ultrasonic range ensures overlapping RF and ultrasonic signals– RF data 7 bytes at 1 kb/s bit rate– RF signal duration 49 ms – Selected ultrasonic range = 30ft < 49 ft– Signal separation < 49 ms
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Minimizing errors.
• Interfering ultrasound causes RF signals to collide
• Listener does a block parity error check– The reading is discarded
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