one interesting embedded system - sites.pitt.edu
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One interesting embedded system Intel Vaunt small glass Key: AR over devices that “look normal”
https://www.youtube.com/watch?v=bnfwClgheF0
More details at: https://www.theverge.com/2018/2/5/16966530/intel-vaunt-smart-glasses-announced-ar-video
ECE 1161/2161 Embedded Computer System Design 2 1
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ECE 1161/2161Embedded Computer System Design 2
Sensing - 2
Wei Gao
Spring 2019 2
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Indoor Localization GPS-free methods Primary approach: range-based localization Multiple anchors Distances between nodes to anchors measured wirelessly Metrics:
• TOA (Time of Arrival )• TDOA (Time Difference of Arrival)• AOA (Angle of Arrival )• RSSI (Receive Signal Strength Indicator)
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Time of Arrival (ToA)
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• Example: GPS• Satellites broadcast
precise time• Estimate distance to
satellite using signal TOA
• Trilateration
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Acoustic measurement Slower propagation speed -> easier measurement Limitations: Require line of sight Short detection rage
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Available device Wireless Cricket http://cricket.csail.mit.edu/
Indoor range ~10-20m
Ranging precision: 1cm – 3cm
Modes: active beaconing & passive listening
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Angle of Arrival (AoA)
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Use antenna array to measure direction of neighbors Flood beacons, update
bearing along the way Once bearing of three
landmarks is known,calculate position
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RF Signal Strength Distance measurement using RF signals Problematic Susceptible to different signal propagation characteristics
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More on RSSI Path loss characteristics depend on environment (1/rn)
Shadowing depends on environment
Short-scale fading due to multipath adds random high frequency component with huge amplitude (30-60dB) – very bad indoors
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DistanceR
SSI
Path lossShadowingFading
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Range-free Approaches Limitations of range-based localization Expensive hardware deployment Limited detection range
Range-free localization Simple hardware But less accuracy
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Centroid
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Idea: Do not use any ranging at all, simply deploy enough beacons
Anchors periodically broadcast their location
Localization:1. Listen for beacons2. Average locations of all anchors
in range3. Result is location estimate
Good anchor placement is crucial!
Anchors
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Hop-Count Techniques
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Works well with a few, well-located seeds and regular, static node distribution. Works poorly if nodes move or are unevenly distributed.
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Approximate Point In Triangle Area-based approach Anchors divide terrain into triangular regions
A node’s presence inside oroutside of these triangular regions allows a node to narrow the area in which it can potentially reside.
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AlgorithmPseudo Code:Receive beacons (Xi,Yi)
from N anchors
N anchors form triangles.
For ( each triangle Ti Є ){
InsideSet Point-In-Triangle-Test (Ti)
}Position = COG ( ∩Ti ∈InsideSet);
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3N
3N
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Perfect Point in Triangle (PIT) If there exists a direction in which M is departure from points
A, B, and C simultaneously, then M is outside of ∆ABC. Otherwise, M is inside ∆ABC.
Require approximation for practical use Nodes can’t move, how to recognize direction of departure Exhaustive test on all directions is impractical
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M
A
CB
MA
CB
Inside Case Outside Case
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Departure testing Recognize directions of departure via neighbor
exchange RSSI
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M
NAAnchor Receiving nodes
300
350
400
450
500
550
600
1 5 9 13 17 21 25 29 33 37Beacon Sequence Number
Sig
nal
Str
en
gth
(m
v)
1 Foot
5 Feet
10 Feet
15 Feet
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Approximate PIT Test only directions towards neighbors Error in individual test exists, may be masked by APIT
aggregation.
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A
C
1
23
4
M
B
A
CB
A. Inside Case B. OutSide Case
1
23
4
M
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Sources of Possible Errors Exhaustive testing on all possible directions is
impossible False positive: M is near the edge of triangle False negative:
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1
2
4
M
A
C
1
2
4
B
A
CB
A. InToOut Error B. OutToIn Error
3
M
PIT = IN while APIT = OUT PIT = OUT while APIT = IN
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APIT aggregation
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Grid-Based Aggregation
-1-1-10011100
-1-1-10122200
0-1-10112211
00-10112210
0001111100
0001110100
0001000000
-1-1-10000
-1-10100
0-1011
00-1010
00011100
00011000
0001100000High Possibility area
Low possibility area
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Applications Location-based services
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Applications Augmented and Virtual Reality
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