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Applications for Position Tracking Using Mobile Sensors

Applications for Position Tracking Using Mobile Sensors. CS 522 Michael Rudolph. Position Tracking. Triangulation – In a 2D space, the location of unknown point s can be found by measuring its distance from three known reference points. Possible Methods.

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Applications for Position Tracking Using Mobile Sensors

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  1. Applications for Position Tracking Using Mobile Sensors CS 522 Michael Rudolph

  2. Position Tracking • Triangulation – In a 2D space, the location of unknown point s can be found by measuring its distance from three known reference points.

  3. Possible Methods • Time of arrival: measure the time it takes for a signal to go from s to reference points – accurate, but requires fast processing capability that isn’t feasible over the short range of the motes • Received Signal Strength Indication: calculate the distance from each reference point by received signal strength – not as accurate, but doesn’t require as much processing capability

  4. Setup • 4 Mica2 motes programmed with beacon software – these serve as known reference points • Mica2dot sensor attached to radio controlled truck • Mica2dot attached to programming board relaying packets from beacon and track motes over serial port

  5. Mote Placement North Truck West East South

  6. Mobile Mote ID 1 byte Sequence # 1 byte Beacon Mote ID 1 byte Received Signal Strength 2 bytes Received Signal Strength 1 byte Ack 1 byte Timestamp 2 bytes Send Security 1 byte Recv Security 1 byte Packet Structure 42 bytes 36 bytes transmitted 6 bytes Dest. Addr. 2 bytes Msg. Handler 1 byte Group 1 byte Length 1 byte Data Up to 29 bytes CRC 1 byte 6 bytes unsent (bookkeeping)

  7. Flow of Events • Mobile mote on truck transmits every 0.25 sec to beacon motes • Beacon motes transmit raw RSSI data back to base station when a mobile mote message is received.

  8. Footage of truck

  9. Results

  10. Critiques • How does one get an actual distance from the readings in this experiment? • Data is too noisy – how can it be improved?

  11. Getting the Distance • Where ADC is the received signal value • Vbatt is the voltage of the receiver’s battery (3.0 V = 2 x 1.5 V AAs)

  12. Getting the distance • Need to find a reference signal for a known location • Find distance using a free space path loss model • Path Loss = 20 log10(d) + 10 • d = 10(RSSI0 - RSSIn - 10)/20 • This formula does not account for loss from atmospheric distortion or antenna gain

  13. Improving Accuracy • More sensors • Additional readings only confirm closed-form solution • Can choose to use only the closest/best readings in the solution. • Change signal transmission frequency and power • Mica2/Mica2Dot sensors use a digital frequency synthesizer, so they can’t be set to arbitrary frequencies • MicaZ motes use a different radio platform that can be tuned at runtime (frequency range around 2.4 GHz….there’s problems with this)

  14. Getting the distance • The problem in RSSI- based tracking and positioning is the erratic behaviour of the 2.4 GHz frequency in an indoor environment. These inaccuracies in the perceived RSSI values makes it virtually impossible to use any kind of closed form solution model to triangulate the position of the MS. • Need to find a correlation between dBm measurements and distance • MoteTrack has an initialization phase where dBm measurements are associated with known locations

  15. Improving readings • Add some kind of scheduling algorithm to prevent packets lost due to collision • Use multihop networking to retransmit packets to base station (i.e., north beacon mote is too far to send a message to south base beacon)

  16. Questions?

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