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Camazotz : Multimodal Activity-Based GPS Sampling

Raja Jurdak , Philipp Sommer , Branislav Kusy , Navinda Kottege , Christopher Crossman, Adam McKeown , David Westcott Autonomous Systems Lab, CSIRO ICT Centre, Brisbane, QLD, Australia CSIRO Ecosystem Sciences, Cairns, QLD, Australia Junction 2013.04.29. Camazotz :

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Camazotz : Multimodal Activity-Based GPS Sampling

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  1. Raja Jurdak, Philipp Sommer, BranislavKusy, NavindaKottege,Christopher Crossman, Adam McKeown, David WestcottAutonomous Systems Lab, CSIRO ICT Centre, Brisbane, QLD, AustraliaCSIRO Ecosystem Sciences, Cairns, QLD, AustraliaJunction 2013.04.29 Camazotz: Multimodal Activity-Based GPS Sampling

  2. Camazotz • The Maya’s Bat-God • Camazotz platform: • Multimodal Activity-based Localization (MAL) • - detect activities by combining multiple sensor streams • for fine-grained control of GPS sampling times. • Target: • Lightweight, long-distance, and long-term tracking

  3. Introduction • track flying foxes (fruit bats)狐蝠(澳大利亞特有種) • Spread Ebola, SARS-like Coronavirus(冠狀病毒) • collection data from highly mobile animals • Position information (GPS) • Activity information (inertial, acoustic, air pressure) • Challenge: • Sensing modalities: burden on limited node energy, processing and memory resources • Uncontrolled 3-D mobility: unpredictable effects on the transceivers, and solar panels Detect unknown congregation areas and roosting camps

  4. Application • to understand flying-fox ecology behavior • Nocturnally active • Roost in large aggregation (40-50,000 animals at a single site) • Highly mobile (travel 20km to their first feeding site in a night and over 100km during nightly, over weeks and months individuals can move hundreds or thousands of kilometers) • Threatened species (agricultural pests) • Virulent emerging infectious diseases • obtain day roost locations for comparison with surveyed comp locations, and know the group number

  5. Platform target • Collecting regular daytime fixes (with accuracy of 10m) at camps to identify new camps • Collecting high-frequency nighttime fixes to monitor movement patterns and landscape use, and doing this with an accuracy of 10m or less using inertial sensors during fine scale movements • Making daytime audio recordings to allow estimation of camp size • Operate over long periods (12 months, and preferably longer) • Provide data download capability

  6. Design Challenges • Size: 2cm x 2cm, 30~50g (<5%animal weight) • Might affect the size of GPS antenna ->accuracy • Mobility dynamics: continental scale • Cellular coverage may not be available • Cellular module also add significant weight, size and energy cost • Choose to transfer position data by installing BS at known roosting camps • Using short-range radio communication opportunistically • High degree of delay tolerance (memory, data compression, opportunistically deliver once connectivity return)

  7. Hardware Zigbee (915MHz band in Australia) • TI CC430F5137 (MSP430 core + CC1101 radio) • Support low power operation and offer high compatibility with popular sensor network operating systems.

  8. Hardware Dual side solar panels can harvest energy during night (up) and daytime (down) GPS antenna Amplifier directionality U-bloxMAX-6 GPS Smaller antenna’s omnidirectional radiation -> favorable for the 3-D mobility Add 20dB low noise amplifier (LNA) Less power consumption * Need 12x ground plane (=overall Camazotz)

  9. Energy charging architecture Fully charged and fully flat -> directly charged from solar panels (bypass circuit) • Fully flat: low current -> if from battery -> risk oscillation around a minimum voltage threshold -> data loss • Fully charged: can use any excess solar energy for increased sampling or computation

  10. Energy budget: low power sensors • Pressure sensor (Bosch BMP085): 12μA • 3-axes Accelerometer/magnetometer (STMicroelectronics LSM303): 830μA • Knowles microphone + 12bit ADC: <1mA Duty Cycle-> on average 12 μA overall

  11. Software • OS: Contiki • RPC (remote procedure calls) to send radio command • Perform certain actions (reading memory blocks, status information) • Adjust configuration parameters (GPS duty cyle) • Sent by unicast/broadcast packet [command id, arguments] • Logging abstraction due to long delay tolerant • Test phase: high sampling rate one SD care • Deployed phase: adjust sampling rate and log in external flash card

  12. Evaluation on Mobility • Bat-to-BS(3G) near roosting location, bats-to-bat communication outside • Under high mobility (7-8m/s) and surrounding trees to increase PRR • Experimental Platform (quad-copter with GPS and inertial sensor) • Duration: max. 30min, total 10 hrs, >20km • Broadcast pkts(32bytes), 8 pkts/sec • BS: 1.5m above the round, 20cm diameter ground plate • 3 kinds of antenna (large, small, and simple whip antenna) • Log RSSI and PRR for evaluation • UAV: send pkt 4Hz to tell GPS location and speed

  13. Evaluation on mobility Antenna Selection Smaller is worst Simple whip antenna outperforms • Almost no packet losses • With smaller variance of the RSSI • dependable

  14. Evaluation on mobility • Impact of Speed • No correlation between speeds and the RSSI • No need to constrain packet transmissions based on the speed

  15. Evaluation on mobility • Impact of Angle • Only a minor degradation of the signal quality at higher angles • Avoid installing the BS directly under the trees populated by flying foxes

  16. Evaluation on GPS TTFF is correlated with the time interval the GPS receiver was switched off • Static outdoor setup • Attach Camazotz board to a tree on campus (when flying fox roosting) • After 60 sec a position fix has been acquired, switch GPS antenna off - keep ephemeris information in RAM - GPS is able to do a warm start • off time interval: [10s, 60min] • measure TTFF (time to first fixt)

  17. Calculated (GPS): (M=7.2, SD=1.3) Measured (GG): (M=5.9, SD=3.0) GPS provide conservative estimates, more cluster Evaluation on GPS • Attached to flying fox in a large outdoor cage • Camazotz log 1 Hz GPS data to its SD card • Continuously send status update messages via radio to a BS • how to measure the true location - roosting location (averaging over 3600 fixes GPS) - use geo-referenced high resolution imagery (with a spatial accuracy of 1m)

  18. Evaluation on long-term operation Dips: caused by shadows from the structure of the bat enclosure • log solar charge current at 1 Hz Just below 5.7 Mw PER DAY Meet the energy neutral target • 5mA peak: small glimpse of sunlight were caught • Lower that static node • Non optimal orientation • Bat’s habit resting in a shade 3mA 12hr (5.7mW)

  19. Evaluation on activity recognition Wing beat frequency For height Use their claws to scratch their bodies Typical in upside down position, moving head/neck Fight for territory Mating advances By distinct sounds Increased movement Use Acc to detect motion upside down to right side up Important to detect: Where they spread seed Default status as baseline

  20. Inertial • Inversion events was detected by computing the angle θ between the current 3-D acceleration vector c and the inferred gravity vector g • identifying contiguous samples of at least 4 s where the angle was shifted by at least 90 degree • 100% accuracy with 3hr trace

  21. Audio • In-built microphone • 22.4 kHz (mainly within 2 ~ 4 kHz, 8 kHz) • Interaction events (mean sound level, call duration, mean normalized frequency) by classification • 1024 samples window (1/2 overlap), simple threshold Mean accuracy 77.5% Mean precision of 70.7% Select 0.002

  22. Air pressure Data average over 1 min time window Fluctuations in consecutive samples appear to be within 0 to 50 cm • GPS Error (horizontal: 10m, vertical: 20m) • instead rely on air pressure sensor • use the pressure sensor on the BS as reference altitude Cage 100m Feeding time

  23. Multimodal activity based localization • To detect interaction event • accelerometer + inertial + audio • with angular shift (inversion) duration shorter than urinate/defecation • with an initial jerk (bat is agitated) • average (54s) -> differentials (high) • each peak: vocalization lasting for 5s 43.8 and 60 degree (with highest differentials in average angular shifts) -> inertial jerks Third highest 18 degree -> 30 as threshold

  24. Multimodal activity based localization • When to trigger GPS sampling (simulation) • 1. accelerometer only • Detect events only from the collared bat • GPS active 21s, 86% power saving • 2. audio only • All 4 events (can’t distinguish events nearby) • GPS active 64s, 7.42mW power consumption • 3. combination

  25. Conclusion • Feature-rich lightweight Camazotz platform for long-term tracking of flying foxes • Comprehensive empirical evaluation in both laboratory and on-animal experiments.

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