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Washington State UniversitySensorweb Research Laboratory Air-dropped Sensor Network for Real-time High-fidelity Volcano Monitoring Wen-Zhan Song, Renjie.

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Presentation on theme: "Washington State UniversitySensorweb Research Laboratory Air-dropped Sensor Network for Real-time High-fidelity Volcano Monitoring Wen-Zhan Song, Renjie."— Presentation transcript:

1 Washington State UniversitySensorweb Research Laboratory Air-dropped Sensor Network for Real-time High-fidelity Volcano Monitoring Wen-Zhan Song, Renjie Huang, Mingsen Xu, Andy Ma, Behrooz Shirazi Washington State University Richard LaHusen U.S. Geological Survey ACM MobiSys 2009 Kraków, Poland, June

2 Washington State UniversitySensorweb Research Laboratory Outline Introduction System design Campus outdoor test Field deployment Conclusion

3 -3- Washington State UniversitySensorweb Research Laboratory Background: Volcano Hazards Volcanoes are everywhere - on Earth and beyond Magmatism is of fundamental importance to planetary evolution and essential to life as we know it On Earth, volcanic risk is increasing rapidly as human population increases Volcanic Earthquakes Directed Blast Tephra Volcanic Gases Lava Flows Debris Avalanches, Landslides, and Tsunamis Pyroclastic Surge Pyroclastic Flows Lahars

4 -4- Washington State UniversitySensorweb Research Laboratory Sugar Bowl camera at Mount St. Helens, 2005 Volcano Crater: a harsh environment Winter EDM survey at Mount St. Helens, 1980s

5 -5- Washington State UniversitySensorweb Research Laboratory Camera and gas sampler spider shown pre- positioned at Sugar Bowl on 14 January Shortly after this picture was taken, spider was deployed within 100 m of extrusion site. Volcano Crater: a harsh environment Two days later, it looked like this. So we need smarter sensors and networks to ensure continuous, spatially dense monitoring in hazardous areas

6 -6- Washington State UniversitySensorweb Research Laboratory Mount St. Helens: an active volcano

7 -7- Washington State UniversitySensorweb Research Laboratory Background: OASIS project Optimized Autonomous Space In-situ Sensorweb OASIS has two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. 1. In-situ sensor-web autonomously determines network topology, bandwidth and power allocation. 2. Activity level rises causing self-organization of in-situ network topology and a request for re- tasking of space assets. 3. High-resolution remote-sensing data is acquired and fed back to the control center. 4. In-situ sensor-web ingests remote sensing data and re-organizes accordingly. Data are publicly available at all stages.

8 -8- Washington State UniversitySensorweb Research Laboratory Application Characteristics Challenging environment Extreme weathers: temperature (baking/freezing), wind, snow, rain, Dynamic environment: rock avalanche, land sliding, gas/steam emissions, volcanic eruptions, earthquake Battery is the only reliable energy source. Solar panel is possible in summer, but frequently covered by ashes Stations are frequently destroyed, some hot spot can only be accessed through air drop Low signal noise ratio of both communication and sampling High data rate, and require network synchronized sampling Seismic sensor: Hz, 16 bit/sample Infrasonic sensor: Hz, 16 bit/sample Lightning sensor: 1Hz, 16 bit/sample GPS raw data: bytes/10 seconds

9 -9- Washington State UniversitySensorweb Research Laboratory System Requirements Synchronized Sampling Real-time Continuous Raw Data One-year Robust Operation Online Configurable Fast Deployment

10 -10- Washington State UniversitySensorweb Research Laboratory Hardware Design Seismic Infrasonic Lightning iMote2 MDA320 UBlox GPS

11 -11- Washington State UniversitySensorweb Research Laboratory Synchronized Sampling Design goal Synchronize with UTC time Synchronized sampling – different nodes sample channels at same time point, 1ms resolution Hybrid Time Synchronization Stay synchronized with GPS if GPS is good Switch to modified FTSP (Flooding Time Synchronization Protocol, Maróti, Sensys 2004) when GPS is disconnected

12 -12- Washington State UniversitySensorweb Research Laboratory Configurable Sensing Configurable Parameters Change sampling rate Add/Delete sensor Change data priority Change node priority

13 -13- Washington State UniversitySensorweb Research Laboratory Configurable Sensing Configurable Data Processing Tasks

14 -14- Washington State UniversitySensorweb Research Laboratory Situation Awareness RSAM (Real-Time Seismic-Amplitude Measurement) RSAM period: 1 sec STA window: 8 sec LTA window: 30 sec Trigger ratio: 2 LTA and STA calculation Detect seismic events and give higher priority to event data.

15 -15- Washington State UniversitySensorweb Research Laboratory Situation Awareness STA/LTA event detection Monitor the ratio of Short-Term Average (STA) and Long-Term Average (LTA) Event is triggered when ratio is over threshold

16 -16- Washington State UniversitySensorweb Research Laboratory Situation Awareness Prioritization Assigning priorities based on data and event type Assigning retransmission opportunities based on priorities

17 -17- Washington State UniversitySensorweb Research Laboratory Agile Data Collection Routing Invalid route when a node detects a loop, or it does not receive route beacon from its parent for more than 6 beacon periods, or all packet transmissions in last 15 seconds fail. Asymmetric links will be avoided. Maintain alternative parent (if available) in neighbor table, which will be used if its current parent lost, instead of rediscovering a new parent. Accelerate good news and bad news propagation.

18 -18- Washington State UniversitySensorweb Research Laboratory Reliable Data Dissemination Opportunistic broadcast flow Parent-children monitoring Explicit and implicit ACK Retry and request Cascades: reliable fast data dissemination

19 -19- Washington State UniversitySensorweb Research Laboratory Light-weight Remote Procedure Call Mechanism Module designers decide which interface or command to be allowed to call remotely, by simply interface It will be translated to XML and used by client for remote control Network Control Originated from Marionette, IPSN 2006

20 -20- Washington State UniversitySensorweb Research Laboratory System Robustness Watchdog mechanism to restart nodes If any illegal operations, such as divide by 0 If radio did not send or receive for 5 minutes (when the network data rate is high). If some memory buffer is full and never get cleared for 5 minutes. Sanity check is necessary. We found some unexpected things in tinyos: Radio corrupts pending tinyos message header and cause the pointer not to return to correct up layer Event sendDone signaled twice to up layer Message passed CRC check, but has shorter or longer length than its length field

21 -21- Washington State UniversitySensorweb Research Laboratory Test Lessons Hardware verification shall start as early as possible, do not wait until last minute We had a headache to extend tx range in last one month Quantitative measurement is essential, do not rely on other’s experiences After we added RF amplified, RSSI was strong, but LQI and link reliability was weak It taught us that: RSSI reflects signal+noise, while LQI reflects signal/noise ratio.

22 -22- Washington State UniversitySensorweb Research Laboratory Test Lessons Open for any possibility – need critical thinking skills. During test, a node’s signal quality decreased during 1PM-6PM sunny days (when temperature is high), we changed everything except cable After we changed the high-quality cables 400-ULTRAFLEX COAXIAL CABLE TIMES MICROWAVE SYSTEMS) to some lower-quality cables (BELDEN 8262M17/ MIL-C :22 ROHS), the problem is gone. This problem does not happen in other nodes, even with same cable. Still do not know exact reasons – it might be related to RF impedence!

23 -23- Washington State UniversitySensorweb Research Laboratory System Deployment

24 -24- Washington State UniversitySensorweb Research Laboratory

25 -25- Washington State UniversitySensorweb Research Laboratory Node 16 10/15/08

26 -26- Washington State UniversitySensorweb Research Laboratory System statistics gray color: Hour-averaged loss ratio black color: Parent node’s LQI

27 -27- Washington State UniversitySensorweb Research Laboratory System statistics The uptime of nodes and data server

28 -28- Washington State UniversitySensorweb Research Laboratory Node 15 disappears in 18 hours, because …… Node 15 10/22/08 Node 15 disappear in first week because …

29 -29- Washington State UniversitySensorweb Research Laboratory Wind speed peaks at 120 miles/hour Infrasonic sensor records the unusual gust …

30 -30- Washington State UniversitySensorweb Research Laboratory Comparison with existing USGS stations Several types of USGS stations in place: Dual frequency GPS with digital store and forward telemetry when polled – not continuous! Short period seismic stations with geophones and analog telemetry – not digital Broad band seismic stations with digital telemetry – cost above $10K and several days to deploy Microphones for explosion detection added to the short period seismic stations

31 -31- Washington State UniversitySensorweb Research Laboratory Cost and function comparison

32 -32- Washington State UniversitySensorweb Research Laboratory Data quality comparison Magnitude 1 Earthquake Mount St. Helens 3 km depth November 4, 2008

33 -33- Washington State UniversitySensorweb Research Laboratory Conclusion Meets the system requirement, with the goal to replace data loggers for volcano monitoring. Synchronized Sampling Real-time Continuous Raw Data One-year Robust Operation Online Configurable Fast Deployment Clears the doubts of domain scientists and proves that the low-cost sensor network system can work in extremely harsh environments. Next deployment on Summer/Fall stations into crater and around flanks Integrate TreeMAC (Song etc, PerCom’09), ALFC compression (Kiely etc, PerCom’09), Over-the-air programming

34 -34- Washington State UniversitySensorweb Research Laboratory Thank You! Thank You! WenZhan Song Deployment video More information, visit

35 -35- Washington State UniversitySensorweb Research Laboratory Hardware Design Controller: Intel Mote2 CPU: PXA MHz with Dynamic Voltage Scaling. 13MHz operates at a low voltage (0.85V) Storage: 256kB SRAM, 32MB SDRAM, 32MB Flash radio: CC2420 Other Hardware Components Seismic: low noise MEMS accelerometer (Silicon Designs Model 1221J-002) Infrasonic: low range differential pressure sensor (All Sensors's Millivolt Output Pressure Sensors Model 1 INCH-D-MV) Lightning (for ash detection): custom USGS/CVO RF pulse detector GPS (for deformation measurement): L1 GPS (Ublox model LEA-4T) Customized SmartAmp 2.4GHz, 250mW, amplify -3dBm input to 20dBm output. Antenna: 12 dB omni, withstand extreme wind speeds in excess of MPH Battery: a bundle of Cegasa air-alkaline industrial batteries


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