Airdropped Sensor Network for Realtime Highfidelity Volcano Monitoring

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Air-dropped Sensor Network for Real-time
High-fidelityVolcano Monitoring
ACM MobiSys 2009 Kraków, Poland, June
22-25 2009
Wen-Zhan Song, Renjie Huang, Mingsen Xu, Andy
Ma, Behrooz Shirazi Washington State
University Richard LaHusen U.S. Geological Survey
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Outline

• Introduction
• System design
• Campus outdoor test
• Field deployment
• Conclusion

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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

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Volcano Crater a harsh environment
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Volcano Crater a harsh environment
Camera and gas sampler spider shown
pre-positioned at Sugar Bowl on 14 January 2005.
Shortly after this picture was taken, spider was
deployed within 100 m of extrusion site.
So we need smarter sensors and networks to ensure
continuous, spatially dense monitoring in
hazardous areas
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Mount St. Helens an active volcano
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Background OASIS projectOptimized 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.

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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 100-200Hz, 16 bit/sample
• Infrasonic sensor 100-200Hz, 16 bit/sample
• Lightning sensor 1Hz, 16 bit/sample
• GPS raw data 200-300 bytes/10 seconds

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System Requirements

• Synchronized Sampling
• Real-time Continuous Raw Data
• One-year Robust Operation
• Online Configurable
• Fast Deployment

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Hardware Design
iMote2
UBlox GPS
MDA320

• Seismic
• Infrasonic
• Lightning

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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

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Configurable Sensing

• Configurable Parameters
• Change sampling rate
• Add/Delete sensor
• Change data priority
• Change node priority

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Configurable Sensing

• Configurable Data Processing Tasks

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Situation Awareness
Detect seismic events and give higher priority to
event data.

• 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

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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

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Situation Awareness

• Prioritization
• Assigning priorities based on data and event type
• Assigning retransmission opportunities based on
  priorities

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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.

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Reliable Data Dissemination

• Cascades reliable fast data dissemination

• Opportunistic broadcast flow
• Parent-children monitoring
• Explicit and implicit ACK
• Retry and request

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Network Control

• Light-weight Remote Procedure Call Mechanism
• Module designers decide which interface or
  command to be allowed to call remotely, by simply
  adding _at_rpc()
• interface SensingConfig _at_rpc()
• It will be translated to XML and used by client
  for remote control
• ltSmartSensingM.SensingConfig.setSamplingRate
  commandID"23" componentName"SmartSensingM"
  functionName"setSamplingRate" functionType"comma
  nd" interfaceName"SensingConfig"
  interfaceType"SensingConfig" numParams"2"
  provided"1" signature" command result_t
  SmartSensingM.SensingConfig.setSamplingRate (
  uint8_t type, uint16_t samplingRate ) "gt
• ltparamsgt
• ltparam0 name"type"gt
• lttype typeClass"unknown"
  typeDecl"uint8_t" typeName"uint8_t" /gt
• lt/param0gt
• ltparam1 name"samplingRate"gt
• lttype typeClass"unknown"
  typeDecl"uint16_t" typeName"uint16_t" /gt
• lt/param1gt
• lt/paramsgt
• ltreturnType typeClass"unknown"
  typeDecl"result_t" typeName"result_t" /gt
• lt/SmartSensingM.SensingConfig.setSamplingRategt

Originated from Marionette, IPSN 2006
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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

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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 others experiences
• After we added RF amplified, RSSI was strong, but
  LQI and link reliability was weak
• It taught us that RSSI reflects signalnoise,
  while LQI reflects signal/noise ratio.

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Test Lessons

• Open for any possibility need critical thinking
  skills.
• During test, a nodes signal quality decreased
  during 1PM-6PM sunny days (when temperature is
  high), we changed everything except cable
• After we changed the high-quality cables
  (LMR_at_-400-ULTRAFLEX COAXIAL CABLE TIMES MICROWAVE
  SYSTEMS) to some lower-quality cables (BELDEN
  8262M17/155-00001 MIL-C-17 16428 2137 1922
  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!

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System Deployment
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SEP
NED
VALT
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10/15/08
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System statistics
gray color Hour-averaged loss ratio black
color Parent nodes LQI
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System statistics
The uptime of nodes and data server
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Node 15 disappears in 18 hours, because
Node 15 disappear in first week because
Node 15
10/22/08
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Wind speed peaks at 120 miles/hour
Infrasonic sensor records the unusual gust
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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

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Cost and function comparison
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Data quality comparison
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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 2009
• 15 stations into crater and around flanks
• Integrate TreeMAC (Song etc, PerCom09), ALFC
  compression (Kiely etc, PerCom09), Over-the-air
  programming

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Thank You!WenZhan SongEmail songwz_at_wsu.edu
Deployment video http//www.youtube.com/watch?vIb
CpioUlF0I More information, visit http//sensorw
eb.vancouver.wsu.edu
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Hardware Design

• Controller Intel Mote2
• CPU PXA271 13-416MHz with Dynamic Voltage
  Scaling. 13MHz operates at a low voltage (0.85V)
• Storage 256kB SRAM, 32MB SDRAM, 32MB Flash
• 802.15.4 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 130 MPH
• Battery a bundle of Cegasa air-alkaline
  industrial batteries