washington state universitysensorweb research laboratory air-dropped sensor network for real-time...
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Washington State University
Sensorweb Research Laboratory
Air-dropped Sensor Network for Real-time
High-fidelityVolcano Monitoring
Wen-Zhan Song, Renjie Huang, Mingsen Xu, Andy Ma, Behrooz Shirazi
Washington State University
Richard LaHusenU.S. Geological Survey
ACM MobiSys 2009
Kraków, Poland, June 22-25 2009
Washington State University
Sensorweb Research Laboratory
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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Sugar Bowl camera at Mount St. Helens, 2005
Volcano Crater: a harsh environment
Winter EDM survey at Mount St. Helens, 1980s
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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.
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
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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
•Seismic
•Infrasonic
•Lightning
iMote2
MDA320
UBlox GPS
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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
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.
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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
Opportunistic broadcast flow
Parent-children monitoring
Explicit and implicit ACK
Retry and request
Cascades: reliable fast data dissemination
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Light-weight Remote Procedure Call Mechanism
Module designers decide which interface or command to be allowed to call remotely, by simply adding @rpc();
interface SensingConfig @rpc(); It will be translated to XML and used by client
for remote control
<SmartSensingM.SensingConfig.setSamplingRate commandID="23" componentName="SmartSensingM" functionName="setSamplingRate" functionType="command" interfaceName="SensingConfig" interfaceType="SensingConfig" numParams="2" provided="1" signature=" command result_t SmartSensingM.SensingConfig.setSamplingRate ( uint8_t type, uint16_t samplingRate ) ">
<params> <param0 name="type"> <type typeClass="unknown" typeDecl="uint8_t" typeName="uint8_t" /> </param0> <param1 name="samplingRate"> <type typeClass="unknown" typeDecl="uint16_t" typeName="uint16_t" /> </param1> </params> <returnType typeClass="unknown" typeDecl="result_t" typeName="result_t" />
</SmartSensingM.SensingConfig.setSamplingRate>
Network Control
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 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.
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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 (LMR@-400-ULTRAFLEX COAXIAL CABLE TIMES MICROWAVE SYSTEMS) to some lower-quality cables (BELDEN 8262M17/155-00001 MIL-C-17 16428 2137 19:22 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!
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System Deployment
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Node 16
10/15/08
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System statistics
gray color:
Hour-averaged loss ratio
black color:
Parent node’s 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 disappears in 18 hours, because …………
Node 15
10/22/08
Node 15 disappear in first week because …
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Wind speed peaks at 120 Wind speed peaks at 120 miles/hourmiles/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
Magnitude 1 Earthquake Magnitude 1 Earthquake Mount St. Helens
3 km depth November 4, 2008
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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, PerCom’09), ALFC
compression (Kiely etc, PerCom’09), Over-the-air programming
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Thank You!Thank You!
WenZhan SongEmail: [email protected]
Deployment video http://www.youtube.com/watch?v=IbCpioUlF0I
More information, visithttp://sensorweb.vancouver.wsu.edu
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Hardware DesignHardware 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