Transcript Document

ACM MobiSys 2009
Kraków, Poland, June 22-25 2009
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
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Outline
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Introduction
System design
Campus outdoor test
Field deployment
Conclusion
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Background: Volcano Hazards
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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
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Volcanic Earthquakes
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Directed Blast
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Tephra
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Volcanic Gases
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Lava Flows
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Debris Avalanches, Landslides, and
Tsunamis
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Pyroclastic Surge
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Pyroclastic Flows
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Lahars
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Volcano Crater: a harsh environment
Sugar Bowl
at Mount
Mount St.
St. Helens,
Helens, 1980s
2005
Winter
EDMcamera
survey at
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Volcano Crater: a harsh environment
Two days later, it looked like this.
Camera and gas sampler spider shown prepositioned 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:
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an active volcano
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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 retasking 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
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Challenging environment
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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
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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
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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
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Design goal
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Synchronize with UTC time
Synchronized sampling – different nodes sample
channels at same time point, 1ms resolution
Hybrid Time Synchronization
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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
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Configurable Parameters
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Change sampling rate
Add/Delete sensor
Change data priority
Change node priority
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Configurable Sensing
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Configurable Data Processing Tasks
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Situation Awareness
Detect seismic events and give higher priority to
event data.
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RSAM (Real-Time Seismic-Amplitude
Measurement)
LTA and STA calculation
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RSAM period: 1 sec
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STA window: 8 sec
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LTA window: 30 sec
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Trigger ratio: 2
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Situation Awareness
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STA/LTA event detection
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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
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Prioritization
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Assigning priorities based on data and event type
Assigning retransmission opportunities based on
priorities
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Agile Data Collection Routing
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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.
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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
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Cascades: reliable fast data dissemination
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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
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Module designers decide which interface or
command to be allowed to call remotely, by simply
adding @rpc();
interface SensingConfig @rpc();
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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>
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Originated from Marionette, IPSN 2006
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System Robustness
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Watchdog mechanism to restart nodes
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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:
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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
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Hardware verification shall start as early
as possible, do not wait until last minute
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We had a headache to extend tx range in
last one month
Quantitative measurement is essential,
do not rely on other’s experiences
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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
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Open for any possibility – need critical
thinking skills.
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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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15 disappearsininfirst
18 hours, because ……
NodeNode
15 disappear
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
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Several types of USGS stations in place:
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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
Mount St. Helens
3 km depth
November 4, 2008
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Conclusion
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Meets the system requirement, with the goal
to replace data loggers for volcano monitoring.
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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
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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!
WenZhan Song
Email: [email protected]
Deployment video
http://www.youtube.com/watch?v=IbCpioUlF0I
More information, visit
http://sensorweb.vancouver.wsu.edu
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Hardware Design
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Controller: Intel Mote2
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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
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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
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