FireWxNet: A Deployment of
Wireless Sensor Networks In the
Forest Fires of the Western U.S.*
Speaker: Professor Rick Han
MANTIS Research Group
Department of Computer Science
University of Colorado at Boulder
*Best Paper Award at ACM MobiSys 2006, with coauthors
Carl Hartung, Saxon Holbrook, and Carl Seielstad
Forest Fires - Costs
• Substantial cost in human lives, property damage,
firefighting expenses, etc.
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–
–
–
–
Deaths and displacement resulting from wildland fires
Billions in property damage (Oakland Hills 1991 cost $2.4 billion)
In 2005 in the U.S., 66,000 fires burned 8.7 million acres
$1 billion spent to fight fires by U.S. government
18,000 fire fighters available for 2006
• WSN technology can help save lives, reduce all of these costs
– By providing finer granularity scientific data - weather
Bitterroot National Forest, Montana, 2000
Weather and Forest Fires
• Temperature
– As Temperature goes up: fuels dry out,
fuels temp rises, etc..
• Relative Humidity
– 10 minute fuels (small twigs) change
with RH quickly.
– 10,000 hour fuels (large trees) not
very affected.
• Wind Speed and Direction
– Feeds fire with extra oxygen. Dictates
direction. Can change quickly.
• Example: Temperature Inversions
and Thermal Belts
– Temperature is colder at lower
elevations.
– Fires above the inversion continue to
burn actively.
– Band of warmer air trapped midway
up the mountain.
– When they break – increased winds,
rapid increase in temp.
Temperature Inversion
Temperature Inversion
Forest Fires – Current Ways to
Measure Weather
Belt Weather Kit
Disadvantages: poor coverage, often forgotten, slow,
etc.
Current Ways to Measure Weather
Remote Automated
Weather Station (RAWS)
Disadvantages: poor
coverage, expensive, etc.
FireWxNet Design Goals
• Deploy a WSN to monitor weather
data around prescribed forest fires
– Temp, RH, wind
– Actually deployed around unplanned
lightning-strike wildfires
– In collaboration with the University
of Montana
• Must be rugged, ondemand/portable, inexpensive,
long-lived, easy to deploy, etc.
– Did not focus on survivability of
nodes, but system is robust to node
failures
• Deployment difficulties => sparse
WSN
– Focus on improved coverage of the
thermal inversion belt – well-known
but difficult to detect
– capturing vertical elevational
CU’s Carl Hartung deploys WSNs
temperature differences, not
horizontal, which would require 100’s
in the fire area via helicopter
of sensor nodes
FireWxNet’s Hierarchical Architecture
Soekris
Base
Station
FireWxNet’s Wireless Sensor Network
• MICA2, 900 MHz, 2 AA batteries
• Mantis OS (MOS)
• Commercial sensors
– e.g. Relative Humidity: Humirel 1520,
extremely accurate below 30% RH
Networking Design:
Deployment, Duty Cycling, and Routing
ON
Deployment
Hears
Beacon
After 14 Minutes
Sleep
After ~1 Minute
Awake:
Sense and
Send
6% Duty Cycle – maintained by the beacons
Ease of Deployment
LOCATE: A
FOUND: A
New Node
A
• Used to set up symmetric links where possible
• Crude but effective, but could be improved
Sensor Network – Routing
• During 1 min Awake period,
– Beacons flooded every 4 seconds from Base
– Establishes tree-structured routing
– Data was sent 1 packet per second for 60 seconds
A (1)
Base
C (2)
B (1)
D (3)
• Fault tolerance: multipath above, plus
– If no beacon heard within 10 seconds (2 ½ beacon cycles)
with DTB <= MyDTB -1, reset DTB and look for new beacon
with any DTB.
– Adapts to failed, moved, shut off nodes
FireWxNet Deployment:
Bitterroot National Forest, Idaho
A) Base Camp
B) Ranger Station
C) Boulder Peak Relay
D) Hell’s Half Acre (SN)
E) Kit Carson (SN)
F) Spot Mountain
• WSNs deployed within 1 km of fire
• One-week deployment, then it snowed
Network Topology and Performance
Kit Carson
Hell’s Half Acre
• Kit Carson Yield at
Base station
• Hell’s Half Acre Yield
• 36% Overall
• 80% Effective
• 47% Overall
• 74% Effective
Base Station Packet Reception Rates
Hell’s Half
Kit Carson
• Extreme packet loss, and nodes further away suffer more loss, e.g. 43 & 44
• Variation across days is consistent
• Node 22 was deliberately set up with shaky connectivity
Base Station Packet Reception Rates
Hell’s Half
Kit Carson
Network Variability – Kit Carson
Node Hop Variability
5
44
4
43
DTB
3
42
2
41
1
40
0
9/6/05 6:00 PM 9/7/05 12:00 AM 9/7/05 6:00 AM 9/7/05 12:00 PM 9/7/05 6:00 PM 9/8/05 12:00 AM 9/8/05 6:00 AM
Time
Large variation even after placement using the LED deployment technique
Sensed Data
Inversion Close up
Inversion
Start
Inversion
End
• This data was used in the morning briefing by the Incident
Commander – we hadn’t fully tested our system yet!
Summary and Lessons Learned
• FireWxNet: Designed, built and deployed a hierarchical WSN to
monitor weather on wildland fires
– Characterized thermal belt - useful to fire fighters
– Somewhat achieved our design goals: robust, on-demand/portable,
inexpensive, long-lived, easy to use, etc.
• Learn what are the real problems
– Extensive RF variability, even after placement => Design for robustness in
networking
– Ease of use in the field:
• Add simple tools (LED blinking) for status/debugging
• Keep the design basic
• Add complexity only when needed, e.g. FireWxNet II this summer (solar,
commands, adaptive FEC, calibration, etc.)
– Software bugs: test & refine iteratively in lab, small deployment outside, etc.
• Partner with the right people! (NCLFA at UMontana)
– Gain acceptance by overcoming cultural issues, obtain red flag training, etc.
Contact: rhan@cs.colorado.edu or
Carl.Hartung@colorado.edu
C. Hartung, S. Holbrook, R. Han, C. Seielstad,
“FireWxNet: A Multi-Tiered Portable Wireless
System for Monitoring Weather Conditions in
Wildland Fire Environments”, Fourth
International Conference on Mobile Systems,
Applications and Services (MobiSys) 2006, pp.
28-41.
Longevity
Our Deployment only ran for 1 week, then the snows came...