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

• Substantial cost in human lives, property damage, firefighting expenses, etc.– 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

Forest Fires - Costs

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,

on-demand/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 temperature differences, not horizontal, which would require 100’s of sensor nodes

CU’s Carl Hartung deploys WSNsin the fire area via helicopter

FireWxNet’s Hierarchical Architecture

SoekrisBase

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

Deployment

Awake: Sense and Send

Sleep

ON

Hears Beacon

After ~1 Minute

After 14 Minutes

6% Duty Cycle – maintained by the beacons

Ease of Deployment

LOCATE: A

New Node

A

FOUND: A

• Used to set up symmetric links where possible• Crude but effective, but could be improved

Sensor Network – Routing

Base

A (1)

B (1)

C (2)

D (3)

• 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

• 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

• Hell’s Half Acre Yield• 47% Overall

• 74% Effective

• Kit Carson Yield at Base station

• 36% Overall

• 80% 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 CarsonNode Hop Variability

0

1

2

3

4

5

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

DTB

44

43

42

41

40

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.

LongevityOur Deployment only ran for 1 week, then the snows came...