sensor network applications for environmental monitoring carla ellis samsi 11-sept-07

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Sensor Network Applications for Environmental Monitoring Carla Ellis SAMSI 11-Sept-07

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Sensor Network Applications for Environmental Monitoring

Carla Ellis

SAMSI 11-Sept-07

Survey of Deployments

• Two in detail: Redwoods and ZebraNet• Others

– Great Duck Island– TurtleNet– James Reserve Forest– Volcanos & earthquakes– Aquatic observing systems– Localization, real-time tracking

Great Duck Island: Petrel MonitoringUCB

• Goal: build ecological models for breeding preferences of Leach’s Storm Petrel

– Burrow (nest) occupancy during incubation

– Differences in the micro-climates of active vs. inactive burrows

– Environmental conditions during 7 month breeding season

• Inconspicuous Operation– Reduce the “observer effect”

• Unattended, off-the-grid operation

• Sensor network– 26 burrow motes deployed

– 12 weather station motes deployed (+2 for monitoring the insides of the base station case)

Burrow Occupancy Detector

TurtleNet (Corner, Umass)

"Wetness" is a measure of current in the water sensor. This graph shows that the turtle came out of the water to sun itself for only brief periods and went back into the colder water.

Mica2Dot hardware, GPS,Solar cells on the backs ofsnapping turtles.

James Reserve Forest (CENS)

• Heterogeneous• Robotics• Imaging

– Full motion cameras

– In nesting boxes

– Time lapse images

• Microclimate array& soil moisture

Volcano Monitoring (Welsh, Harvard)

• Motes with seismic sensors deployed on active volcano in Ecuador• Science dictates: high fidelity during events, large spatial

separation, time synchronization.• Nature of the application allows triggered data collection rather than

continuous.

Aquatic Observing Systems (CENS)

Macroscope in RedwoodsSenSys 05

Tolle et alUC Berkeley

Intel Research Berkeley

Deployment Up a Tree

• Dense temporal and spatial data collection

• 44 days from Apr 27 to Jun 10

• 33 sensor nodes• Sampling every 5

minutes• Temperature, relative

humidity, PAR

Sensor Node Platform & Package

• Mica2Dot node from Crossbow– 4MHz processor

– 433 MHz radio, 40 Kbps

– 512 KB Flash

– Sensors

• Packaging

TASK Software

• Duty cycling – node on 4 sec every 5 min

• Time synchronization

• Tree route discovery between gateway and nodes

• TinyDB data collection and querying

• Data logging in Flash as backup

Temporal Distributions

Temporal Distributions

Spatial Distributions

Subtracting Timestamp Mean

Subtracting Timestamp Mean

One Day in the Life of a Tree

One Day in the Life of a Tree

Visualizing Change

Visualizing Change

Outliers & Battery

• Once battery voltage falls, temperature reading goes bad

• Opportunity to automatically reject outliers

Performance of the Network:Data Transmitted

Performance of the Network:Data Transmitted

Logged Data

Both Logging & Transmission

• Both are good – compensate for the other’s failures– Flash running out of

space but transmissions continue

– Transmissions stopped but Flash retains those data points

Wildlife Tracking – ZebraNetAsplos 02

Juang et al

Princeton

Biological Goal

• Long-term & wide ranging zebra herd migration tracking

• Associated with data on feeding behavior, heart-rate, body temp.

Why a Wireless Sensor Network Approach?

• Traditional radio collars – coarse grain information

• Sensor nodes (GPS), not networked – usually must retrieve collar to download stored data

• Satellite tracking – high energy costs, low bitrate

A Day in the Life of a Zebra

• Social structure can be exploited– Plains zebra form tight-knit harems (1 male,

multiple females). Collar 1 individual and track the group

– Sometimes form loose herds of multiple harems, often at watering holes

• Drink water on a daily basis

• Mostly moving 24 hours a day

Mobility Model

Collar Design

GPS samples every 3 minutesDetailed activity logs for 3 min every hr1 year of operation3-5 lb weight limit

Energy and Weight Measurements

Drive-by Mobile Base Station

• Vandalism is a problem for deploying an array of fixed antennas or base stations

• Base station sporadically available

Peer to Peer System Design

zebraA1010111101100011000110000

zebraB10010111111000110000

Peer to Peer System Design

zebraA1010111101100011000110000

zebraB10010111111000110000

zebraA1010111101100011000110000

zebraB10010111111000110000

Peer to Peer System Design

zebraB10010111111000110000

zebraA1010111101100011000110000

zebraB10010111111000110000

zebraA1010111101100011000110000

Peer to Peer System Design

zebraB10010111111000110000

zebraA1010111101100011000110000

Implications of Collar Design

• GPS provides precise synchronized clock – For avoiding short-range network collisions

• Assume 5 days battery life between recharging– Need 13.5AH to sample (6KB/day), search for peers

(6hr/day), search for base station (3 hr/day), and transmitting 640KB of data.

• 640KB Flash = 300 days of data compressed, 110 days uncompressed– Need to accommodate redundancy of data stored from

other nodes

Homing Success Rate

• Fraction of data successfully delivered to base station (goal to eventually get 100% data reported)

• Simulation study (single radio):– Flooding protocol – share data with everyone

encountered

– History protocol – send to “best” peer discovered based on their previous success in delivering to base

– Direct protocol – not peer-to-peer, just to base

Simulation Results: Ideal

Results with Constrained Storage(10 collar days)

Results with Constrained Bandwidth (12kps)

Short-range, flooding bestLong-range, history best

Energy (unconstrained case; normalized to direct)

Final Design Choices

• Storage viewed as effectively infinite

• 2 radios: – one short-range, do flooding– other long-range, direct

Summary of Challenges

• Energy in battery powered nodes. – Constrain lifetime of nodes, if not recharged

– Energy harvesting, weight of solar collectors

– Duty cycling necessary -> clock synchronization

• Data delivery– Missing data

• Connectivity – Routing issues

– Unsynchronized duty cycles

– Collisions

• Dead nodes

– Outliers• Calibration of sensors

• Hierarchy, heterogeneity, mobility– Robotics, actuation

• Packaging– Weather effects = dead nodes– Weatherproofing – gets in the way of sensors

• How to deal with massive amounts of data

• Infrastructure– System behavior monitoring – Interactive remote control (retasking)

Breakouts

• Form 3 or 4 ad hoc multi-disciplinary groups (outside comfort zone: mix ECE+stat+CS+bio)

• Discuss one of two topics– Research question you might address with Duke Forest data

– Research study you might design from scratch, its requirements and challenges.

• Report back at end of class (elect a spokesperson)