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Sensor Network Applications for Environmental Monitoring

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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 ... – PowerPoint PPT presentation

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Title: Sensor Network Applications for Environmental Monitoring


1
Sensor Network Applications for Environmental
Monitoring
  • Carla Ellis
  • SAMSI 11-Sept-07

2
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

3
Great Duck Island Petrel MonitoringUCB
  • Goal build ecological models for breeding
    preferences of Leachs 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
4
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.
5
James Reserve Forest (CENS)
  • Heterogeneous
  • Robotics
  • Imaging
  • Full motion cameras
  • In nesting boxes
  • Time lapse images
  • Microclimate array soil moisture

6
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.

7
Aquatic Observing Systems (CENS)
8
Macroscope in RedwoodsSenSys 05
  • Tolle et al
  • UC Berkeley Intel Research Berkeley

9
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

10
Sensor Node Platform Package
  • Mica2Dot node from Crossbow
  • 4MHz processor
  • 433 MHz radio, 40 Kbps
  • 512 KB Flash
  • Sensors
  • Packaging

11
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

12
Temporal Distributions
13
Temporal Distributions
14
Spatial Distributions
15
Subtracting Timestamp Mean
16
Subtracting Timestamp Mean
17
One Day in the Life of a Tree
18
One Day in the Life of a Tree
19
Visualizing Change
20
Visualizing Change
21
Outliers Battery
  • Once battery voltage falls, temperature reading
    goes bad
  • Opportunity to automatically reject outliers

22
Performance of the NetworkData Transmitted
23
Performance of the NetworkData Transmitted
24
Logged Data
25
Both Logging Transmission
  • Both are good compensate for the others
    failures
  • Flash running out of space but transmissions
    continue
  • Transmissions stopped but Flash retains those
    data points

26
Wildlife Tracking ZebraNetAsplos 02
  • Juang et al
  • Princeton

27
Biological Goal
  • Long-term wide ranging zebra herd migration
    tracking
  • Associated with data on feeding behavior,
    heart-rate, body temp.

28
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

29
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

30
Mobility Model
31
Collar Design
GPS samples every 3 minutes Detailed activity
logs for 3 min every hr 1 year of
operation 3-5 lb weight limit
32
Energy and Weight Measurements
33
Drive-by Mobile Base Station
  • Vandalism is a problem for deploying an array of
    fixed antennas or base stations
  • Base station sporadically available

34
Peer to Peer System Design
35
Peer to Peer System Design
36
Peer to Peer System Design
37
Peer to Peer System Design
38
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

39
(No Transcript)
40
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

41
Simulation Results Ideal
42
Results with Constrained Storage(10 collar days)
43
Results with Constrained Bandwidth (12kps)
Short-range, flooding best Long-range, history
best
44
Energy (unconstrained case normalized to direct)
45
Final Design Choices
  • Storage viewed as effectively infinite
  • 2 radios
  • one short-range, do flooding
  • other long-range, direct

46
Summary of Challenges
47
  • Energy in battery powered nodes.
  • Constrain lifetime of nodes, if not recharged
  • Energy harvesting, weight of solar collectors
  • Duty cycling necessary -gt clock synchronization
  • Data delivery
  • Missing data
  • Connectivity
  • Routing issues
  • Unsynchronized duty cycles
  • Collisions
  • Dead nodes
  • Outliers
  • Calibration of sensors

48
  • 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)

49
Breakouts
  • Form 3 or 4 ad hoc multi-disciplinary groups
    (outside comfort zone mix ECEstatCSbio)
  • 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)
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