Experiences and Challenges in Campaign Style Deployments using Wireless Sensor Networks
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Transcript of Experiences and Challenges in Campaign Style Deployments using Wireless Sensor Networks
Experiences and Challengesin Campaign Style Deploymentsusing Wireless Sensor Networks
Jayant Gupchup†, Scott Pitz*, Douglas Carlson† , Chih-Han Chang*, Michael Bernard*,
Andreas Terzis†, Alex Szalay±, Katalin Szlavecz*
Department of Computer Science, Johns Hopkins University†
Department of Physics and Astronomy, Johns Hopkins University±
Department of Earth and Planetary Sciences, Johns Hopkins University*
Campaign Style Deployment
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Quito
Requirements / Constraints
• No access to line power or internet
• Collect data at a high rate (e.g. 30s)– Deployment order of days to weeks
• Researchers require access to data in field
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A Typical Sensor Network
Gateway/Basestation
Stable Storage
…….7 Ah
Differences / Challenges
• On-site decisions
• Ad hoc hardware reconfigurations
• Dealing with high data rates in the field (using a netbook)
• Use of high power sensors– Vaisala CO2 sensors– Driven by a car battery
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Power ~ 4W
Deployment Details - I
• Location : Quito, Ecuador
• Goal :
Understand tropical soil respiration
• Duration : 16 days604/21/23 Jayant Gupchup
Deployment Details -II
• 30s Sampling Interval
• Data retrieved over the air using a netbook
• 20 Sampling locations– 12 Soil CO2
– 8 Soil Temperature & Moisture
• Each CO2 Location– 3 depths (12 locations, 3 depths = 36 sensors)
– Vaisala GMT 220 Series– CO2 Powered by 12 V / 45 Ah Car Battery
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A CO2 Set-Up
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3 m
3 m
3 m
Under The Hood
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Antenna
TelosB Mote
CO2 Sensors
Mote Battery
CO2 SensorPower Connector
Power Consumption
• Lead acid car batteries 12V / 45Ah
• Each battery serviced 9 CO2 sensors
• Total current draw :1A
• Lasted 36 hours after recharge
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Power Cycling Motivation
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• Batteries needed replacement/recharged every other day
• Carried every other day for ~ 3 Km
• 12V/40Ah car battery weighs 14Kg
• Power Cycling!– Warm up time: 15 min
Some Data
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Power Loss Sensors lack range
Ad Hoc Replacements
• At 11 locations, sensors lacked range to sense the phenomenon
• Distribution of CO2 hardware– 10000 ppm : 26– 20000 ppm : 12– 30000 ppm : 3– 100000 ppm : 3
• Researchers placed sensors initially– Reconfigured sensors if range was not good enough
• Final data calibration requires accurate metadata:– sensor type and date of reconfiguration
• Motivates need for self-Identifying sensors (Dallas 1-wire protocol)
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High Data Rates
• Decisions in field are driven by the data
• Researchers used netbook to download and view data
• 10 days of 30s sampling: ~ 576000 rows– Spreadsheet and word processing software unable to
handle this volume– Researchers stopped looking
• Downsample: Provide low-resolution “view” in the field
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System Performance
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Automated parts from existing system worked well.
Conclusions
• WSN technology is mature enough to be driven by scientists
• Challenges / Lessons Learned– Power cycling for high power sensors
– Self-Identifying sensor design
– Researchers require low-resolution data in field
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Credit
• NSF- MIRTHE, NSF- IDBR
• Microsoft Research
• Betty and Gordon Moore Foundation
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Questions
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