INSIGHT: InternetSensor Integration for Habitat Monitoring

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INSIGHT Internet-Sensor Integration for
Habitat Monitoring

• Murat Demirbas
• Ken Yian Chow
• Chieh Shyan Wan
• University at Buffalo, SUNY

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WSN for monitoring

• A sensor node (Tmote)
• CC2420 Radio compliant with IEEE 802.15.4 and is
  Zigbee ready
• 8MHz Texas Instruments MSP430 microcontroller
  (10k RAM, 48k Flash)
• integrated onboard antenna with 50m range indoors
  / 125m range outdoors
• integrated humidity, temperature, and light
  sensors ( internal voltage)
• costs in bulk 5 (now 80130)
• WSN can improve Supervisory Control and Data
  Acquisition (SCADA)
• monitoring and control of a plant in industries
  such as telecommunications, water and waste
  control, energy, and transportation

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Requirements for WSN monitoring

• Energy efficiency
• the sensor nodes should not need batteries for at
  least 6 months
• Remote querying and reconfiguration
• query data and reconfigure parameters via the
  Internet
• Ease of deployment
• no pre-configuration needed
• Reliability
• high availability, quick recovery

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Our contributions

• Remote querying
• basestation serves webserver and SQL database
• Data can be visualized, plotted, compared via
  webpage
• Email alerts based on user-defined subscriptions
• XML interface for data extraction
• Energy-efficiency
• 6 months requirement met via HPL power
  management, delta reporting
• Ease of deployment
• drop and play functionality via singlehop network
  decision
• Reliability
• reset-timers soft-state system
• Deployment at a greenhouse
• 2 months deployment at UB greenhouse exposed
  overheating problem

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Outline

• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results

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System overview

• Single-hop network
• Basestation serves webpage
• access via web-browser or running an XML query
• To circumvent firewall
• a replica is established
• replica obtains new data periodically via XML
  query

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Basestation
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Outline

• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results

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HPL power management

• To enable HPL sleep mode, radio is turned off
  after transmission
• Motes wake-up 1 sec every minute for sampling and
  transmission
• 2 orders of magnitude power-saving is possible
• Since motes do not need to relay transmission
  from more distant motes, wake-up times are kept
  short, and need not be coordinated

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Delta monitoring

• If the change in sensed-values between subsequent
  samplings are insignificant (less than delta),
  mote goes back to sleep without transmission
• originally proposed in TinyDB
• highly sensitive (fast-reaction) to changes in
  sensed values, and yet energy-efficient in the
  steady case scenario
• In our implementation, after 20 duty cycles
  cumulative average readings are reported to the
  basestation as part of a heartbeat message, and
  average is reset
• we set delta for humidity is 1, for temperature
  0.2C, for light 2 lux, and for voltage 0.03 volts

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Outline

• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results

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Reset timers

• Event losses might lead to livelocks in TinyOS
• Transmission Pending bit not being reset after
  transmission is done
• we appended a reset-timer to fix the problem
• Watchdog timer to recover frozen motes
• if not reset by application, its overflow
  interrupt forces a soft reset
• Watchdog timer script resets the TinyBaseStation
  application, the webserver and the database if
  they become unresponsive

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Ease of deployment

• The system can be up by just turning on all the
  motes and the basestation
• No state is maintained at the motes
• in a singlehop network no coordination is needed
  for routing/relaying
• No state is maintained at the basestation
• all essential applications launch automatically
  on startup
• users can locate the webpage by navigating to a
  dynamic DNS address
• MySQL stores motes information and sensor data
• sensor data is timestamped as it arrives in the
  database

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Outline

• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results

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Ease of use

• Web-based user-interface is easy to understand
• Graphical overview
• provides access to the data by using graphs
• Tactical overview
• provides real-time access to the data in a
  top-view image
• Query wizard
• the wizard asks a question and the user select
  the options desired

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Demo

• http//INSIGHT.podzone.net

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Outline

• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results

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Deployment
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Effects of delta monitoring

• Our analysis and experimental results show a
  network lifetime of gt 6 months

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Temperature data

• Long periods of overheating (gt40C) are observed
• Ceiling mote recorded 2C higher temperatures
  than average

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Concluding remarks

• Insight simplifies high-fidelity remote querying
  monitoring
• internet is ubiquitous
• users are familiar with web-browsers
• Due to singlehop architecture no preconfiguration
  is needed
• no need for time sync, routing, and coordination
  algorithms
• If a PC is already available, price is just the
  cost of the motes
• Lifetime is around 6 months with sampling every
  minute

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Future work

• Integrating actuator/control mechanisms (X10?)
• Using predictive monitoring to improve energy
  efficiency
• using Internet to obtain info that can help
  predictive monitoring
• Integration with Google-Earth
• An Internet-wide system for querying sensor data
  from Insight deployments