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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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Presentation on theme: "INSIGHT: Internet-Sensor Integration for Habitat Monitoring Murat Demirbas Ken Yian Chow Chieh Shyan Wan University at Buffalo, SUNY."— Presentation transcript:

1 INSIGHT: Internet-Sensor Integration for Habitat Monitoring Murat Demirbas Ken Yian Chow Chieh Shyan Wan University at Buffalo, SUNY

2 2 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 $80~$130) 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

3 3 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

4 4 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

5 5 Outline System architecture Energy-efficiency Reliability Internet-integration Deployment results

6 6 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

7 7 Basestation

8 8 Outline System architecture Energy-efficiency Reliability Internet-integration Deployment results

9 9 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

10 10 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

11 11 Outline System architecture Energy-efficiency Reliability Internet-integration Deployment results

12 12 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

13 13 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

14 14 Outline System architecture Energy-efficiency Reliability Internet-integration Deployment results

15 15 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

16 16 Demo http://INSIGHT.podzone.net

17 17 Outline System architecture Energy-efficiency Reliability Internet-integration Deployment results

18 18 Deployment

19 19 Effects of delta monitoring Our analysis and experimental results show a network lifetime of > 6 months

20 20 Temperature data Long periods of overheating (>40C) are observed Ceiling mote recorded 2C higher temperatures than average

21 21 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

22 22 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


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