INSIGHT: Internet-Sensor Integration for Habitat Monitoring

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

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

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. Basestation

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

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

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

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. Demo http://INSIGHT.podzone.net

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

18. Deployment

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

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

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. 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