insight: internet-sensor integration for habitat monitoring
DESCRIPTION
INSIGHT: Internet-Sensor Integration for Habitat Monitoring. Murat Demirbas Ken Yian Chow Chieh Shyan Wan University at Buffalo, SUNY. WSN for monitoring. A sensor node (Tmote) CC2420 Radio compliant with IEEE 802.15.4 and is Zigbee ready - PowerPoint PPT PresentationTRANSCRIPT
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 $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
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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
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
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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 > 6 months
Average Hourly Transmission Frequency in 24 Hours
0
10
20
30
40
50
60
70
1 6 11 16 21
Time (Hour)
Pac
kets
Tra
nsm
itte
d
Packets
Max Freq
Min Freq
Comparison of Delta Monitoring Energy Consumption
2.965
2.97
2.975
2.98
2.985
2.99
2.995
3
3.005
0 1 2 3 4 5 6
Days
Vo
lts
Delta Mon., no LEDs
Delta Mon., LEDs
No Delta Mon., LEDs
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Temperature data
• Long periods of overheating (>40C) 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