insight: internet-sensor integration for habitat monitoring

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

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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 > 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

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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