Download 294 Presentation “sensors for phishing”

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

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
2
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
3
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
4
Outline
• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results
5
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
6
Basestation
7
Outline
• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results
8
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
9
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
10
Outline
• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results
11
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
12
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
13
Outline
• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results
14
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
15
Demo
http://INSIGHT.podzone.net
16
Outline
• System architecture
• Energy-efficiency
• Reliability
• Internet-integration
• Deployment results
17
Deployment
18
Effects of delta monitoring
• Our analysis and experimental results show a network
lifetime of > 6 months
Average Hourly Transmission Frequency in 24 Hours
Comparison of Delta Monitoring Energy Consumption
70
3.005
60
50
2.995
Packets
Max Freq
Min Freq
40
2.99
Volts
Packets Transmitted
3
2.985
Delta Mon., no LEDs
Delta Mon., LEDs
No Delta Mon., LEDs
30
2.98
20
2.975
2.97
10
2.965
0
0
1
6
11
16
21
1
2
3
4
5
6
Days
Time (Hour)
19
Temperature data
• Long periods of overheating (>40C) are observed
• Ceiling mote recorded 2C higher temperatures than average
20
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
21
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
22