Wireless Sensor Networks for Habitat Monitoring: Architecture, Sensors, Energy Management, Study notes of Computer Science

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CMSC 828K: Wireless Sensor Networks

Amol Deshpande

University of Maryland, College Park

September 4, 2007

Administrivia

Introductions

Summaries

Text only

List three questions you would have liked answers to

How far are the technologies?

The assumptions don’t make sense

I wish they had compared against that approach..

Assignments, projects

2 guest lectures end September

Habitat Monitoring

“Wireless Sensor Networks for Habitat Monitoring”; Alan

Mainwaring et al; WSNA 2002.

One of the first real deployments

Small island near Maine

Monitoring Leach’s storm Petrel

Usage patterns of nesting burrows?

Changes in the burrows during 7 month breeding season

Differences in micro-environments with and without the

birds?

Application-driven paper

Illustrates all the details you need to worry about

Habitat Monitoring: System Architecture

geable

Al- ons, ths. rest en- olar op- wer rob- y to Al- Figure 1 : System architecture for habitat monitor- ing

Habitat Monitoring: Sensor Nodes

UC Berkeley motes: Mica

Single channel 916 MHz radio at 40kbps Atmel Atmega 103 microcontroller 4MHz Nonvolatile storage: 512 KB 2 AA Batteries 2.0 * 1.5 * 0.5 inches

libration data or threshold filters), according to the application’s needs. al data logging systems, networked advantages: they can be retasked in asily communicate with the rest of king allows the scientists to refocus on the analysis of the initial results. e want to collect the absolute tem- ver after the initial interpretation ealize that significant temperature ned threshold are most interesting. s communicate and coordinate with s will typically form a multihop net- other’s messages, which vastly ex- ns. If appropriate, the network can egation (e.g., reporting the average gion). This flexible communication roduce a network that delivers the ting the energy requirements. We nt communication protocols in Sec- Figure 2: Mica Hardware Platform: The Mica sen- sor node (left) with the Mica Weather Board devel- oped for environmental monitoring applications

Habitat Monitoring: Sensor Nodes

Sensor Accuracy Interchangeability Sample Rate Startup Current Photoresistor N/A 10% 2000 Hz 10 ms 1. 235 mA I^2 C Temperature 1 K 0. 20 K 2 Hz 500 ms 0. 150 mA Barometric Pressure 1. 5 mbar 0.5% 10 Hz 500 ms 0. 010 mA Barometric Pressure Temp 0. 8 K 0. 24 K 10 Hz 500 ms 0. 010 mA Humidity 2% 3% 500 Hz 500- 30000 ms 0. 775 mA Thermopile 3 K 5% 2000 Hz 200 ms 0. 170 mA Thermistor 5 K 10% 2000 Hz 10 ms 0. 126 mA

Table 1: Mica Weather Board: Characteristics of each sensor included on the Mica Weather Board.

4.2 Sensor Board

To provide relevant measurements to scientists, we de- signed and manufactured an environmental monitoring sen- sor board, shown in Figure 2. The Mica Weather Board provides sensors that monitor changing environmental con- ditions with the same functionality as a traditional weather station. The Mica Weather Board includes temperature, photoresistor, barometric pressure, humidity, and passive infrared (thermopile) sensors. The barometric pressure module is a digital sensor man- ufactured by Intersema. The sensor is sensitive to 0. 1 mbar of pressure and has an absolute pressure range from 300 to 1100 mbar. The module is calibrated during manufacturing and the calibration coefficients are stored in EEPROM per- sistent storage. The pressure module includes a calibrated temperature sensor to compensate raw barometric pressure readings. The humidity sensor is manufactured by General Eastern. It is a polymer capacitive sensor factory calibrated to within

terchangeability and accuracy, the sensors can be deployed in the field quicker since little or no calibration is needed prior to deployment. Another key aspect of choosing a sen- sor is its startup time. The start up time is the time a sensor must be powered before its reading stabilizes. Sensors with long start up times require current for a longer period of time, resulting in higher power consumption. Minimizing start up time yields more power per day to perform other tasks, such as routing and communication. Start up times for each sensor are listed in Table 1. The unique combination of sensors can be used for a va- riety of aggregate operations. The thermopile may be used in conjunction with its thermistor and the photoresistor to detect cloud cover [6]. The thermopile may also be used to detect occupancy, measure the temperature of a nearby object (for example, a bird or a nest), and sense changes in the object’s temperature over time. If the initial altitude is known, the barometer module may be used as an altimeter. Strategically placed sensor boards with barometric pressure sensors can detect the wind speed and direction by mod-

Details about the sensors in the paper

Things to note:

Each sensor has < 3% variation wrt others of the same

model

Accurate within 3% (both allow fast deployment)

Small startup times

Individual components on the sensor board can be

turned on/off

Platforms enabling the WSNs

Architecture will typically be dictated by the application

Expect a 4-tier architecture in many cases

sensor-network hardware, extrapolating future capa-

bilities in future devices.

Platform Classes

Initial deployment experience has shown that sensor

network systems require a hierarchy of nodes start-

ing at low-level sensors and continuing up through

high-level data aggregation, analysis, and storage

nodes (see Figure 1). This tiered architecture is com-

mon in virtually all sensor networks and is best illus-

trated by example.

but often need to be plugged into the public

system for long-term operation.

In addition to traditional security appli

wireless sensor networks are being designed t

mobile assets, as well as personnel, through a

tiny, low-cost security tags (mini-motes). Th

cial-purpose sensor nodes are synonymou

Smart Dust [8], or cubic-millimeter-scale devi

ported by extremely limited energy resource

could trigger an alarm when an asset leaves a

without authorization. M

they must be highly integra

very inexpensive.

In security systems, th

network of sensors is likely

one or more end points con

a database or other aggr

software designed to proc

store individual sensor re

These head, or gateway,

provide an interface into

existing types of networks.

Table 1 outlines typical

ing characteristics of th

classes of nodes—specialize

ing platform, generic sensi

form, high-bandwidth s

and gateway—implemente

state-of-the-art technolog

Spec node the autho

designed at the University

fornia, Berkeley, is representative of the spec

Web interfaces, databases

Cameras, microphones

Dozens of high-bandwidth sensors

Door, window, motion sensors

Asset tags

A few gateway nodes

The Internet

Hundreds of generic sensor nodes

Thousands of special-purpose sensors

Figure 1. Hierarchical

Platforms enabling the WSNs

and door-and-window sensors as the foundation of a

building security system. Moreover, the Mica2 is

capable of receiving messages from Spec nodes

attached to high-value assets, including personal com-

puters and laptops, at risk of being stolen. The mem-

ory and processing power available on the Mica2 node

easily handles the computa-

tion required to keep track

of several dozen Spec-based

asset tags.

networks, including 802.11, Ether

varieties. Moreover, the processing

visions on the Stargate node allow

front-end to sensor networks wh

data via a Web browser.

The operating system running o

form must be m

form’s under

capabilities. Fo

and generic-sen

special operati

TinyOS (develo

sity of Califor

designed to run

limited CPU p

space. Unlike

operating system

integration betw

nectivity and

tions. Howev

capabilities im

example, the

more advanced

support is required to meet the

complex applications. Multiproc

task switching, and even virtual

become desirable when managin

Node Type

Sample “Name” and Size

Typical Application Sensors

Radio Bandwidth (Kbps)

MIPS

Flash RAM

Typical Active Energy (mW)

Typical Sleep Energy (uW)

Typical Duty Cycle (%) Specialized sensing platform

Generic sensing platform

High- bandwidth sensing

Gateway

Spec

mm 3

Mote

1-10cm 3

Imote

1-10cm 3

Stargate

10cm 3

Specialized low- bandwidth sensor or advanced RF tag

General-purpose sensing and communications relay

High-bandwidth sensing (video, acoustic, and vibration)

High-bandwidth sensing and communications aggregation Gateway node

<50Kbps

<100Kbps

~500Kbps

500Kbs– 10 Mbps

< 0.1Mb < 4Kb < 10 < 0.5Mb <10Kb < 50 <10Mb <128Kb < < 32Mb < 512Kb

1.8V*10–

15mA

3V*10–

15mA

3V*60mA

3V*200mA

1.8V *1uA

3V *10uA

3V *100uA

3V *10mA

Table 1. Typical operating

characteristics of the four

classes of sensor-network

nodes.

Major challenges

Programming interfaces/abstractions

A lot of variety in the platforms

Need new abstractions for power-constrained devices

Event-based, FSM-based (finite state model)

programming

Direct interfacing with the hardware (interrupts etc)

Motes don’t have screens (LEDs used for debugging)

Reprogramming?

Need to do it remotely

Major challenges

Networking

Traditional protocols don’t work

Reliable multi-hop is tricky

Inherently lossy channel

Instead of trying to guarantee message delivery, work

around it.

Localization

GPS may be too energy-expensive

Time synchronization

Links

WSN Tutorial

Glucotel

Pressure sensors in the eye

WSN Blog

Bridge

RFID