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Liora Malki-Epshtein (CEGE), Venus Shum (Computer Science) Bracelet v2 ( Figure 5) uses I2C buses and allows for more modules to be attached to

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TEMPLATE DESIGN © 2008

www.PosterPresentations.com Spatio-temporal Description of Air Quality with Mobile and Static Arrays of MOS Sensors Serge Guillas (Statistical Science), Russell Binions & Daren Caruana (Chemistry) Liora Malki-Epshtein (CEGE), Venus Shum (Computer Science)

About this Group

A variety of air pollutants have known harmful effects on human health and the environment. The London Air Quality Network is made of 160 continuous monitoring sites. However, in urban settings, the concentrations of these pollutants can vary dramatically. Hence, some streets layouts with corresponding trace may lead to unsustainable local levels of concentrations. We have teamed up researchers from statistical science, chemistry and computer science departments to develop new science in pollution monitoring and modeling with pervasive sensing technologies. The areas we work on include:- •!State of Art Gas Sensors - we evaluate the performance and limitation of commonly used electrochemical gas sensors for pervasive applications •!Metal Oxide Sensors (MOS) - we research into the latest advance in MOS technology and the suitability of the sensors for portable applications •!Wireless Sensor Network (WSN) - we research into the hardware and software aspects of the technology •!Pollution modeling - we investigate new technique for pollution modeling using fine-grain, mobile sensor data provided by WSN

Bracelet Hardware Platform

Bracelet is the flexible, portable, modular hardware platform developed by the Computer Science department for pervasive sensing applications. Different modules, including procesors, radio modules, GPS modules, sensors, interface boards, external memory modules can be mixed and matched, tailored for the application. Bracelet v1 (Figure 4) uses SPI communication bus between the modules. Bracelet v2 (Figure 5) uses I2C buses and allows for more modules to be attached to the platform.

Figure 4

Calibration

The gas sensors with their sensor modules must be calibrated (Figure 6) individually before deployment. Ideally, they should be calibrated against environmental factors including temperature and humidity.

Implementation and Data Analysis Future Work Contact information

A small lab trial with 5 sensor nodes (2 with CO sensors) and 1 base station (sink). The sensor nodes take readings at regular interval and send the information back to the base station wirelessly. The base station display the information to the user. (Figure 7) We have demonstrate the use of portable gas sensor units for pervasive pollution monitoring application. In the near future, •! Deploy 20 sensor units in a street-canyon environment in London to collect fine-grain temporal-spatial data. •! Research and develop the use of MOS sensor in pervasive monitoring. •! Use the data collected to develop new technique for pollution modeling. •! Investigate other similar application domains for the techniques developed. Statistical Science Department Serge Guillas [serge@stats.ucl.ac.uk] Chemistry Department Russell Binions [uccarbi@ucl.ac.uk] Daren Caruana [d.j.caruana@ucl.ac.uk]

Processor

board

Wireless

board

USB-serial interface

(for programming only) Power board

Bracelet strip (mounted on fibre glass for

development purpose)

USB GPS

Figure 5

Sensor Module

Several commercial Carbon Monoxide (CO) electrochemical sensors (Figure 1) were evaluated to see if they are suitable to detect the range of street-level pollution level. The calibration looks at their sensitivity (Figure 2) towards the gas and the response time (Figure 3). The bigger sensors tends to have better sensitivity and quicker response time.

-50510152025 0 500
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CO concentration (ppm)

ADC reading (4096 = 3.3V)

RCO100F: y=103.9828x + 387.8499 mV

3CO1ET1500: y=74.4762x + 327.0358 mV

COAX: y=48.4801x + 252.2829 mV

COBX: y=63.6403x + 231.9754 mV

CO-D4: y=23.5547x + 223.3620 mV

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Metal Oxide Sensors

Figure 1

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