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Particulate sensor developed using open source approach

A New York based start up company has used an open source approach, as well as funding from Kickstarter, to develop AirBeam – a handheld sensor which determines the concentration of particles in the air measuring 2.5µm or less.

According to AirCasting, PM2.5 is one of the six air pollutants monitored and regulated by the US Environmental Protection Agency. It's also a figure of interest to the EU, which has set a requirement that PM2.5 concentrations should not exceed 25µg/m3.

The reason for the concern is that these particles – produced from sources such as diesel car exhausts – are small enough to pass through the lungs and enter the bloodstream, with adverse health effects.

AirBeam, developed with Sonoma Technology and New York University's School of Medicine, draws air into a sensing chamber, where light from an LED is scattered from the particles in the air. A detector then estimates the number of particles in the air.

This data is transmitted once per second via Bluetooth to the AirCasting app on an Android phone, where it is graphed in real time. Areas with higher PM2.5 concentration are shown in red.

At the end of each AirCasting session, the collected data is sent to the AirCasting website, where the data is used to generate maps showing where PM2.5 concentrations are highest.

The company also plans to develop LiteBeam. This hand held device, which is built around the PIC microcontroller based IOIO board, takes data from the AirCasting app via Bluetooth and illuminates green, yellow or red LEDs, according to the concentration.

The AirCasting app and website code is available on GitHub as open source, along with the AirBeam firmware and electronic schematics. The STL files for 3D printing the AirBeam and LiteBeam enclosures can be downloaded from www.shapeways.com.

For more information on open source sensor software, click here.

Author
Graham Pitcher

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It will be interesting to see this technology unfold. Already numerous cities are implementing sensor networks into their infrastructure. Open source is certainly a huge advantage for AirCasting, but what else will set it apart enough to make it a realistic approach to monitoring air quality?

Posted by: Kat Dornian, 24/11/2014

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