https://doi.org/10.1140/epjti/s40485-014-0009-z
LETTER
Real-time gas identification on mobile platforms using a nanomechanical membrane-type surface stress sensor
1
World Premier International (WPI) Research Center Initiative, International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, 305-0044, Japan
2
University of Waterloo, 200 University Ave W, Waterloo, N2L 3G1, Canada
* e-mail: YOSHIKAWA.Genki@nims.go.jp
Received:
23
June
2014
Accepted:
19
August
2014
Published online:
30
September
2014
Here we show real-time multiple gas identification on a mobile platform through the use of an array of nanomechanical membrane-type surface stress sensors (MSS). Commercially available hardware is used to integrate the MSS array into a portable unit with wireless capability. This unit transmits data to a consumer mobile tablet where data is displayed and processed in real-time. To achieve real-time processing with the limited computational power of commercial mobile hardware, a machine learning algorithm known as Random Forest is implemented. We demonstrate the real-time identification capability of the device by measuring the vapours of water, ethanol, isopropanol, and ambient air.
Key words: Random forest / MSS / Piezoresistive / Gas identification / Android / Mobile phone
© The Author(s), 2014