Selective Sensing of Mixtures of Gases with CMOS-SOI-MEMS Sensor Dubbed GMOS

Adir Krayden, Dima Shlenkevitch, Tanya Blank, Sara Stolyarova, Yael Nemirovsky

Research output: Contribution to journalArticlepeer-review

Abstract

The need to achieve digital gas sensing technology, namely, a technology to sense and transmit gas-enabled digital media, has been recognized as highly challenging. This challenge has motivated the authors to focus on complementary metal oxide semiconductor silicon on insulator micro electro-mechanical system (CMOS-SOI-MEMS) technologies, and the result is a new pellistor-like sensor, dubbed GMOS, with integrated signal processing. In this study, we describe the performance of such sensors for the selective detection of mixtures of gases. The novel key ideas of this study are: (i) the use of the GMOS for gas sensing; (ii) applying the Kalman filter to improve the signal-to-noise ratio; (iii) adding artificial intelligence (AI) with tiny edge approach.

Original languageEnglish
Article number390
JournalMicromachines
Volume14
Issue number2
DOIs
StatePublished - Feb 2023

Keywords

  • classification
  • data analytics
  • gas sensor
  • Kalman filtering
  • machine learning
  • MEMS
  • MOS
  • SOI
  • tinyML

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Electrical and Electronic Engineering

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