Microsystems & Nanoengineering (Oct 2024)

A Drosophila-inspired intelligent olfactory biomimetic sensing system for gas recognition in complex environments

  • Xiawei Yue,
  • Jiachuang Wang,
  • Heng Yang,
  • Zening Li,
  • Fangyu Zhao,
  • Wenyuan Liu,
  • Pingping Zhang,
  • Hong Chen,
  • Hanjun Jiang,
  • Nan Qin,
  • Tiger H. Tao

DOI
https://doi.org/10.1038/s41378-024-00752-y
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 12

Abstract

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Abstract The olfactory sensory system of Drosophila has several advantages, including low power consumption, high rapidity and high accuracy. Here, we present a biomimetic intelligent olfactory sensing system based on the integration of an 18-channel microelectromechanical system (MEMS) sensor array (16 gas sensors, 1 humidity sensor and 1 temperature sensor), a complementary metal‒oxide‒semiconductor (CMOS) circuit and an olfactory lightweight machine-learning algorithm inspired by Drosophila. This system is an artificial version of the biological olfactory perception system with the capabilities of environmental sensing, multi-signal processing, and odor recognition. The olfactory data are processed and reconstructed by the combination of a shallow neural network and a residual neural network, with the aim to determine the noxious gas information in challenging environments such as high humidity scenarios and partially damaged sensor units. As a result, our electronic olfactory sensing system is capable of achieving comprehensive gas recognition by qualitatively identifying 7 types of gases with an accuracy of 98.5%, reducing the number of parameters and the difficulty of calculation, and quantitatively predicting each gas of 3–5 concentration gradients with an accuracy of 93.2%; thus, these results show superiority of our system in supporting alarm systems in emergency rescue scenarios.