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

被引：0

作者：

Yue, Xiawei ^{[1
,2
]}

Wang, Jiachuang ^{[1
,2
]}

Yang, Heng ^{[1
,2
]}

Li, Zening ^{[1
,2
]}

Zhao, Fangyu ^{[1
,2
]}

Liu, Wenyuan ^{[1
,2
]}

Zhang, Pingping ^{[3
]}

Chen, Hong ^{[4
]}

Jiang, Hanjun ^{[4
]}

Qin, Nan ^{[1
,2
]}

Tao, Tiger H. ^{[1
,2
,5
,6
,7
,8
,9
,10
]}

机构：

[1] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, State Key Lab Transducer Technol, Shanghai 200050, Peoples R China

[2] Univ Chinese Acad Sci, Sch Grad Study, Beijing 100049, Peoples R China

[3] Suzhou Huiwen Nanotechnol Co Ltd, Suzhou 215004, Jiangsu, Peoples R China

[4] Tsinghua Univ, Sch Integrated Circuits, Beijing 100084, Peoples R China

[5] Univ Chinese Acad Sci, Ctr Mat Sci & Optoelect Engn, Beijing 100049, Peoples R China

[6] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, 2020 X Lab, Shanghai 200050, Peoples R China

[7] Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China

[8] Neuroxess Co Ltd Jiangxi, Nanchang 330029, Jiangxi, Peoples R China

[9] Guangdong Inst Intelligence Sci & Technol, Zhuhai 519031, Guangdong, Peoples R China

[10] TianQiao & Chrissy Chen Inst Translat Res, Shanghai, Peoples R China

来源：

MICROSYSTEMS & NANOENGINEERING | 2024年 / 10卷 / 01期

基金：

中国国家自然科学基金;

关键词：

SENSOR ARRAY; SURFACE;

D O I：

10.1038/s41378-024-00752-y

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

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.

引用

页数：12