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.
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页数:12
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