文献类型：期刊文献

英文题名：A Quantitative Array Optimization Method for the Electronic Nose System Based on Edge Computing and MEMS Sensors

作者：Chen, Lechen[1,2];Wang, Tao[3];Ni, Wangze[1,2];Zhu, Jiaqing[4];Cheng, Weiwei[4];Mei, Haixia[5];Zhang, Bowei[3];Xuan, Fuzhen[3];Yang, Jianhua[1,2];Zeng, Min[1];Hu, Nantao[1,2];Yang, Zhi[1]

机构：[1]Shanghai Jiao Tong Univ, Natl Key Lab Adv Micro & Nano Manufacture Technol, Shanghai 200240, Peoples R China;[2]Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Dept Micro Nano Elect, Shanghai 200240, Peoples R China;[3]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai Key Lab Intelligent Sensing & Detect Tech, Shanghai 200237, Peoples R China;[4]Shanghai Univ Engn Sci, Sch Mat Sci & Engn, Shanghai 201620, Peoples R China;[5]Changchun Univ, Key Lab Intelligent Rehabil & Barrier Free Disable, Minist Educ, Changchun 130022, Peoples R China

年份：2024

卷号：8

期号：11

外文期刊名：IEEE SENSORS LETTERS

收录：EI(收录号：20244417284508);WOS:【ESCI(收录号:WOS:001346715400001)】；

基金：This work was supported in part by the National Key Research and Development Program of China under Grant 2022YFB3205500, in part by the National Natural Science Foundation of China under Grant 62301314, 62371299 and Grant 62101329, in part by the China Postdoctoral Science Foundation under Grant 2023M732198, and in part by the Natural Science Foundation of Shanghai under Grant 23ZR1430100.

语种：英文

外文关键词：Sensor systems; array optimization; electronic nose (E-nose); micro-electro-mechanical systems (MEMS) sensor; multitask model; quantitative indicator; array optimization; electronic nose (E-nose); micro-electro-mechanical systems (MEMS) sensor; multitask model; quantitative indicator

摘要：The selection of the sensor array represents a pivotal aspect of the system design for the electronic nose (E-nose). In practical applications, achieving an optimal balance between array size and system performance is often challenging. Therefore, realizing a high-performance E-nose with a minimum number of sensors is necessary, particularly for portable E-noses with limited size and power. This letter proposes a cost-effectiveness ratio (CER) as an array optimization criterion to address these issues. The CER is defined for quantifying costs and benefits as a basis for array optimization. Applying the designed array optimization criterion to the portable E-nose system, which comprises eight MEMS sensors, achieves an 80% prediction accuracy while reducing the number of sensors by nearly 40%. In addition, the concept of extreme sensor number is proposed to illustrate the existence of limit values for the number of sensors in the process of array optimization. This study offers a foundation for quantitative metrics for sensor array optimization, which serves as a crucial reference for the design of size- and power-sensitive portable E-nose systems.