{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:41:42Z","timestamp":1783579302403,"version":"3.55.0"},"reference-count":151,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T00:00:00Z","timestamp":1567123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872038, 42161811530335, 61774014"],"award-info":[{"award-number":["61872038, 42161811530335, 61774014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities under Grant","award":["FRF-BD-18-016A"],"award-info":[{"award-number":["FRF-BD-18-016A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the development of the Internet-of-Things (IoT) technology, the applications of gas sensors in the fields of smart homes, wearable devices, and smart mobile terminals have developed by leaps and bounds. In such complex sensing scenarios, the gas sensor shows the defects of cross sensitivity and low selectivity. Therefore, smart gas sensing methods have been proposed to address these issues by adding sensor arrays, signal processing, and machine learning techniques to traditional gas sensing technologies. This review introduces the reader to the overall framework of smart gas sensing technology, including three key points; gas sensor arrays made of different materials, signal processing for drift compensation and feature extraction, and gas pattern recognition including Support Vector Machine (SVM), Artificial Neural Network (ANN), and other techniques. The implementation, evaluation, and comparison of the proposed solutions in each step have been summarized covering most of the relevant recently published studies. This review also highlights the challenges facing smart gas sensing technology represented by repeatability and reusability, circuit integration and miniaturization, and real-time sensing. Besides, the proposed solutions, which show the future directions of smart gas sensing, are explored. Finally, the recommendations for smart gas sensing based on brain-like sensing are provided in this paper.<\/jats:p>","DOI":"10.3390\/s19173760","type":"journal-article","created":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T10:31:17Z","timestamp":1567161077000},"page":"3760","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":298,"title":["Review on Smart Gas Sensing Technology"],"prefix":"10.3390","volume":"19","author":[{"given":"Shaobin","family":"Feng","sequence":"first","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fadi","family":"Farha","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingjuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yueliang","family":"Wan","sequence":"additional","affiliation":[{"name":"Beijing Engineering Research Center for Cyberspace Data Analysis and Applications, Beijing 100083, China"},{"name":"Research Institute, Run Technologies Co., Ltd. Beijing, Beijing 100192, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Lab of Information Network Security of Ministry of Public Security (The Third Research Institute of Ministry of Public Security), Shanghai 201204, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6413-193X","authenticated-orcid":false,"given":"Huansheng","family":"Ning","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China"},{"name":"Beijing Engineering Research Center for Cyberspace Data Analysis and Applications, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chen, J., Gu, J., Zhang, R., Mao, Y., and Tian, S. 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