C. Wongchoosuk, C. Khunarak, M. Lutz, T. Kerdcharoen
{"title":"WiFi electronic nose for indoor air monitoring","authors":"C. Wongchoosuk, C. Khunarak, M. Lutz, T. Kerdcharoen","doi":"10.1109/ECTICON.2012.6254166","DOIUrl":null,"url":null,"abstract":"Several indoor chemical contaminants such as CO and NO2 are highly toxic. Inhalation of CO or NO2 as low as ppm level may cause respiratory distress or failure. Therefore, detection of indoor air is very important in the industrial, medical, and environmental applications. In this paper, a new electronic nose (E-nose) architecture has been proposed for the real-time quantification and qualification of indoor air contaminations. The metal oxide TGS gas sensors were used as the sensing part. The principal component analysis (PCA) method and a set of mathematical model were employed in data analysis. By combining with the proposed mathematical model, this E-nose can estimate the amount of CO gas contaminations in air at ppm levels. Moreover, the PCA results can clearly show a classification between two different rooms.","PeriodicalId":6319,"journal":{"name":"2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECTICON.2012.6254166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Several indoor chemical contaminants such as CO and NO2 are highly toxic. Inhalation of CO or NO2 as low as ppm level may cause respiratory distress or failure. Therefore, detection of indoor air is very important in the industrial, medical, and environmental applications. In this paper, a new electronic nose (E-nose) architecture has been proposed for the real-time quantification and qualification of indoor air contaminations. The metal oxide TGS gas sensors were used as the sensing part. The principal component analysis (PCA) method and a set of mathematical model were employed in data analysis. By combining with the proposed mathematical model, this E-nose can estimate the amount of CO gas contaminations in air at ppm levels. Moreover, the PCA results can clearly show a classification between two different rooms.