Air Quality Monitoring for Vulnerable Groups in Residential Environments Using a Multiple Hazard Gas Detector

• Main Authors: Yujiao Wu, Taoping Liu, Sai Ho Ling, Jan Szymanski, Wentian Zhang, Steven Weidong Su
• Format: Article
• Language: English
• Published: MDPI AG 2019-01-01
• Series: Sensors
• Subjects: electronic nose; environmental monitoring; remote sensing and control
• Online Access: http://www.mdpi.com/1424-8220/19/2/362

This paper presents a smart “e-nose” device to monitor indoor hazardous air. Indoor hazardous odor is a threat for seniors, infants, children, pregnant women, disabled residents, and patients. To overcome the limitations of using existing non-intelligent, slow-responding, deficient gas sensors, we propose a novel artificial-intelligent-based multiple hazard gas detector (MHGD) system that is mounted on a motor vehicle-based robot which can be remotely controlled. First, we optimized the sensor array for the classification of three hazardous gases, including cigarette smoke, inflammable ethanol, and off-flavor from spoiled food, using an e-nose with a mixing chamber. The mixing chamber can prevent the impact of environmental changes. We compared the classification results of all combinations of sensors, and selected the one with the highest accuracy (98.88%) as the optimal sensor array for the MHGD. The optimal sensor array was then mounted on the MHGD to detect and classify the target gases without a mixing chamber but in a controlled environment. Finally, we tested the MHGD under these conditions, and achieved an acceptable accuracy (70.00%).