Source Classification of Indoor Air Pollutants Using Principal Component Analysis for Smart Home Monitoring Applications

摘要

Indoor air pollution has much greater impact on our health than we perceive. Presence of particulates and volatile organic compounds (VOCs) in indoor air are in much higher concentrations than outdoor air. These particulates and VOCs are known to cause numerous health problems to millions of people every year. This paper presents a solution for passive and continuous monitoring of harmful VOCs using a sensor array. We tested common household products for VOCs emissions. The items were tested in a controlled laboratory setting which simulated an indoor environment. In the laboratory, the developed system was able to detect the presence of the harmful VOCs and classify the sources of those VOCs. Principal component analysis (PCA) was used for identification and classification. The presented system aims to assist the users to monitor the presence of harmful VOCs and inform about their possible sources. How we designed the system and the test results are presented and discussed.