Identifying Outdoor Context by Correlating Air and Noise Pollution Sensor Log

Abstract

In an urban area, the degree of ambient noise and air pollution play a vital role in determining the quality of human life. The impact of these two pollutants is increasing day-by-day due to rapid urbanization. Although, creating real-time pollution maps and forecasting of pollution levels have been studied extensively, the contextual, spatio-temporal correlation between air and noise pollution has not been investigated thoroughly. This correlation is important to identify the characteristics of an urban area. In this paper, we have highlighted some aspects that are useful to identify a context from different pollutant data. To collect the noise data, we have developed an android based application “AudREC” that uses the inbuilt mobile micro-phone sensor. Moreover, for measuring air pollutants, we have used a ready-made “Flow” device that senses PM2.5 and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , etc. The initial outdoor experiments show the feasibility of the platform for recognizing contexts from air and noise pollution information.