通过关联空气和噪音污染传感器记录来识别室外环境

Biswajit Maity, Yashwant Polapragada, Arindam Ghosh, Sanghita Bhattacharjee, S. Nandi
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引用次数: 4

摘要

在城市地区,环境噪音和空气污染的程度对人们的生活质量起着至关重要的作用。由于快速城市化,这两种污染物的影响日益增加。尽管创建实时污染地图和预测污染水平已经得到了广泛的研究,但空气和噪音污染之间的背景、时空相关性还没有得到彻底的研究。这种相关性对于确定城市地区的特征非常重要。在本文中,我们强调了从不同污染物数据中识别上下文有用的一些方面。为了收集噪声数据,我们开发了一个基于android的应用程序“AudREC”,该应用程序使用内置的移动麦克风传感器。此外,在测量空气污染物方面,我们使用了一个现成的“Flow”装置,可以检测PM2.5和CO2等。初步的室外实验证明了该平台从空气和噪声污染信息中识别上下文的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Outdoor Context by Correlating Air and Noise Pollution Sensor Log
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 CO2, etc. The initial outdoor experiments show the feasibility of the platform for recognizing contexts from air and noise pollution information.
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