Air pollution monitoring system.

V. Revathy, K. Ganesan, K. Rohini, S. T. Chindhu, T. Boobalan
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引用次数: 15

Abstract

In recent years, the problem of low air quality has been discussed in mass media over and over, with increasing urgency. Air pollutants are many and varied - caused by industrial and domestic activities, natural disasters and accidents, and more. Continuous daily breathing of polluted air has a bad effect on human health. The availability and easy access to up-to-date air quality information is useful for citizens when they plan outdoor activities and for their health prevention. There are numerous software applications on the web that track different characteristics of air quality in various cities. Some of them collect data using their own measuring stations, while others collect data from specialized sensors that citizens purchase and install at their preferred location. The task of aggregating data from multiple sources and providing it to users in an appropriate format is a topical task. The paper presents a web application that reports real-time air quality in a user-selected city. The application visualizes information on air temperature and humidity, particulate matter levels, ozone, nitrogen dioxide, ozone and sulfur dioxide. The data is collected using web services from various sources – informational websites and specialized sensors. Future work is directed toward the use of artificial neural networks to predict air pollution, and to determine real-time air quality at points where no measuring stations exist.
空气污染监测系统。
近年来,空气质量低下的问题在大众媒体上被反复讨论,越来越紧迫。空气污染物种类繁多,包括工业和家庭活动、自然灾害和事故等。每天持续呼吸被污染的空气对人体健康有不良影响。公民在规划户外活动和预防健康时,可以方便地获得最新的空气质量信息。网上有许多软件应用程序可以跟踪不同城市空气质量的不同特征。其中一些城市使用自己的测量站收集数据,而另一些城市则通过市民购买并安装在自己喜欢的地方的专用传感器收集数据。聚合来自多个数据源的数据并以适当的格式提供给用户的任务是一项主题任务。本文介绍了一个网络应用程序,可以实时报告用户选择的城市的空气质量。该应用程序将空气温度和湿度、颗粒物水平、臭氧、二氧化氮、臭氧和二氧化硫等信息可视化。这些数据是通过各种来源的网络服务收集的——信息网站和专门的传感器。未来的工作方向是使用人工神经网络来预测空气污染,并在没有测量站的地方确定实时空气质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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