空气质量监测预报系统

Shital Pawar, Swadesh Kelkar, Neeraja Khire, Tejas Khairnar, Maithili Kharabe
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引用次数: 2

摘要

工业革命以来,工业化和城市化的速度大大加快。大多数工业应用造成空气污染,这对人们的健康有害。汽车尾气排放也是造成这些问题的一个主要因素。大多数发展中国家遭受严重的空气污染。根据最近的报告,超过10个印度城市排名第一。空气质素是决定空气质素的重要因素。因此,为了使城市智能化和宜居化,必须定期监测空气质量指数。本研究旨在将物联网与云结合使用,使服务实时、更快。该系统的主要目标是基于实时传感器数据访问和可视化空气质量。每隔一段时间,测量每一种有害污染物的水平。计算出测量到的污染物的空气质量指数(AQI),并通过一个显示特定地点空气质量指数的网络应用程序提高公众的意识。进一步,建立了基于收集数据预测未来空气质量指数数值的ML模型,以便在空气质量指数最差的情况下对公共卫生做出预防安排。
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AQI Monitoring and Predicting System
The rate of industrialization and urbanization has accelerated substantially since the Industrial Revolution. The majority of industrial applications cause air pollution, which is hazardous to people's health. Vehicle emissions are also a major factor to these issues. The majority of developing countries suffer from severe air pollution. According to recent reports, more than ten Indian cities are ranked first. Air quality is an important component in determining air quality. As a result, in order to make a city smart and livable, the air quality index must be regularly monitored. This study aims to use IOT in conjunction with the cloud to make services real-time and faster. The system's primary goal is to access and visualize air quality based on real-time sensor data. At regular intervals, the level of each hazardous pollutant is measured. The Air Quality Index (AQI) for the measured pollutants is calculated, and public awareness is raised via a web application that shows the air quality index in that specific place. Further, ML model is developed which can predict future AQI index value based on the collected data which in order can helps in making precautions arrangements in the case of worst AQI index in concern of public health.
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