COVID19: Forecasting Air Quality Index and Particulate Matter (PM2.5)
作者机构：School of Information Technology and EngineeringVellore Institute of TechnologyVellore632007India Department of Computer ScienceCollege of Computer Science and EngineeringTaibah University41477Saudi Arabia Department of Electrical EngineeringUmm Al Qura UniversityMakkah21955Saudi Arabia School of Computer Science and Engineering and EngineeringVellore Institute of TechnologyVellore632007India
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2021年第67卷第6期
页 面：3363-3380页
核心收录：
学科分类：07[理学] 070602[理学-大气物理学与大气环境] 0706[理学-大气科学]
基 金：funded by grant number 14-INF1015-10 from the National Science Technology,and Innovation Plan(MAARIFAH) the King Abdul-Aziz City for Science and Technology(KACST) Kingdom of Saudi Arabia.We thank the Science and Technology Unit at Umm Al-Qura University for their continued logistics support
主 题：AQI PM2.5 COVID19 air quality in India AQI-forecasting
摘 要：Urbanization affects the quality of the air,which has drastically degraded in the past *** quality level is determined by measures of several air pollutant *** create awareness among people,an automation system that forecasts the quality is *** COVID-19 pandemic and the restrictions it has imposed on anthropogenic activities have resulted in a drop in air pollution in various cities in *** overall air quality index(AQI)at any particular time is given as the maximum band for any ***2.5 is a fine particulate matter of a size less than 2.5 micrometers,the inhalation of which causes adverse effects in people suffering from acute respiratory syndrome and other cardiovascular ***2.5 is a crucial factor in deciding the overall *** proposed forecasting model is designed to predict the annual PM2.5 and *** forecasting models are designed using Seasonal Autoregressive Integrated Moving Average and Facebook’s Prophet Library through optimal hyperparameters for better *** AQI category classification model is also presented using classical machine learning *** experimental results confirm the substantial improvement in air quality and greater reduction in PM2.5 due to the lockdown imposed during the COVID-19 crisis.
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