Method for predicting air quality using machine learning algorithms, involves training machine learning models to predict air quality levels with reasonable accuracy, identify patterns, trends and potential pollution sources, implement effective mitigation strategies and improve overall air quality
	SIVARAMAN; KUMAR G A; YOGITHA G; KOLA G V J; REDDY G C K; JANISHA J
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069565-A
成果简介	NOVELTY - The method involves analyzing historical data and various environmental factors. Machine learning (ML) models are trained to predict air quality levels with reasonable accuracy, assist in identifying patterns, trends and potential pollution sources, implement effective mitigation strategies and improve overall air quality. The accuracy and reliability of air quality predictions, the quality and availability of data, the selection of appropriate features and the choice of ML algorithms depend on several factors. The air quality is influenced by complex interactions of various atmospheric and environmental factors. USE - Method for predicting air quality using ML algorithms. ADVANTAGE - The method predicts air quality in locality using historical data and environmental factors, collects and processes a comprehensive dataset containing air quality measurements and relevant atmospheric and environmental features, employs data cleaning and feature engineering techniques to ensure data quality and extract meaningful information, measures the effects of air pollution on materials, vegetation, and animals, estimates health effects on humans from epidemiological evidence, provides the evidence which comes from occupational exposure to much higher concentrations of pollutants than the general-public is exposed to and the health effects of smoking and other lifestyle characteristics and exposures confound the observations of air pollutant effects, monitors and maintains air quality and under control for a better future and healthy living for all, examines and protects air quality avoids meteorological and traffic factors, burning of fossil fuels, industrial parameters, deposition of harmful gases e.g. sulfur dioxide in the air, irritation of the skin and mucous membranes of the eyes, nose, throat and lungs.
IPC 分类号	G01N-033/00 ; G06F-018/24 ; G06N-020/00 ; G06N-003/04 ; G06N-003/08 ; G06Q-010/04 ; G16Y-040/10 ; H04L-067/12
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19568
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	SIVARAMAN,KUMAR G A,YOGITHA G,et al. Method for predicting air quality using machine learning algorithms, involves training machine learning models to predict air quality levels with reasonable accuracy, identify patterns, trends and potential pollution sources, implement effective mitigation strategies and improve overall air quality. IN202341069565-A[P]. 2023.

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