ISSN 2394-5125
 

Research Article 


AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW

Sneha P Khedekar, Dr. Sunil B Thakare.

Abstract
Predicting air pollutant concentration in urban areas is a subject of considerable interest in research into air quality due to the
recognition of its connection with health effects. Long-term regulation of air pollution is important in order to avoid the longterm
situation from getting worse. Recently, a lot of attention was paid to the improvement of methods which are used to air
quality forecasting.The air pollution problems in developing countries deserve more attention because the air in developing
countries is more polluted, and less research is being done to reduce emissions compared to developed countries. As part of an
effective urban air quality management program, monitoring, evaluation and forecasting of ambient air pollutants in urban
corridors have thus become an integral requirement. Recently, due to developments in Artificial Intelligence applications and
the availability of environmental sensing networks and sensor data, several researchers have started using the Artificial
Intelligence techniques. The purpose of this research paper is to explore various Artificial Intelligence techniques for air quality
prediction. This paper summarizes the reported findings of work related to air quality assessment using artificial intelligence
approaches, decision trees, deep learning etc. This also sheds light on some of the problems and demands of future study.

Key words: air pollution, forecasting, air quality, artificial intelligence, prediction


 
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Pubmed Style

Sneha P Khedekar, Dr. Sunil B Thakare. AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. JCR. 2020; 7(9): 2675-2681. doi:10.31838/jcr.07.09.432


Web Style

Sneha P Khedekar, Dr. Sunil B Thakare. AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. http://www.jcreview.com/?mno=117582 [Access: April 10, 2021]. doi:10.31838/jcr.07.09.432


AMA (American Medical Association) Style

Sneha P Khedekar, Dr. Sunil B Thakare. AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. JCR. 2020; 7(9): 2675-2681. doi:10.31838/jcr.07.09.432



Vancouver/ICMJE Style

Sneha P Khedekar, Dr. Sunil B Thakare. AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. JCR. (2020), [cited April 10, 2021]; 7(9): 2675-2681. doi:10.31838/jcr.07.09.432



Harvard Style

Sneha P Khedekar, Dr. Sunil B Thakare (2020) AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. JCR, 7 (9), 2675-2681. doi:10.31838/jcr.07.09.432



Turabian Style

Sneha P Khedekar, Dr. Sunil B Thakare. 2020. AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. Journal of Critical Reviews, 7 (9), 2675-2681. doi:10.31838/jcr.07.09.432



Chicago Style

Sneha P Khedekar, Dr. Sunil B Thakare. "AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW." Journal of Critical Reviews 7 (2020), 2675-2681. doi:10.31838/jcr.07.09.432



MLA (The Modern Language Association) Style

Sneha P Khedekar, Dr. Sunil B Thakare. "AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW." Journal of Critical Reviews 7.9 (2020), 2675-2681. Print. doi:10.31838/jcr.07.09.432



APA (American Psychological Association) Style

Sneha P Khedekar, Dr. Sunil B Thakare (2020) AIR QUALITY ASSESSMENT USING ARTIFICIAL INTELLIGENCE APPROACHES: A REVIEW. Journal of Critical Reviews, 7 (9), 2675-2681. doi:10.31838/jcr.07.09.432