Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 14, Issue 3


Published
on


Pages

722-727


DOI

Article

A New Artificial Intelligence Model for Air Quality Prediction and Analysis


Authors

G. Sahithi Affiliation:
Department of CSE, MALLAREDDY ENGINEERING COLLEGE FOR WOMEN(AUTONOMOUS), TELANGANA, India
, G. Akhila Affiliation:
Department of CSE, MALLAREDDY ENGINEERING COLLEGE FOR WOMEN(AUTONOMOUS), TELANGANA, India
, K. Sahasra Affiliation:
Department of CSE, MALLAREDDY ENGINEERING COLLEGE FOR WOMEN(AUTONOMOUS), TELANGANA, India
and G. Manusha Affiliation:
Department of CSE, MALLAREDDY ENGINEERING COLLEGE FOR WOMEN(AUTONOMOUS), TELANGANA, India


Abstract

Traffic and power generation are the main sources of urban air pollution. The idea that outdoor air pollution can cause exacerbations of pre-existing asthma is supported by an evidence base that has been accumulating for several decades, with several studies suggesting a contribution to new-onset asthma as well. In this Series paper, we discuss the effects of particulate matter (PM), gaseous pollutants (ozone, nitrogen dioxide, and sulphur dioxide), and mixed traffic-related air pollution. We focus on clinical studies, both epidemiological and experimental, published in the previous 5 years. From a mechanistic perspective, air pollutants probably cause oxidative injury to the airways, leading to inflammation, remodelling, and increased risk of sensitisation. Although several pollutants have been linked to new-onset asthma, the strength of the evidence is variable. We also discuss clinical implications, policy issues, and research gaps relevant to air pollution and asthma.


Keywords

air pollution, exacerbation's, particulate matter, epidemiological


Citation

Sahithi, G., Akhila, G., Sahasra, K., & Manusha, G. (2023). A new artificial intelligence model for air quality prediction and analysis. Turkish Journal of Computer and Mathematics Education, 14(3), 722–727.

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