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September 10, 2025International Journal for Research in Applied Science and Engineering TechnologyOpen Access

A Survey on Air Pollution Prediction Using Machine Learning Techniques

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Authors

MUMrs. P. UmasanthiyaMEMarrynal S. Eastaff

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Overview

Review evaluates machine learning models for predicting air pollution levels, highlighting challenges and innovations.

Key Points

  • Accurate prediction of air pollution levels is vital for safeguarding ecosystems and health, and this review explores various models.
  • The research analyses 32 publications, examining machine learning algorithms, hybrid approaches, and statistical models for forecasting pollution.
  • Categorization of prediction models based on methodologies and data requirements highlights strengths and limitations for effective air quality management.
  • Integration of IoT sensors and deep learning techniques may enhance prediction accuracy while addressing existing challenges in air quality forecasting.

Cite This Study

Umasanthiya et al. (2025) studied this question.

synapsesocial.com/papers/68c1dda254b1d3bfb60fc48bhttps://doi.org/10.22214/ijraset.2025.73888
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