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Air quality degradation due to pollution is a pressing global issue impacting public health and environmental sustainability. Traditional monitoring methods often struggle to provide timely and precise data necessary for effective intervention. In recent years, artificial intelligence (AI) has emerged as a transformative tool in the field of air quality management. AI models leverage advanced algorithms and large-scale data analytics to enhance the accuracy, speed, and predictive capabilities of air quality monitoring systems. This abstract explores the role of AI in monitoring air quality, highlighting its ability to identify pollution sources, predict pollutant levels, and facilitate data-driven decision-making.

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Artificial Intelligence for Monitoring and Forecasting Air Quality

  • 章节

  • 发表日期：

    2026年

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  • Monika Yadav,
  • Pragya Pathak,
  • Rituraj Kashyap

摘要

Air quality degradation due to pollution is a pressing global issue impacting public health and environmental sustainability. Traditional monitoring methods often struggle to provide timely and precise data necessary for effective intervention. In recent years, artificial intelligence (AI) has emerged as a transformative tool in the field of air quality management. AI models leverage advanced algorithms and large-scale data analytics to enhance the accuracy, speed, and predictive capabilities of air quality monitoring systems. This abstract explores the role of AI in monitoring air quality, highlighting its ability to identify pollution sources, predict pollutant levels, and facilitate data-driven decision-making.