Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 106640 10.2205/2025ES001070 aeioyx Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ” Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ” Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ” Artificial Intelligence Models as a Tool for Environmental Monitoring: Review and Analysis Artificial Intelligence Models as a Tool for Environmental Monitoring: Review and Analysis https://orcid.org/0000-0003-4181-8776 Довгаль Виталий Анатольевич Dovgal Vitaly Anatolyevich https://orcid.org/0000-0002-3182-0672 Куижева Саида Казбековна Kuizheva S. K. Майкопский государственный технологический университет Майкоп Россия Maykop State Technological University, Maykop, Russia Maykop Russian Federation Майкопский государственный технологический университет Майкоп Россия Maykop State Technological University, Maykop, Russia Maykop Russian Federation 10 12 2025 10 12 2025 25 6 ES6001 10 09 2025 10 11 2025 https://rjes.ru/en/nauka/article/106640/view

The application of artificial intelligence (AI) for environmental monitoring enables accurate forecasts of natural disasters, identification of pollution sources, and comprehensive monitoring of air and water quality. This article provides an overview of the challenges associated with monitoring using traditional methods, as well as the potential for implementing AI-based solutions. The article discusses several models that apply artificial intelligence in the implementation of environmental monitoring, demonstrating case studies of environmental research. However, realizing the full potential of AI faces obstacles such as the lack of specialized AI experts in the environmental sector and the problem of data access, control and privacy. The above challenges are more acute in regions with developing technological infrastructure.

The application of artificial intelligence (AI) for environmental monitoring enables accurate forecasts of natural disasters, identification of pollution sources, and comprehensive monitoring of air and water quality. This article provides an overview of the challenges associated with monitoring using traditional methods, as well as the potential for implementing AI-based solutions. The article discusses several models that apply artificial intelligence in the implementation of environmental monitoring, demonstrating case studies of environmental research. However, realizing the full potential of AI faces obstacles such as the lack of specialized AI experts in the environmental sector and the problem of data access, control and privacy. The above challenges are more acute in regions with developing technological infrastructure.

 Artificial intelligence environmental monitoring pollution detection disaster forecasting air and water quality Artificial intelligence environmental monitoring pollution detection disaster forecasting air and water quality No. No.

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