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Environmental risks have become a primary threat to the ecosystem and human health, and identifying the most influential factors is a crucial issue. Technological advancements have made it possible to identify and detect these factors, most notably …
Environmental risks have become a primary threat to the ecosystem and human health, and identifying the most influential factors is a crucial issue. Technological advancements have made it possible to identify and detect these factors, most notably artificial intelligence (AI), which has played an effective role in analysis, detection, and inference. IoT, sensors, and AI technology are highly effective in environmental monitoring, such as detecting water, air, and soil pollutants. Therefore, this review aims to present and explore the most important recent developments in the use of sensors, AI technologies, and the Internet of Things in monitoring and controlling environmental pollution, while considering the complexities of the prediction process and the dynamic nature of the environment, taking into account the variables of pollution type. However, they also present challenges. Key considerations include understanding and selecting the most appropriate AI models, the ability to adjust and balance model performance, data processing, and the problems associated with their sharing, and finally, the interpretability of results. This study aims to monitor environmental pollution by leveraging artificial intelligence and its technologies, sensors, IoT, the latest trends, and the findings of recent studies
