Internet of Things and Artificial Intelligence-Based Sensing Systems for Environmental Monitoring and Risk Assessment: A Systematic Review

Abstract

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.