Harnessing AI for environmental resilience : mitigating heavy metal pollution and advancing sustainable practices in diverse spheres

As the global community faces unprecedented environmental challenges, the application of artificial intelligence (AI) in environmental studies has become an essential tool for mitigating the impacts of human activity. This paper presents an in-depth analysis of the role of AI in detecting, monitoring, and managing heavy metal pollution across various spheres of development. By employing advanced algorithms, predictive modeling, and machine learning techniques, we showcase the potential of AI in identifying contamination sources, assessing risk levels, and guiding remediation strategies. Furthermore, we explore the integration of AI-driven solutions with sustainable practices in agriculture, industry, and urban planning to reduce the future release of heavy metals into the environment. Finally, we discuss the limitations and future trends in AI applications for environmental studies and emphasize the need for interdisciplinary collaboration to address global environmental challenges holistically.