AI‐Driven Environmental Real‐Time Monitoring, and Screening

Artificial intelligence (AI) has emerged as a transformative force in environmental monitoring, enabling real-time data collection, analysis, and interpretation to address pressing ecological challenges. This paper explores the applications of AI-driven technologies in environmental real-time monitoring and screening, focusing on their potential to enhance decision-making processes and improve environmental management practices. By integrating machine learning, remote sensing, and IoT devices, AI facilitates the continuous tracking of environmental parameters such as air quality, water quality, soil health, and biodiversity. The implementation of these technologies leads to more accurate predictions of environmental changes, timely responses to ecological threats, and optimized resource allocation. This study highlights successful case studies, evaluates the challenges of AI integration in environmental monitoring, and discusses future prospects for AI technologies in fostering sustainable environmental practices.