The Role of Artificial Intelligence in Environmental Radioactivity Monitoring

Abstract

Effective radioactive monitoring is essential for safeguarding human health and the environment. Traditional detection methods, while reliable, often lack the speed, adaptability, and predictive capability required in fast-moving or high-risk scenarios. Recent developments in artificial intelligence (AI)—combined with uncrewed aerial vehicles (UAVs), sensor networks, and Internet-of-Things (IoT) systems—enable real-time, autonomous, and predictive radiation monitoring [11], [12], [13]. By processing complex data streams, AI can detect anomalies, forecast contamination spread, and guide timely decision-making. This paper reviews how integrating AI with advanced sensing technologies transforms environmental radioactivity monitoring, improving accuracy, safety, and efficiency. It also outlines strategies for predictive analytics, automated responses, and optimized decontamination—creating safer and more resilient infrastructures.