A Novel Iot-Enabled Wireless System with Blockchain-Based Security and AI-Enhanced Detection for Hazardous Nuclear and Chemical Waste Management

Abstract

This paper presents the development, implementation, and experimental validation of an advanced IoT-enabled wireless system designed to detect and mitigate hazardous nuclear and chemical wastes. The system integrates blockchain technology to ensure data security and integrity, along with AI, neural networks, and machine learning techniques to enhance detection accuracy and predictive capabilities. Through detailed experimental setups in both nuclear and chemical engineering environments, the study analyzes the system's performance, including detection accuracy, data security, operational efficiency, and predictive analytics. Specific hazardous materials, including plutonium-239, cesium-137, benzene, vinyl chloride, and mercury, are monitored. The integration of AI, neural networks, and machine learning enables the system to predict potential contamination events and optimize sensor deployment dynamically. The results highlight the system's potential to enhance safety in high-risk industrial environments by preventing environmental contamination and mitigating toxic impacts.