Advancements in Process Control Methodologies for CBRN Decontamination Techniques: A Review

Chemical, biological, radiological, and nuclear (CBRN) incidents pose significant risks to public safety and require effective decontamination techniques to mitigate their impact. Process control methodologies play a crucial role in ensuring the successful execution of decontamination operations. This review paper aims to explore the current state of process control methodologies in CBRN decontamination and highlight the potential for integrating new technologies to enhance their effectiveness. By examining existing literature, this review identifies key areas where advancements can be made, including real-time monitoring, automation, data analytics, and intelligent decision-making systems. Real-time monitoring technologies, such as advanced sensors and surveillance systems, can provide critical data for timely and informed responses. Automation in decontamination processes can reduce human error and increase operational efficiency. Data analytics enables the processing of large volumes of information to predict and respond to CBRN threats more effectively. Intelligent decision-making systems, including artificial intelligence and machine learning, can optimize decontamination strategies based on real-time data. Through the incorporation of these technologies, the process control methodologies can be transformed to enable faster, more efficient, and safer CBRN decontamination operations. This paper emphasizes the need for ongoing research and development in these areas to improve preparedness and response capabilities for CBRN incidents, ultimately enhancing public safety and minimizing the impact of such events.