Emergency Preparedness and Response

Chaima Jendoubi^*

• Ontario Tech University, Oshawa, Canada

Nuclear energy is considered one of the safest sources of energy in the world, however there is a low probability of occurrence of a nuclear accident that might trigger a nuclear emergency. As of December 2023, there are 413 operating nuclear power plants in 31 different countries, and although the design of these nuclear power plants is based upon the concepts of Defence in Depth with very conservative assumptions, the hazard from natural disaster, human error and non-vigilant actions might results in nuclear emergency. Since the last major nuclearaccident Fukushima Daichi in 2011, many researchers have highlighted the need for more advanced and automated system to support the emergency preparedness and response in optimizing the protective action strategies. In this study we introduce the concept of applying artificial intelligence to enhance the readiness and the response capability during nuclear emergency. Through the predictability and computational features of AI models and machine learning techniques, the EPR systems can be enhanced by improving the hazard assessment, optimizing the dose projections models, enhancing the protective actions strategies and improving the decision-making process. However, this application also presents challenges such as data reliability, cybersecurity and regulatory compliance. The results of this study highlight the significance of applying AI in EPR and the need for further research on this application with a particular focus on addressing these challenges to ensure safe implementation.