AI Assistant with Predictive Decision-Making for Enhancing Security at Indonesian Nuclear Facilities

Protecting nuclear facilities requires swift and accurate decision-making, especially in the face of increasingly sophisticated threats. This study explores the design of an AI Assistant to enhance security operations in Indonesian nuclear facilities by integrating real-time CCTV surveillance, advanced monitoring for cyber threats, and predictive learning algorithms to assess and mitigate risks. During emergencies, whether physical breaches or cyber intrusions, the system analyzes the situation instantly and provides specific instructions based on personnel location and role. This personalized approach significantly reduces response times and ensures a coordinated, effective reaction to threats. Using a literature review approach, this research develops a conceptual model of the AI Assistant. By seamlessly combining physical and cybersecurity measures, the AI Assistant not only enhances decision-making but also strengthens the overall security framework of nuclear facilities. With its ability to minimize human error, accelerate critical actions, and predict potential threats, this innovative system is a game-changer in safeguarding high-risk infrastructure, offering a smarter, faster, and more reliable approach to nuclear security. While the study does not include implementation or coding, the conceptual framework serves as a foundation for future development, offering a strategic approach to modernizing nuclear security through AI-driven intelligence.