Video surveillance systems, which are now common in cities and workplaces, present a valuable opportunity to predict and prevent harmful incidents before they occur. This project seeks to create advanced technologies capable of analyzing video streams in real time to anticipate potential anomalies with high accuracy. When such events are predicted, the system can initiate preventive measures, such as alerting users or triggering automated interventions—like activating a car's brakes or stopping an escalator. Importantly, the system will also provide detailed explanations, enabling users to understand why their actions or environment were adjusted. By leveraging cutting-edge techniques to identify patterns that precede abnormal events and generate visual or text-based explanations, this project has the potential to transform public safety and operational efficiency. For example, in intelligent traffic systems, it could help reduce pedestrian accidents and fatalities. In warehouses, it could prevent losses caused by equipment mishaps. In air traffic control, it could serve as a critical safeguard to ensure safe and orderly flight operations. By enhancing safety, reducing risk, and supporting human decision-making, this work addresses a critical need and aligns with national priorities to promote prosperity and welfare. While significant advancements have been made in video processing through artificial intelligence (AI), the task of anticipating video anomalies remains larg