Adaptive Threat Detection System: Real-Time Anamoly Understanding And Response in CCTV Footage Using Multimodal AI

The growing complexity of security threats necessitates the development of advanced surveillance systems capable of real-time anomaly detection and proactive threat mitigation. Traditional security solutions rely on static, rule-based approaches, leading to high false alarm rates and limited adaptability to evolving environments. This paper presents an Adaptive Threat Detection System (ATDS) that leverages Artificial Intelligence (AI) to analyze CCTV footage and accurately identify suspicious activities. Unlike conventional systems, ATDS employs dynamic AI models that continuously adapt to changing scenarios, minimizing false positives while enhancing situational awareness.The system integrates computer vision for visual anomaly detection, temporal analysis algorithms to interpret activity sequences, and context-aware AI to incorporate environmental factors such as location, time, and event-specific data. This holistic approach allows the system to detect context-sensitive anomalies that traditional methods often overlook. Real-time processing ensures immediate threat recognition, enabling rapid security interventions. Additionally, its adaptive architecture facilitates seamless integration with existing surveillance infrastructures, ensuring scalability and operational efficiency. Preliminary findings demonstrate significant improvements in detecting complex security threats, achieving higher accuracy and faster response times. The system features a user-friendly interface that provides actionable insights, helping security personnel visualize threats and analyze behavioral patterns effectively. Moreover, its ability to generate detailed reports and integrate with centralized security networks enhances overall operational coordination. By embedding adaptive intelligence into surveillance, ATDS establishes a new standard in proactive threat management, offering scalable and robust security solutions tailored to contemporary challenges.