Enhancing Real‑Time Surveillance Video Analysis With AI‑Powered Deep Learning Techniques
Shivani Shingh, Jay Kumar Pandey · 2026
Abstract The evolution of surveillance technology has transformed security and monitoring systems, leveraging artificial intelligence (AI) and deep learning to enhance Real‑Time video analysis. This chapter explores the transition from traditional analog surveillance systems to sophisticated AI‑driven frameworks. We examine the role of deep learning models, including convolutional neural networks (CNNs) for object detection and recurrent neural networks (RNNs) for behavior analysis. Additionally, we discuss challenges such as data privacy, computational requirements, and environmental factors affecting video quality. The chapter concludes by highlighting future advancements in edge computing, sensor fusion, and AI‑driven security systems.