Developing a Deep Learning-Based Framework for Real-Time Anomaly Detection and Alerting Mechanism Using Embedded Systems
Vijayalakshmi G. V. Mahesh, Richesh Gaurav, M A Nisarga, Ratnala Mani Deepika, B. R. Raksha · Advances in computational intelligence and robotics book series · 2025
The increase in surveillance and monitoring devices at various locations over the last decades has provided new ways to use the collected data in a variety of useful applications. This includes event management forecasting, live data monitoring, traffic analysis, crowd behavior, home security, public safety and targeted analysis, especially in the areas of anomaly and intrusion detection. Artificial intelligence methods with machine learning and deep learning architectures have emerged as a valuable anomaly detection tool that is highly effective in modern society. This chapter aims to present an approach based on deep learning methods, specially designed to detect anomaly activities through video surveillance cameras for smart city applications to aid law enforcement.