Security Framework for Enhanced Surveillance Monitoring in Banking Systems with Behavioural Pattern Identification Using Machine Learning

Robberies, altercations, and various atypical incidents are increasingly prevalent in banking institutions. In response to these challenges, numerous video surveillance systems have been implemented; some relying on human oversight while others utilize artificial intelligence. Our objective is to create a robust surveillance system that leverages machine learning to identify anomalous behaviors and trigger alerts. Video surveillance entails the observation of specific behaviors that warrant attention, as well as the monitoring of scenes that deviate from the norm. This process involves pinpointing particular locations with a heightened likelihood of unusual activities, allowing for targeted monitoring by surveillance cameras.