PROPOUNDING FIRST ARTIFICIAL INTELLIGENCE APPROACH FOR PREDICTING ROBBERY BEHAVIOR POTENCIAL IN AN INDOOR SECURITY CAMERA

Abstract

In order to foresee potential robbery activity, our study is pioneering a new artificial 
intelligence technology for evaluating data from inside security cameras. The 
proposed method employs artificial intelligence to examine camera video and predict 
potential thief conduct, which is a highly sought-after proactive security measure. 
This approach uses cutting-edge computer vision techniques in conjunction with 
machine learning algorithms to detect suspicious patterns of behaviour. Through 
training on a diverse array of footage from inside security cameras, the algorithm 
learns to distinguish between normal activities and potential robbery behaviours. The 
project aims to enhance safety and security in interior settings by contributing to the 
enhancement of indoor security systems. Its ultimate objective is to provide an 
intelligent and proactive tool for early detection and prevention of criminal activities.