Real Time Crime Detection Using Deep Learning Algorithm

P. Sivakumar, V Jayabalaguru., R Ramsugumar., S Kalaisriram.

20212021 International Conference on System, Computation, Automation and Networking (ICSCAN)34 citationsDOI

Abstract

The Crime Rate and number of Criminals are increasing day by day, so there is great concern about the security issues, so to prevent and identify the crime before it occurs is the primary goal of the police officials. With the help of Recent Technologies, especially CCTV is normally deployed in every private and public area to control crime but it needs human supervision to monitor. It's hard for a human to monitor many screens at the same time. It leads to many errors. To overcome these problems, we proposed Real-Time Crime Detection Technique using a Deep Learning Algorithm which monitors real-time videos and alerts the nearby Cybercrime admin about the occurrence of crime with current location. In this paper, We present YOLO as our object detection algorithm. Our architecture is extremely fast and process image in real-time at 45 frames per second.

Topics & Concepts

CybercrimeComputer sciencePublic securityProcess (computing)Object detectionArchitectureDeep learningCrime controlComputer securityArtificial intelligenceFrame rateCrime preventionReal-time computingPattern recognition (psychology)CriminologyWorld Wide WebVisual artsOperating systemCriminal justiceArtThe InternetSociologyVideo Surveillance and Tracking MethodsAnomaly Detection Techniques and ApplicationsAdvanced Neural Network Applications