A Novel Methodology Utilizing Modern CCTV Cameras and Software as a Service Model for Crime Detection and Prediction

doi:10.23940/ijpe.25.02.p6.112121

Abstract

Abstract: This research introduces a new way to detect and predict crime using modern CCTV cameras. It uses a “software as a service” model to make crime monitoring and analysis more affordable. The system works with both old and new cameras, even those without GPS, by using latitude and longitude mapping. This means it can detect crimes in areas with poor internet connection. The method ensures data remains private and secure, which is important due to the sensitive nature of crime information. The paper also explains how to install the software on different types of cameras. Special software for police officers provides instant crime updates, helping them respond faster and more effectively. The study shows that analyzing crime data can identify high-risk areas, allowing authorities to prevent crimes before they happen. Overall, this approach is promising for helping police and investigators reduce crime and improve public safety. It also opens up new opportunities for research in crime detection technology. The study explores various deep learning methods for image recognition and suggests a real-time alert system for law enforcement, using tools like TensorFlow, Google Maps, and Firebase. It highlights the importance of involving people, using smart video analysis, and advancing technologies like computer vision, federated learning, and edge computing to improve crime detection.

Key words: CCTV camera, facial recognition, deep learning, convolutional neural network, violence detection, crime anticipation

Pancham Singh, Updesh Kumar Jaiswal, Eshank Jain, Nikhil Kumar, and Vimlesh Mishra. A Novel Methodology Utilizing Modern CCTV Cameras and Software as a Service Model for Crime Detection and Prediction [J]. Int J Performability Eng, 2025, 21(2): 112-121.

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