Department of Computer Science Engineering (Data Science), ACE Engineering College, Hyderabad, Telangana, India.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(02), 570-579
Article DOI: 10.30574/wjaets.2025.15.2.0600
Received on 26 March 2025; revised on 30 April 2025; accepted on 03 May 2025
In today’s world, safety remains a critical concern, especially in public spaces like schools, offices, and streets. This project presents a smart AI-based surveillance system that uses computer vision to detect weapons in real time and respond immediately. Our system integrates a webcam with the YOLO(You Look Only Once) deep learning model to automatically identify weapons from live video feeds. Upon detection, it activates a buzzer, records video and audio, and sends an emergency email containing the user's live location to nearby authorities and predefined contacts. This immediate response helps in alerting both officials and nearby individuals, enabling faster and more accurate intervention. The goal is to shift from passive surveillance to proactive crime prevention, using intelligent technology to improve public safety and reduce the delay in emergency response.
YOLO; Real-Time Detection; Deep Learning; Surveillance; Crime Prevention; Public Safety
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Ashok Kumar Pasi, Lasya Palarapu, Akshitha Mailaram, Laxmi Prasanna Kanithi and Deekshith Bommana. Real-time crime detection system using yolo. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(02), 570-579. Article DOI: https://doi.org/10.30574/wjaets.2025.15.2.0600.