International Journal of Advanced Research in Computer and Communication Engineering

Abstract: The growing incidence of street crimes such as theft, robbery, assault, harassment, and illegal weapon possession has highlighted the urgent need for real-time surveillance and rapid response systems. This paper proposes a mobile-based crime detection framework that transforms everyday smartphones into intelligent CCTV devices capable of identifying suspicious activity. Leveraging deep learning techniques, the system detects violent behavior, identifies weapons (e.g., knives and firearms), and performs facial recognition to detect known suspects. Upon threat detection, alerts are sent instantly to authorities along with supporting evidence such as images, timestamps, and location. The proposed system offers a scalable, affordable, and effec- tive solution for urban surveillance—especially in areas lacking traditional CCTV infrastructure—thus enabling quicker law enforcement response and contributing to safer, smarter cities.

Keywords: Crime Detection, Mobile Surveillance, Weapon Detection, Violence Recognition, Real-Time Alert System.

Downloads: | DOI: 10.17148/IJARCCE.2025.141053