StealthWatch: Artificial Intelligence based Shoplifting Detection [Retail Theft]
Thirunavukkarasu Kanimozhi, Adhitya Raj Rajamurugan, S. N., D P Harihareshwar, Vanaj Kalyan S R · 2024
Retail industries face significant challenges in preventing shoplifting, which leads to substantial financial losses. ‘Stealth Watch’ is a comprehensive solution that leverages advanced computer vision techniques to combat this issue. Utilizing the power of YOLO (You Only Look Once) and OpenCV (Open Source Computer Vision Library), the system monitors live video footage in real-time to detect suspicious activities. When a potential shoplifting event is identified, ‘Stealth Watch’ sends immediate alerts to connected systems and triggers an automatic call to the store's owner or manager, ensuring prompt awareness and action. The system also incorporates facial recognition technology to log shoplifters' identities, storing this information along with the date and time of the incident in a database for future reference. ‘Stealth Watch’ exemplifies how cutting-edge technology can enhance security in retail environments. By automating the detection and alert process, this system reduces the need for constant human monitoring while increasing the speed and accuracy of responses to theft. Its ability to log repeat offenders also serves as a deterrent, making it a valuable tool for store owners and security personnel. In conclusion, ‘Stealth Watch’ is a recent advancement in the use of technology to address the persistent challenges of retail security.