• Geetha Yodham Rajendra
• Deependra Rastogi

Retail shrinkage and loss prevention remain critical challenges that compromise profitability and operational efficiency in modern stores. This study explores the integration of computer vision technologies into smart retail environments as a robust solution to mitigate theft and reduce shrinkage. By leveraging real-time video analysis and deep learning algorithms, the proposed system continuously monitors in‐store activities and identifies anomalous behaviors indicative of potential theft. The system processes data from strategically positioned cameras, extracting features that differentiate between normal customer actions and suspicious activities. Extensive experiments were conducted under varying lighting conditions and customer densities to ensure reliability and adaptability in dynamic retail settings. Results from simulated and live‐store trials indicate a substantial decrease in shrinkage incidents, improved response times from security personnel, and enhanced inventory management accuracy. Moreover, the system provides actionable insights that help retailers optimize store layouts and refine loss prevention protocols. The research also discusses practical implementation challenges such as data privacy, integration with existing infrastructures, and computational resource requirements. Ultimately, this work demonstrates that computer vision‐based theft prevention not only reinforces traditional security measures but also contributes to a more efficient, customer‐friendly retail experience. The findings pave the way for future developments in automated security systems and encourage further exploration of intelligent monitoring solutions in the retail industry. Additionally, the adoption of these systems can lead to long-term cost savings and a stronger security culture among employees, further enhancing customer trust and satisfaction in an increasingly competitive market. These advancements signal a new retail security era.

Computer Vision, Retail Shrinkage, Loss Prevention, Theft Detection, Smart Retail, Deep Learning, Surveillance, Inventory Management, Security Systems

"Shrinkage Reduction and Loss Prevention in Retail : Computer Vision-Based Theft Prevention in Smart Retail Environments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.h606-h619, March-2025, Available :http://www.jetir.org/papers/JETIR2502777.pdf

"Shrinkage Reduction and Loss Prevention in Retail : Computer Vision-Based Theft Prevention in Smart Retail Environments", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. pph606-h619, March-2025, Available at : http://www.jetir.org/papers/JETIR2502777.pdf