Introduction
Self-Checkout Lanes have helped improve the convenience of shopping for both consumers and retailers. Consumers can avoid waiting in long lines, and retailers can increase the throughput of checkout lanes without the need of additional staff. Together this means an improved shopping experience for consumers, retailers, and staff.
Despite the convenience for customers and retailers, self-checkout systems are often the largest source of loss caused by shoplifting. Loss prevention at self-checkout lanes relies on equipment which can be inaccurate or frustrate shoppers with false alerts. Staff are often too busy assisting customers to be able to keep a sharp eye out for shoplifters taking advantage of the self-checkout machines.
One company is developing an AI powered solution for loss prevention in self-checkout systems. Utilizing behavioral analysis and object detection, the system uses two cameras—one above the customer to analyze body movements and another pointed at the barcode scan area to confirm items are scanned by the barcode reader—to determine if an item wasn’t scanned. The system can even tell if a shoplifter places an item into their pockets. With edge computing operation, the system can detect shoplifting behaviors in real-time and alert in-store loss prevention staff.
