For traditional surveillance architecture, “queuing units” are one of the most challenging objects to accurately identify and consistently track, as individual customers come and go, and queue lines are always flexible.
Vionvision has been working on developing cutting-edge AI algorithms to identify queuing units in a variety of scenarios and provide managers with the ability to identify queuing units from the perspectives of cashier occupancy, checkout lane shapes, prevention of abandonment, and on-site queue fatigue-release methods, as well as provide managers with data-driven adjustment strategies and digital management infographics.
Using Vionvision TrueFlow and ReID technology, wait and service times per queuing shopper/household, length of each checkout lane, and cart abandonment rates can be analyzed.
In real-world scenarios, a "queuing unit" can be hard to identify due to mixture of customers and shopping cart in line, as well as different profiles between family buyers and single buyers. In addition, customers in the queue are likely to leave and return temporarily, or leave with a shopping trolley or basket, abandoning their purchases. Vionvision's queue analysis system takes all into account and accurately analyzes the number of "queue units" in each queue, distinguishes between waiting time and served time, and accurately identifies those who return and those who abandon their purchases.
In the self-checkout areas, where the flexible and varied shape of the queue places requires more intelligent queue analysis system, queue management system is able to automatically identify free-form queues and accurately measure waiting and service times.
Queue length is determined by customer arrival number and checkout efficiency. Vionvision's queue management system is capable of predicting customer arrivals, so that appropriate service capacity can be deployed in advance, improving the quality and stability of the customer experience. By interfacing with manpower scheduling systems, the overall customer queuing experience can be further enhanced.
