Queue and Wait Time Prediction

One of the earliest and most widely cited deployments of queue prediction technology occurred at Tesco, the British grocery chain. In 2006, Tesco chief executive Sir Terry Leahy credited thermal imaging queue-sensing cameras, supplied by Irisys, as a key factor in the company's half-year pre-tax profits rising 10%. The system enabled store managers to monitor service levels by customer, by store, and by the minute, with Tesco reporting that a quarter of a million more customers per week no longer had to queue as a result of the deployment. The technology used overhead thermal sensors to count customers approaching checkout areas and predict staffing needs in real time.

In the U.S. grocery sector, Kroger implemented Irisys thermal imaging technology in 2008. Marnette Perry, then senior vice president of retail operations, credited the people-counting devices with helping reduce customer wait times from four minutes to less than 30 seconds. The system analyzed foot traffic patterns to predict checkout demand and trigger staffing adjustments before queues formed. Additional U.S. grocery deployments followed, with Ralphs installing infrared cameras and body heat detectors across nearly all of its supermarkets in 2013, and Hawaii-based Foodland deploying thermal people-counting and checkout management sensors to optimize staffing across its store network in the same year.

More recently, a computer vision queue management pilot conducted by Agmis at one of Central and Eastern Europe's largest retailers demonstrated the next generation of AI-driven queue prediction. Using existing security cameras and deep learning algorithms, the system monitored all manned counters simultaneously and predicted queue formation before lines developed. During the two-month trial, the system prevented 237 queue formation incidents per store per day and reduced cashier idle time by 57.66%, equivalent to reclaiming over 2.5 productive labor-hours per store daily.