Queue Time Estimation in Checkout Counters Using Computer Vision and Deep Neural Network

Abstract

Abstract In this busy world, everyone wants to make decisions that are more efficient and save their time and not cause/ incur them loss. Sometimes they even get skeptical about making the decision. A similar situation arises when we are required to decide which queue, we should join for billing of the items during the weekend rush in a posh supermarket. To crack this problem, this paper recommends using Computer Vision and Deep Learning Algorithms to estimate the time closely, a customer will take to reach the counter if they join a particular queue. The algorithm will estimate the number of items present in the trolley or the basket and the number of such trolleys in the queue. The next thing the program will measure is the employee’s efficiency who is present in the checkout/billing counter in terms of scanning the items, accepting the payment, and handing over the bill. This will help the customers to make better decisions and save time; it will also make the supermarket look less crowded and use all the counters/resources effectively.