Artificial intelligence and technology for operational efficiency in retail store

Technology has played a very important role in advancement and speed of working in retail industry. In this paper, an artificial intelligence-based approach to support the retailer learn the shelf space availability/empty space on the shelf and the need to replenish the products is explained. The approach is action oriented and a good guidance for the store employee to perform their duties. The developed solutions involve the following steps: 1) offline - capture images from the shelves and generate a reference table of the various status of the shelf; 2) priorities the shelves to be replenished based on the empty space on the shelf; 3) identify the product that needs to be replenished; 4) compare with count with the inventory for feasibility of replenishment; 5) prepare action table for the employee. The approach implemented on a dataset, provided results of 90% accuracy in product identification and 95% in prioritisation of shelves for replenishment.