Automation of the buying and selling process
One of the tasks set by the artificial intelligence developers of our association in the retail sector is to maximise automation of the buying and selling process. The request for such developments was formed by large retail chains, based on large profit margins due to the reluctance of buyers to lose a lot of time in queues. The complexity of such operations in shops without cash registers is linked to the need to track multiple items at the same time and to correctly generate the final value of the goods chosen by the customer.
Specialists from the association involved in the development of these systems have identified a number of problems. These include the transfer of goods by customers to the wrong places from which they were taken. This problem is particularly evident when shop visitors come with children. This alone makes it impossible to use sensors on racks and shelves to record the quantity of a particular product. Thus, in order to identify the goods taken from their places, a comprehensive algorithm for tracking them has been developed, with conditional marking of the position “on месте\ not in place”, combined with the definition of the end customer.
Amazon, a renowned global retail giant, became interested in such technologies, having previously purchased the supermarket chain Whole Foods Market. After a long test period, the company opens its first retail shop in Seattle, which operates without cash registers. The decision to open the shop for a wide customer, not just for Amazon employees, was made after the problem of identifying visitors with similar sets and clothing had been resolved.
Pattern recognition and identification systems with artificial intelligence in general and trainable neural systems in particular came to the aid of this issue. The specialists of our association have been working in this field for many years now, seeing its application in virtually every aspect of human life, starting with shops without sellers, passenger control systems in public transport and ending with global video surveillance in the largest cities of the world.