Automatic inventory tracking in brick and mortar store based on sensor data

Abstract

A brick-and-mortar (BAM) store control system uses sensors and wireless transceivers to track customers, merchant representatives, devices, and/or objects within a BAM store area. The system can identify and track product and/or service inventory within the BAM store area and/or in individual's personal inventories, for instance by detecting movements of objects by individuals in sensor data. The system can generate inventory replenishment schedules, for instance based on inventory quantity patterns. The system can provide recommendations to customers and/or merchants, for example recommending products that customers have interacted with. The system can identify individuals and/or objects using a machine learning algorithm, which can learn based on feedback. The system can generate temporary identifiers for unrecognized individuals or objects, which it can merge or convert into long-term identifiers as more information is received. The system can recognize sensitive information based on secure identifiers generated based on the sensitive information.