A system and method for advanced inventory management using deep neural networks. The system may be disposed in a business establishment or it may be a cloud-based network comprising a one or more databases to store and retrieve including patron data, recipe data, business data, and inventory data, mobile and compute devices, staff and suppliers, one or more gateways for vendors and staff to interface with other third-party business, and an inventory analysis server. Taken together or in part, optimize organizational operations by predicting and optimizing key inventory decisions using artificial intelligence or other computerized methods around inventory management based upon a large amount of variables associated with the enterprise.

A system and method for a restaurant-as-a-service system, comprising one or more database(s), a cluster manager, and a platform which provides restaurants automated, multiple-domain spanning, intelligent business predictions and optimizations leveraging modular, highly integrable microservices which perform various domain-specific functions and tasks to enhance restaurant operations and patron experience. The cluster manager may intercept data requests and algorithmically forward requests to the appropriate microservice operating on an available cluster of computing devices.

A cross-entity and cross-retailer platform is provided that captures transaction and item return data, indexes, and stores the data in a cloud-accessible data store. A service is provided that custom processes retailer and entity-defined workflows based on purchase transactions and return transactions using the data store. The entities may comprise manufacturers of an item, a supplier of the item, a distributor of the item, and a Consumer Packaging Goods (CPG) company of the item. In an embodiment, a given entity workflow causes the service on a given return to calculate a custom aggregation of returns for a given item or a given set of items across different retailers within a given geographical region for a select period of time and provide selective data about the returns automatically to an inventory system and/or a schedule/delivery system of the given entity through an Application Programming Interface (API).

According to one embodiment, a code reader includes an interface, a scanner, and a processor. The interface transmits and receives data to and from an external device. The scanner reads a code from an item. The processor extracts a portion of code information obtained from the code read by the scanner and transmits the portion of the code information to the external device through the interface.

Systems and methods are provided for retail environments. In one implementation, a non transitory computer-readable medium may include instructions that when executed by a processor cause the processor to perform a method. The method may include determining product availability data indicative of an availability of one or more products on at least one retail shelf in a retail store; using the product availability data to generate a synthetic visual representation of the one or more products on the at least one retail shelf; presenting the synthetic visual representation on a display; receiving from a user an input indicative of a selection of at least a portion of the synthetic visual representation; and in response to receiving the input, presenting on the display an actual image corresponding to the selected at least a portion of the synthetic visual representation, wherein the actual image was acquired with an image sensor.

A registration apparatus includes a reader, an imaging device, and a processor. The reader is configured to read commodity identification information for identifying a commodity from a code symbol attached to the commodity and to read benefit information regarding a benefit of a commodity from a benefit symbol attached to the commodity. The imaging device is configured to image an imaging area including a readable area of the reader. The processor is configured to extract identification data corresponding to the commodity identification information, acquire image data obtained by the imaging device, determine whether a commodity in the acquired image data is the same as the commodity that is identified by the commodity identification information, and register transaction information regarding transaction of the commodity identified by the commodity identification information.

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.

Provided herein is a methods, apparatus, and system for the configuration of customizable trays for the storage and dispensing of articles. Methods may include: receiving an indication of a plurality of articles to be stored in a tray; determining a plurality of bins corresponding to the plurality of articles; generating a layout of the bins on the tray; identifying locations of the plurality of articles within the bins on the tray; and causing the tray to be configured according to the layout of the plurality of bins on the tray. Methods may include: receiving an indication of an article to be loaded into a bin of the plurality of bins; receiving a unique identifier of the bin of the plurality of bins into which the article is loaded; and storing, in a memory, a correlation between the unique identifier of the bin and the article loaded into the bin.

Systems and methods for generating visual disposition data and identifying causal event are disclosed. An example system may include an electronic mobile device to generate visual disposition data from a plurality of items in a store. The example system may further include a server to generate processed disposition data via image processing the visual disposition data and determine disposition analysis data for an item of sale from the processed disposition data. The server may further transmit the disposition analysis data, where the disposition analysis data includes an indication of a causal event for the disposal of the item of sale.

A system and method for applications of computer vision in linking users with virtual data that can include detecting digital interaction state of a plurality of subjects in an environment using at least one sensor-based monitoring system; detecting a contextual organization of subjects relative to an operator station; at the operator station, augmenting the user interface based on the contextual organization of subjects which comprises of at least: presenting a set of subject indicators in the user interface with the subject indicators arranged in response to contextual organization, and in response to received user interaction with at least one selected subject indicator, accessing the digital interaction state of the subject associated the at least one subject indicator.