Various embodiments of a system, methods, server, client, and graphical user interface to displaying on map interface, place(s) associated with particular location of place wherein places including current, nearest, nearby, category specific, searched and any combination thereof for enabling user to select or identify specific place or place of business on map and view associated standardized and integrated payment user interface with/in said selected or identified place or place icon or place user interface which enable user to make entered or inputted or selected or displayed or pre-set or default or pushed particular amount of payment from user's account to said selected or identified place associated automatically identified merchant's account, without the user having to enter the account information related to merchant.

An item level security system is provided that uses dynamic security settings to optimize the competing requirements for high security and transaction throughput. Customer metrics such as customer traffic volume and the number and type of items purchased change over the course of a day and are further influenced by the day of the week and by holidays and certain vacation schedules for local schools and employers. The invention provides dynamic security settings for the item level security system that address the changing customer metrics.

This disclosure is directed to techniques in which a first user in an environment scans visual indicia associated with an item, such as a barcode, before handing the item to a second user. One or more computing devices may receive an indication of the scan, retrieve image data of the interaction from a camera within the environment, identify the user that received the item, and update a virtual cart associated with the second user to indicate addition of the item.

A controller using image processing to identify produce is disclosed herein. The controller may include one or more memories and one or more processors communicatively coupled to the one or more memories. In some implementations, a controller may receive a trigger associated with presence of an item at a product processing zone. The controller may capture, via an imager, an image representing the item. Accordingly, the controller may apply a first convolutional neural network (CNN) to the image to determine a bounding box associated with the item. The controller may determine that the item within the bounding box satisfies an occlusion threshold and may apply a second CNN to the image to determine a query image representation. Accordingly, the controller may receive, from a database, an indication of one or more candidate items based on the query image representation and indicate, via a user interface, the candidate item(s).

Technologies are shown for automatically registering items in an automated physical shopping cart involving receiving image data for items in the cart, detecting a change in a weight of items in the cart and, determining whether a correlated item was identified in the image data. If no correlated item was identified, a message is displayed indicating that no correlated item was detected and a user can be prompted. A user device may be used to scan items and display messages for the cart. Items may be scanned using image recognition to determine item information. An item weight may be determined based on the change in the weight of items in the cart and priced accordingly to weight. A notification for an item in the cart may be provided to an inventory or a shopping list application indicating that the correlated item was added to the cart.

In a restaurant having a customer-facing food service counter, a video camera is positioned to produce video of an area that includes the food service counter. The video is analyzed to determine the ingredients that are used to prepare each of multiple customer meals. This information may be used to recommend a modified ingredient layout of the food service counter, where the modified ingredient layout is formulated so as to improve serving efficiency or customer convenience.

In one embodiment, a log-in control apparatus has a processor which controls an operation for log-in to an information terminal moving along with a carrier for carrying a commodity to be purchased. The processor detects a state in which the commodity is placed on the carrier, in cooperation with a sensor attached to the carrier. The processor detects the operation for log-in to the information terminal, in cooperation with an input device included in the information terminal. When the processor detects the operation for log-in, in a case in which the processor detects the state in which the commodity is placed on the carrier, the processor judges that the operation for log-in is ineffective.

The present disclosure discloses a method and a system for identifying goods of intelligent shopping cart. The method comprises: reading bar code information of a to-be-purchased goods and obtaining corresponding prestored goods information; continuously detecting and obtaining a total goods weight m.sub.n+1 in the shopping cart, and comparing the total goods weight m.sub.n+1 with a total goods weight m.sub.n acquired after a previous purchasing action is completed, to obtain a variation m.sub.Δ of the total goods weight. According to the method of the present disclosure, when a customer puts a goods in the shopping cart in the shopping course, the correct goods is automatically identified and recorded in a shopping list, then the customer can directly settle the account after completing the shopping, accordingly a lot of time for the customers to wait for the settlement is saved.

A vending device has at least one display area and an evaluator. The display area is formed by a rigid body, and has at least two, spatially-separated product areas, the rigid body of the display area being held by force transmission areas of at least two weighing cells. The evaluator is configured to, at periodic intervals or when a total weight detected by the at least two weighing cells changes: determine new coordinates of a center of gravity from data of the weighing cells, and transmit the new coordinates to a controller. The controller is configured to: determine a product area within the display area based upon changes in the coordinates of the center of gravity, determine, from the change in a total weight, the weight of goods removed from or added to the determined product area, and update an inventory, stored in a memory, for the product.

Methods for accurate object tracking are disclosed herein. An example the method includes receiving, from a first optical imaging assembly having a first field of view (FOV), a first image captured over the first FOV and based on a decode of an indicia associated with an object of interest, identifying the object of interest within the first image. The method further includes determining a location of the object of interest within the first image and mapping the location of the object of interest within the first image to a predicted location of the object of interest within a second image, the second image being received from a second optical imaging assembly having a second FOV and the second image being captured over the second FOV.