A method of auxiliary data capture control includes: storing, at a data capture device, (i) detection criteria corresponding to events having respective event identifiers; and (ii) a registration indicator associated with at least one of the event identifiers; controlling a primary data capture sensor to obtain primary captured data; in response to detecting, based on the primary captured data, that the detection criteria are satisfied for a detected one of the event identifiers, determining whether the registration indicator is associated with the detected event identifier; and when the registration indicator is associated with the detected event identifier, controlling an auxiliary data capture sensor to obtain auxiliary captured data.

A method for tracking non-homogeneous products on a shelf comprises monitoring weight measurement data points corresponding to the weight of the shelf and the products arranged thereupon, determining a set of weight-event parameters of a weight event, such as product identification and an action taken with respect to the product, and at least one of recording information about the results and displaying information about the results. A system for tracking non-homogeneous products on a shelf comprises processors for carrying out stored program instructions for carrying out the steps of the method.

A self-checkout system for controlling an exit of a checkout area (110) is provided. The system comprises a sensor arrangement (120) comprising at least one sensor (140), wherein the sensor arrangement (120) is configured to track, by the at least one sensor (140), a person being inside the checkout area (110), receive a payment signal confirming a successful payment by a person (1), receive an exit detection signal, from the at least one sensor (140) representing that a person (1) is at a predetermined distance from the exit in the checkout area (110), and determine if the exit detection signal and the payment signal correspond to the same person (1), and if so transmit an opening signal to said exit so that said person (1) is allowed to exit the area (110).

A total property security system may be implemented to conduct security and surveillance operations. The system includes security operations centers that are connected to one or more sensors and vehicles for collecting and transmitting surveillance data to a database hosted on cloud services. The collected surveillance data is analyzed in order to automatically deploy security measures and/or recommend courses of action using a rules engine that can be configured to client-specific or user-specific security needs. The cloud services can provide a set of application program interface services that can act on the surveillance operations center. Sensor fusion data and other surveillance data can be also transmitted to vetted monitoring service providers on a subscription basis to provide physical security services to the area within the property perimeter. During the subscription period, the selected monitoring service providers can obtain time-based encryption token for accessing surveillance data.

A total property security system may be implemented to conduct security and surveillance operations. The system includes security operations centers that are connected to one or more sensors and vehicles for collecting and transmitting surveillance data to a database hosted on cloud services. The collected surveillance data is analyzed in order to automatically deploy security measures and/or recommend courses of action using a rules engine that can be configured to client-specific or user-specific security needs. The cloud services can provide a set of application program interface services that can act on the surveillance operations center. Sensor fusion data and other surveillance data can be also transmitted to vetted monitoring service providers on a subscription basis to provide physical security services to the area within the property perimeter. During the subscription period, the selected monitoring service providers can obtain time-based encryption token for accessing surveillance data.

Disclosed herein relates to a self-checkout anti-theft vehicle system, comprising: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise.

Aspects of the present disclosure include methods, systems, and non-transitory computer readable media that perform the steps of receiving a visual code identifier associated with a transaction of one or more transaction merchandises, receiving a radio frequency identification (RFID) identifier associated with the transaction, analyzing the image, determining at least one of one or more detected merchandises, a number of the one or more detected merchandises, and a price of the one or more detected merchandises based on information in the RFID identifier and the analyzed image, determining a merchandise discrepancy, a number discrepancy, or a price discrepancy, and transmitting, in response to determining the at least one of the merchandise discrepancy, the number discrepancy, or the price discrepancy, an alert.

The present disclosure is directed to systems and methods for generating investigations of user behavior. In an example embodiment, the system includes a video camera configured to capture video of user activity, a video analytic module to perform real-time video processing of the captured video to generate non-video data from video, and a computer configured to receive the video and the non-video data from the video camera. The computer includes a video analytics module configured to analyze one of video and non-video data to identify occurrences of particular user behavior, and an investigation generation module configured to generate an investigation containing at least one video sequence of the particular user behavior. In some embodiments, the investigation is generated in near real time. The particular user behavior may be defined as an action, an inaction, a movement, a plurality of event occurrences, a temporal event and/or an externally-generated event.

An electronic device is disclosed. The electronic device includes a memory, a camera module, a communications module, and a processor that is configured to: receive, from the camera module, image data associated with a machine-readable optical label, the optical label encoding transaction details of a transfer of data to a recipient account, wherein the transaction details do not indicate an identity of the recipient account; receive a user input indicating authorization to initiate a transfer of data, via a protected resource, from an account associated with the user to the recipient account; and in response to receiving the user input, generate a request for initiating the transfer of data based on the transaction details, the request including an access token for use in authenticating the user on requests to access the protected resource.

Decentralized cameras perform video tracking on captured video. The cameras produce metadata representing tracking of objects from the captured video. The metadata is passed between the cameras as the object moves within the captured video. Final metadata from at least one of the cameras is sent to a server, the server processes the final metadata to produce a summary of the object tracking and process one or more automated actions based on the summary.