Abstract: A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.

Abstract: A system for identifying a group of consumers and associating a first purchase with the group that includes a purchase terminal at which the first purchase is made by a first consumer in the group of consumers; an RF tag having identification information and configured to move in unison with the first consumer; a first RF antenna configured to record a location of the RF tag via reception of the identification information from the RF tag; at least one camera configured to collected video data of the group of consumers within an entrance/exit zone; and a computer processor in communication with the purchase terminal, the RF antenna, and the at least one camera.

Abstract: A method of product detection includes receiving, at a product detector from a product source, a first annotation package for a first product and a second annotation package for a second product. An artificial intelligence model is trained to detect the first product based on the first annotation package and the second product based on the second annotation package. The artificial intelligence model is implemented on the product detector. At the product detector, the first product is categorized into a first category of products and the second product is categorized into a second category of products. A subscription is received from a retailer to one of: the first category of products; the second category of products; and the first category and the second category of products. An image is received at the product detector from the retailer. The first product is detected in the image by the artificial intelligence model.

Abstract: A system for collecting demographic information and associating the demographic information with a purchase by a consumer includes an RF tag having identification information associated with the purchase by the consumer and configured to move in unison with the consumer, a first RF antenna configured to record a location of the RF tag via reception of the identification information from the RF tag, a camera configured to collected video data including the consumer, and a computer processor configured to receive location information and the identification information of the RF tag from the first RF antenna, receive information regarding the purchase and associate the RF tag with the information regarding the purchase, and receive video data from the camera. The computer processor can be configured to determine demographic information of the consumer from the video data and associate the demographic information with the information regarding the purchase.

Abstract: A method of obtaining images and data to train an AI model for product detection includes generating, with an image collection system at a first product source, a first annotation package including one or more images of and data about a first product. The first product is placed in a first enclosure located at the first product source. A process for obtaining the one or more images of the first product is initiated in the first enclosure. The one or more images of the first product is obtained with one or more cameras positioned in the first enclosure. The one or more images of the first product is provided to an edge compute device. Data about the first product is input, using an input device, into the edge compute device. An annotation package for the first product is created that includes the one or more images and the data.

Abstract: Apparatus and associated methods relate to automating building of a software solution that is cooperatively performed. A broadcasting computing entity selects a functional operation from a set of one or more functional operations associated with the software solution and then broadcasts a request to perform the functional operation selected. Each of a plurality of listening computing entities connected to the network receives the request to perform the functional operation and determines capability of performing the functional operation. A capable one of the plurality of listening computing entities that determines itself capable of performing the functional operation transmits a response to the request received indicating capability of performing the functional operation and performs the functional operation, thereby generating the output of the functional operation, which is transmitted to the broadcasting computing entity.

Abstract: A build of a software solution that is cooperatively performed is automated. A broadcasting computing entity selects a selected set of functional operations from one or more sets of functional operations associated with the software solution and then broadcasts a request to perform each of the functional operations in the selected set. Each of a plurality of listening computing entities connected to the network receives the request and determines capability of performing each of the functional operations in the selected set. After determining itself capable, a capable one of the plurality of listening computing entities transmits a response to the request indicating such capability, and then performs each of the functional operations in the selected set, thereby generating and transmitting to the broadcasting computing entity the output of the selected set of functional operations. The broadcasting computing entity then performs an action using the output of the functional operation received.

Abstract: A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.

Abstract: A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.

Abstract: A method of improving a main output of a main AI model [language will be added when claims are finalized]

Abstract: A method of scheduled modifications of preprocessing of incoming video data of at least one region of interest from a camera collecting video data having a first field of view includes receiving incoming video data from the camera and preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file. The preprocessing includes formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view.

Abstract: A method of improving a main output of a main processing application processing first video data includes analyzing incoming video data via a first processing pipeline and analyzing incoming video data via a second processing pipeline. The second processing pipeline includes identifying, by a parameter optimization module, first test preprocessing parameters; preprocessing the incoming video data according to the first test preprocessing parameters, wherein the first test preprocessing includes formatting the incoming video data to create first test video data; processing the first test video data by a test processing application to determine a first test output that is indicative of a first test inference dependent upon the first test video data; and comparing the first test output and the main output to a baseline criterion.

Abstract: A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.

Abstract: A method of processing first video data from incoming video data includes receiving the incoming video data; preprocessing the incoming video data, by a first computer processor, according to preprocessing parameters, wherein the preprocessing parameters include formatting the incoming video data to create first video data; publishing the first video data to an endpoint; subscribing, by a second computer processor, to the endpoint; and processing, by a second computer processor, the first video data to determine at least one output that is indicative of a first inference dependent upon the first video data. The preprocessing parameters that format the incoming video data to create the first video data are dependent upon the processing to be performed on the first video data.

Abstract: A method of processing first video data of a region of interest from incoming video data includes receiving, by a computer processor, the first video data that is preprocessed according to preprocessing parameters defined within a runtime configuration file, the preprocessing includes formatting the incoming video data to create the first video data of the first region of interest and processing, by the computer processor, the first video data to determine at least one output that is indicative of a first inference dependent upon the first video data. The preprocessing parameters are dependent upon the processing to be performed on the first video data.

Abstract: A method of processing first video data of a region of interest from incoming video data includes preprocessing, according to preprocessing parameters defined within a runtime configuration file, incoming video data to create the first video data of the first region of interest and processing, by a computer processor, the first video data to determine at least one output that is indicative of a first inference dependent upon the first video data. The preprocessing parameters that format incoming video data to create the first video data are dependent upon the processing to be performed on the first video data.

Abstract: A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.

Abstract: A method of improving a main output of a main AI model processing first video data includes analyzing incoming video data via a first processing pipeline and analyzing incoming video data via a second processing pipeline. The second processing pipeline includes receiving the incoming video data from the camera; identifying, by a parameter optimization module, first test preprocessing parameters; preprocessing the incoming video data according to the first test preprocessing parameters defined within a test runtime configuration file, wherein the first test preprocessing includes formatting the incoming video data to create first test video data; accessing the first test video data by a test AI model; processing the first test video data by the test AI model to determine a first test output that is indicative of a first test inference dependent upon the first test video data; and comparing the first test output and the main output to a baseline criterion.

Abstract: Apparatus and associated methods relate to automating building of a software solution for a specific intention that is cooperatively performed by a plurality of computing entities. A broadcasting computing entity broadcasts the specific intention, which includes announcing performance capability of a functional operation by the broadcasting computing entity over a network. One or more listening computing entities listening to such a broadcast then transmit a response to the broadcast. The response includes a subscription to an output of the functional operation. The broadcasting computing entity generates the output of the functional operation and provides the output generated to the one or more listening computing entities. In this way, the broadcasting computing entity advertises services that the broadcasting computing entity can provide, and the listening computing entities can avail themselves of services needed, all in an automated fashion.

Abstract: A method of preprocessing incoming video data of at least one region of interest from a camera collecting video data having a first field of view is disclosed herein that includes receiving the incoming video data from the camera; preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file, with the preprocessing including formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view; and publishing the first video data of the first region of interest to an endpoint to allow access by a first subscriber.