Abstract: Methods, systems, and platforms for managing machine learning models are described. A model registry system receives first data including a model and second data including metadata and at least one metric of the model. Via a local network, the first data is stored to a data storage device and the second data is sent to an application programming interface (API). The first data is retrieved from the data storage device to a model use case program operating in a software development environment native to where the model registry system stores the model. The second data, including the metadata and the at least one metric of the model, is sent to a user interface (UI) via the API. The stored model can be deployed from the model use case program via the API.

Abstract: An example distributed system for trip estimation is described. The system includes a plurality of sensors disposed in a plurality of geographically distributed facilities. Each of the plurality of geographically distributed facilities includes departments including retrievable items, and each one of the plurality of geographically distributed facilities includes at least one of the plurality of sensors in each of the departments. The system includes a computing system in communication with the plurality of sensors and the one or more databases. The computing system can be configured to receive an item and a source geographic location from a user device, select a subset of the geographically distributed facilities, establish a contemporaneous density of people at a particular department corresponding to the item received from the user device, and output to a user interface on the user device an estimated first transit value based on the contemporaneous density.

Abstract: Provided is a system and methods for reducing wait time in a store with a plurality of checkout queues. The system includes an item counting device coupled to a shopping cart. The item counting device includes a weigh sensor and a counter, wherein the counter increments by 1 in response to the weigh sensor detecting an increase in weight as an item is placed within the shopping cart. The system includes an efficiency analyzer that determines a historical efficiency of an employee at a checkout register. Additionally, the system includes proximity processor that receives data from a customer through an input device and outputs a proximity of the customer to a queue. The system has a wait time processor that determines the wait time of a plurality of checkout queues and outputs the same to the customer.

Abstract: An example distributed system for trip estimation is described. The system includes a plurality of sensors disposed in a plurality of geographically distributed facilities. Each of the plurality of geographically distributed facilities includes departments including retrievable items, and each one of the plurality of geographically distributed facilities includes at least one of the plurality of sensors in each of the departments. The system includes a computing system in communication with the plurality of sensors and the one or more databases. The computing system can be configured to receive an item and a source geographic location from a user device, select a subset of the geographically distributed facilities, establish a contemporaneous density of people at a particular department corresponding to the item received from the user device, and output to a user interface on the user device an estimated first transit value based on the contemporaneous density.

Abstract: Provided is a system and methods for reducing wait time in a store with a plurality of checkout queues. The system includes an item counting device coupled to a shopping cart. The item counting device includes a weigh sensor and a counter, wherein the counter increments by 1 in response to the weigh sensor detecting an increase in weight as an item is placed within the shopping cart. The system includes an efficiency analyzer that determines a historical efficiency of an employee at a checkout register. Additionally, the system includes proximity processor that receives data from a customer through an input device and outputs a proximity of the customer to a queue. The system has a wait time processor that determines the wait time of a plurality of checkout queues and outputs the same to the customer.

Abstract: An electronic device transmits a user profile to a server. The electronic device receives a voice call from the server, where audio content of the voice call includes an advertisement related to the user profile. The electronic device automatically accepts the received voice call based on predefined settings. The electronic device then records the audio content of the voice call. The electronic device extracts the advertisement from the recorded audio content and stores the extracted advertisement in a memory of the electronic device. In another implementation, the electronic device receives a text message from the server, where content of the text message includes a characteristic of the advertisement. The electronic device then associates and stores the received characteristic with the stored advertisement.