Systems and methods for auto-replenishment of products using pressure mapping sensors and machine learning

A system for identifying, tracking usage of, and replenishing products on a shelf of a product storage unit, the system comprising:

• a pressure sensor array positioned on the shelf and configured to detect forces exerted on the pressure sensor array by each of the products located on the shelf;
• an electronic database configured to store reference pressure array data representative of a reference pressure data model relative to each of the products;
• a computing device in communication with the pressure sensor array and the electronic database;
• the reference pressure data model for a selected one of the products being generated via training, by the computing device, of a machine learning model using pressure data generated on the pressure sensor array by a reference product substantially identical to the selected one of the products when the reference product is at a plurality of consumption levels;
• each reference pressure data model generated via training of the machine learning model being associated in the electronic database with product identity data that identifies a product corresponding to the reference pressure data model;
• and
• the computing device including a processor-based control circuit configured to:
• activate the pressure sensor array to cause the pressure sensor array to generate a pressure reading for the selected one of the products when the selected one of the products is positioned on the pressure array;
• obtain a pressure data set associated with the selected one of the products and captured by the pressure sensor array when the selected one of the products was positioned on the pressure sensor array;
• process the pressure data set associated with the selected one of the products and captured by the pressure sensor array when the selected one of the products was positioned on the pressure sensor array by generating a boxed pressure data set, where a virtual bounding box extends around the pressure data set associated with the selected one of the products;
• correlate the boxed pressure data set associated with the selected one of the products with the reference pressure array data stored in the electronic database;
• in response to a determination by the control circuit that the reference pressure array data stored in the electronic database includes a reference pressure data model generated via the training of the machine learning model that matches the boxed pressure data set associated with the selected one of the
• products, obtain the product identity data stored in the electronic database in association with the reference pressure data model that matches the boxed pressure set associated with the selected one of the products to determine an identity of the selected one of the products;
• and
• in response to a determination by the control circuit that the reference pressure array data stored in the electronic database does not include the reference pressure data model generated via the training of the machine learning model does not match the boxed pressure data set associated with the selected one of the products:
• cause the selected one of the products to be scanned by a sensor configured to scan identifying indicia on the selected one of the products;
• obtain the identifying indicia scanned by the sensor and, based on a determination of the identity of the selected one of the products, generate product identity data identifying the selected one the products;
• update the trained machine learning model that is stored in the electronic database associated with the selected one of the products such that an updated machine learning model includes the an updated boxed pressure set associated with the selected one of the products the identity of which was determined based on the scan of the identifying indicia of the selected one of the products;
• and
• identify, by the updated machine learning model, a subsequent product identical to the selected one of the products based on a match between the pressure data generated on the pressure sensor array by the subsequent product when the subsequent product is located on the shelf and the updated boxed pressure set included in the updated machine learning model.