Tracking product items in an automated-checkout store

A system for tracking a product item in an automated-checkout store comprising a computer system and a plurality of sensors including at least one or more cameras, one or more weight sensors, one or more pressure sensors, and one or more capacitive sensors, the computer system comprising a processor and a non-transitory computer-readable storage medium storing instructions executable by the processor to cause the system to perform operations comprising:

• receiving, by the computer system from the plurality of the sensors, data collected by the plurality of the sensors;
• identifying, by the computer system, an account associated with a person who enters the store;
• receiving, by the computer system, data on movement of the product item collected by the plurality of the sensors;
• determining, by the computer system, an interaction between the person and the product item based on the data collected by the plurality of the sensors;
• extracting, by the computer system, from the data received from the one or more plurality of the sensors, a plurality of features associated with the product item, wherein the features comprise a conductivity, a color, a position, and a surface force image, the conductivity is used to determine a type of material that makes up at least a part of the product, and the surface force image is used to determine a footprint of the product that includes a shape of a bottom surface of the product;
• determining, by the computer system, using a machine-learning model, an identity of the product item based on the extracted features including the conductivity, the color, the position, and the surface force image, wherein the machine-learning model is trained based on training data collected from the plurality of the sensors;
• storing, by the computer system, information associating the product item with the person;
• and
• deducting, by the computer system, a payment amount from the identified account, wherein the payment amount is based on a price of the product item associated with the person.

A non-transitory computer-readable storage medium for tracking a product item in an automated-checkout store, configured with instructions executable by one or more processors to cause the one or more processors to perform operations comprising:

• receiving, from a plurality of sensors including at least one or more cameras, one or more weight sensors, one or more pressure sensors, and one or more capacitive sensors, data collected by the sensors;
• identifying an account associated with a person who enters the store;
• receiving, by the computer system, data on movement of the product item collected by the plurality of the sensors;
• determining an interaction between the person and the product item based on the data collected by the plurality of the sensors;
• extracting, by the computer system, from the data received from the plurality of the sensors, a plurality of features associated with the product item, wherein the features comprise a conductivity, a color, a position, and a surface force image, the conductivity is used to determine a type of material that makes up at least a part of the product, and the surface force image is used to determine a footprint of the product that includes a shape of a bottom surface of the product;
• determining, by the computer system, using a machine-learning model, an identity of the product item based on the extracted features including the conductivity, the color, the position, and the surface force image, wherein the machine-learning model is trained based on training data collected from the plurality of the sensors;
• storing information associating the product item with the person;
• and
• deducting a payment amount from the identified account, wherein the payment amount is based on a price of the product item associated with the person.