Vision-based ai image recognition systems and control logic for automated object identification and documentation

A non-transient, computer-readable medium storing instructions executable by a device controller of a handheld portable computing device (PCD) of a user, the instructions, when executed by the device controller, causing the handheld PCD to perform operations comprising:

• capturing, using an optical image sensor of the handheld PCD, image data indicative of a product image of a physical product;
• determining, using a geopositional transceiver of the handheld PCD responsive to capturing the image data, a real-time geographic location of the physical product;
• transmitting, via a wireless communications transceiver of the handheld PCD over a distributed computing network to a vision-based product recognition system, the image data and the real-time geographic location of the product;
• receiving, from an AI-based image recognition and classification (RnC) model, a product classification data set derived by analyzing the image data of the physical product, the product classification data set including a product type and an attribute list of product components and materials for the physical product;
• and
• receiving, from a system controller of the vision-based product recognition system, an electronic data record (EDR) corresponding to the physical product generated using the product classification data set, the EDR including a record identifier, summary data representative of the product components and materials, and an electronic pointer identifying a location of predefined product data associated with the physical product on a data repository.

A vision-based product recognition system, comprising:

• a handheld portable computing device (PCD);
• a dedicated software application operating on the handheld PCD;
• an optical image sensor communicatively connected to the handheld PCD;
• a geopositional transceiver communicatively connected to the handheld PCD;
• and
• a system controller communicatively connected to the handheld PCD over a distributed computing network, the system controller being programmed to:
• receive, from the optical image sensor via the handheld PCD, image data indicative of a product image of a physical product;
• receive, from the geopositional transceiver via the handheld PCD responsive to capturing the image data, a real-time geographic location of the physical product;
• derive, using an AI-based image recognition and classification (RnC) model, a product classification data set by analyzing the image data of the physical product, the product classification data set including a product type and an attribute list of product components and materials;
• and
• generate, using on the product classification data set, an electronic data record (EDR) corresponding to the physical product, the EDR including a record identifier, summary data representative of the product components and materials, and an electronic pointer identifying a location of predefined product data associated with the physical product on a data repository.