Products (ex: product, part, component) share common universal & transaction data and descriptive attributes. There are significant challenges to securely capture data, and to easily search / access the data throughout its lifecycle. It is also very difficult to find a universal method to describe a product and/or product attributes in a consistent and scalable manner. Utilizing blockchain technology, we will capture product attributes and corresponding data through a universal label and/or artificial barcode. Products will be scanned by users to collect data throughout a product’s use and send data to the Cloud. Data can then be accessed and analyzed using advanced artificial neural networks (ANN) to organize, connect, and gain inference of the product itself. This innovation allows a scalable and consistent way to find usage and attributes for any product.
Still further, aspects of the presented techniques support the training of an artificial neural network (ANN) through machine learning (ML) to make the product and product attributes searchable and to provide recommendations and intelligent matches based on user inputs and questions regarding product attributes and details.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Ligon, Kate; Ghose, Ted; and Peterson, Ariel, "UNIVERSAL PRODUCT ARTIFICIAL NEURAL NETWORK (UPANN)", Technical Disclosure Commons, (April 04, 2022)