Brady has been granted a patent for a system that streamlines label printing for objects with multiple features, like patch panels. The system utilizes a camera and machine learning to capture images, detect features, and automatically determine label characteristics based on their locations and distances. GlobalData’s report on Brady gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Brady, Pressure Sensitive Adhesive Tape was a key innovation area identified from patents. Brady's grant share as of July 2024 was 61%. Grant share is based on the ratio of number of grants to total number of patents.
Automated label printing using machine learning for features
The patent US12067313B1 describes a sophisticated system designed for printing labels for objects characterized by multiple features. The system includes a camera, a processor, memory, and a label printing module. The process begins with the camera capturing an image that contains at least two adjacent features from a group. This image is then analyzed by a feature detection machine learning model (MLM) trained to identify features within the object. The MLM detects the adjacent features, determines their location, and calculates the distance between them. Additionally, the system assesses the total number of features in the group and derives at least one characteristic for the label based on the distance and the number of features. A print job is subsequently created to produce the label, which is sent to a printing device.
Further claims detail the system's capabilities, including its application to specific objects like patch panels, where the image may show multiple ports. The system can operate automatically following user input, with the MLM performing tasks such as counting features and determining label characteristics without further user intervention. The label characteristics may include dimensions and markings that delineate adjacent features. The system is also capable of handling multiple groups of features, creating separate print jobs for each group as needed. Additionally, the technology can be implemented on mobile devices, utilizing a compressed version of the MLM for efficient processing. Overall, this patent outlines a method and system that enhances the efficiency and accuracy of label printing for complex objects.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
