Epicor Software has patented a system and method for processing demand data for resources in a technology platform. The method involves collecting demand profiles, reformatting them into cumulative demand plots, calculating distance metrics, clustering resources, and generating visualizations for each cluster to aid in platform management. GlobalData’s report on Epicor Software 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 Epicor Software, Medical device secure data transmission was a key innovation area identified from patents. Epicor Software's grant share as of May 2024 was 72%. Grant share is based on the ratio of number of grants to total number of patents.
Resource demand processing system for technology platform management
A recently granted patent (Publication Number: US11977925B2) discloses a resource demand processing system that involves inputting demand profiles for a set of resources, reformatting them into cumulative demand plots, calculating distance metrics between these plots, clustering the resources based on these metrics, and generating visualizations for each cluster. The system further includes generating mathematical characterizations for each cluster, automatically creating metatags based on these characterizations, load balancing resources, and analyzing clusters using machine learning models to provide metatags, control parameters, predictions, or recommendations. The resources can range from computing and energy resources to autonomous vehicles and inventory units.
Additionally, the patent describes a method for processing demand data in a technology platform by collecting demand profiles, reformatting them into cumulative demand plots, calculating distance metrics, clustering resources, and generating characterizations for each cluster to facilitate platform management. The method also involves generating visualizations, automatically creating metatags, load balancing resources, and analyzing clusters using machine learning models. The technology platform can include distributed computing, energy resources, web resources, communication resources, autonomous vehicles, inventory units, or SKU identifiers. The method emphasizes the normalization of cumulative demand plots and the calculation of distance metrics based on the area between pairs of normalized plots, enhancing the efficiency and effectiveness of resource management within the platform.
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