Procore Technologies’s patent involves a computing platform using machine learning models to predict construction project parameters based on historical data. The platform trains models on reference projects, predicts values for parameters, and presents them to users. This innovation streamlines project planning and decision-making processes. GlobalData’s report on Procore Technologies 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 Procore Technologies, 3d modelling and rendering was a key innovation area identified from patents. Procore Technologies's grant share as of May 2024 was 13%. Grant share is based on the ratio of number of grants to total number of patents.
Construction project parameter prediction using machine learning
A recently granted patent (Publication Number: US11983653B2) discloses a computing platform that utilizes machine learning models to predict parameters related to construction projects. The platform trains machine learning models using historical data from reference construction projects to predict values for parameters such as cost or completion time. By inputting data values associated with a given construction project into the trained models, the platform can predict similar reference projects and determine parameter values for the given project. The platform also incorporates unsupervised clustering techniques to analyze historical data and improve the accuracy of predictions. Additionally, the platform can receive information from client stations to enhance the data used for predictions, ensuring more accurate and tailored results for each construction project.
Furthermore, the patent describes a method carried out by the computing platform, detailing the process of training machine learning models, obtaining data values for construction projects, aligning timeframes with reference projects, and presenting predicted parameter values to users. The method emphasizes the importance of sufficient information for accurate predictions, allowing the platform to adjust and update parameter values based on new data. By incorporating multiple machine learning models and clustering techniques, the platform aims to provide precise and reliable predictions for various construction projects. Overall, the patent highlights the innovative use of machine learning in the construction industry to streamline project management and decision-making processes, ultimately improving efficiency and outcomes in the field.
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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.
