Pro-core Technologies Limited

Julian Clayton

Matt Man

Mohammad Soltani

Navin Kaminoulu

Azadeh Yazdan Panah Gohar Rizi

Taylor Wasser

An example computing platform is configured to: obtain a two-dimensional drawing of a portion of a construction project; perform an image processing analysis of the two-dimensional drawing to identify one or more location entities within the two-dimensional drawing; derive embeddings for each location entity in the two-dimensional drawing; based on the derived embeddings, determine relationships between the one or more location entities; and based on the determined relationships between the one or more location entities, generate a location entity data taxonomy that includes each identified location entity as a respective node that is related to at least one other location entity.

Computer systems and methods for identifying location entities and generating a location entity data taxonomy

A computing system is configured to determine an update to a master schedule for a construction project that comprises a plurality of tasks, each task comprising a respective scheduled start date; execute a machine learning model that has been trained with historical construction project schedule data and thereby identify one or more tasks that is each a candidate for commencement earlier than its scheduled start date; cause a client station to display each identified task, its scheduled start date, a respective new start date, and an impact on the master schedule if the task is commenced on the respective new start date; receive user input indicating a selection of a given task that is to be commenced earlier than its scheduled start date; and cause a notification to be transmitted to a party responsible for completing the given task indicating that the given task has been nominated for earlier commencement and requests approval for earlier commencement.

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Milford, CT, United States of America

Julian Clayton