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Cooper Darling

CS125752: Machine Learning for Construction Safety: A Construction Project Manager’s Perspective

(Duration 56:11)

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Key Learning

Key Learning

  • Learn about applications of machine learning for construction safety
  • Learn about industry requirements and challenges for adopting predictive analytics and assistive technologies
  • Discover best practices to adopt technology from a construction project manager’s perspective
  • Discover lessons learned implementing Autodesk Project IQ on a large construction project

Description

Description

There's a perfect storm of technology change driving the construction revolution today. Mobile devices, Internet of Things, sensors, and drones are continuously capturing construction job-site data and the cloud is aggregating this data. Machine-learning applications such as BIM 360 IQ software help construction project teams analyze risk from this data in real time and take corrective actions. Layton Construction and Autodesk have been collaborating and working together for the past year to apply the BIM 360 IQ machine-learning system for construction safety. In this session, Cooper Darling-an assistant project manager from Layton Construction-will be sharing his project manager experiences involved in helping identify and reduce safety risks on a construction job site with the aid of assistive technologies such as machine learning. Cooper is also part of Layton's National Safety Leadership Team, and he's helping champion the processes and standards based on BIM 360 software for Layton.

Target Audience

Target Audience

Construction industry professionals and decision makers interested in learning about new adopting technology in construction

Speakers

Speakers

Related Classes

Related Classes

Tags

Published

  • 2017
  • CS125752
  • AU Las Vegas;

Software

  • BIM 360 Field
  • BIM 360 Docs
  • BIM 360 Plan
  • BIM 360 Glue

Industry

  • Construction Services

Topics

  • Building Construction
  • Internet of Things
  • Building Information Modeling