Abstract
The unprecedented growth of data on construction site through unmanned ground and aerial vehicles, smartphones, fixed cameras and sensors and the development of robotics, computer vision, and construction management provide a unique opportunity to establish a CPS to automate and streamline progress monitoring from data collection, progress and activity tracking, and reporting. Automated ground robots and drones collect data and upload to the cloud system, the system generates Reality models and analyze construction activities using state-of-the-art computer vision techniques. The models are then fused with Building Information Model (BIM) and project schedules to detect and track the progress in real-time. To make the models actionable, the CPS generates visual analytics in the format of digital models, dashboards to physical reports, weekly work plans to facilitate the project control decision making. In this chapter, we present how the latest robotics, computer vision technologies with construction management theories that can establish a CPS to enable performance tracking. We introduce the cutting edge techniques for each component in the CPS such as deep learning, object detection in the context of construction progress monitoring and discuss the underlying method with a use case. The challenges of using these techniques in construction progress monitoring and the open research areas are also discussed in detail.
Original language | English (US) |
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Title of host publication | Cyber-Physical Systems in the Built Environment |
Publisher | Springer |
Pages | 63-87 |
Number of pages | 25 |
ISBN (Electronic) | 9783030415600 |
ISBN (Print) | 9783030415594 |
DOIs | |
State | Published - Jan 1 2020 |
Keywords
- Autonomous data collection
- BIM
- Computer vision
- Construction progress monitoring
- Daily construction reports
- Lean construction
- Machine learning
- Project controls
- Reality capture
- SLAM
ASJC Scopus subject areas
- General Engineering
- General Arts and Humanities
- General Environmental Science