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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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Computer Vision-Based Construction Process Sensing for Cyber-Physical Systems: A Review.

Binghan Zhang1, Bin Yang1, Congjun Wang2

  • 1Department of Structural Engineering, Tongji University, 1239 Siping, Shanghai 200092, China.

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|August 28, 2021
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Summary
This summary is machine-generated.

This study explores computer vision (CV) for sensing in cyber-physical systems (CPSs) within the Architecture, Engineering, and Construction (AEC) industry. A novel CV-based CPS architecture is proposed to enhance construction site sensing and automation.

Keywords:
computer visioncyber–physical systemsreviewsensing system

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Area of Science:

  • Engineering and Computer Science
  • Construction Management
  • Automation and Robotics

Background:

  • Cyber-physical systems (CPSs) represent the future of engineered systems, yet their adoption in Architecture, Engineering, and Construction (AEC) remains limited.
  • Effective sensing methods are crucial for CPS implementation in construction, but current approaches face challenges in complex site environments.

Purpose of the Study:

  • To review the application potential of computer vision (CV)-based sensing methods for CPS in the AEC industry.
  • To identify knowledge gaps and propose practical suggestions for improving construction site sensing.
  • To introduce a novel CV-based sensing approach and architecture for construction process CPS.

Main Methods:

  • A comprehensive literature review was conducted on current CPS applications in AEC.
  • The review focused on the advantages and applications of CV for sensing various construction entities.
  • A novel CV-based construction site sensing method and CPS architecture were conceptualized.

Main Results:

  • Computer vision offers unique advantages for low-cost, non-invasive information acquisition in complex construction environments.
  • The proposed CV-based CPS architecture leverages visual data for enhanced on-site sensing.
  • This approach can significantly supplement existing sensing methods, promoting automation and intelligence in construction processes.

Conclusions:

  • Computer vision presents a viable and advantageous solution for sensing in construction process CPS.
  • The proposed architecture provides a framework for implementing CV-based sensing, addressing current limitations.
  • This research contributes to advancing automation and intelligence in the AEC industry through innovative sensing strategies.