Integrating BIM–IoT and Autonomous Mobile Robots for Construction Site Layout Printing

Author:

Iqbal Fahad1ORCID,Ahmed Shiraz1,Amin Fayiz1,Qayyum Siddra2ORCID,Ullah Fahim2ORCID

Affiliation:

1. Department of Civil Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences & Technology, Topi 23640, Pakistan

2. School of Surveying and Built Environment, University of Southern Queensland, Springfield Central, QLD 4300, Australia

Abstract

The traditional methods of marking construction site layouts using manual techniques such as chalk lines are prone to human errors, resulting in discrepancies between blueprints and actual layouts. This has serious implications for project delivery, construction, costs and, eventually, project success. However, this issue can be resolved through autonomous robots and construction automation in line with Industry 4.0 and 5.0 goals. Construction automation enables workers to concentrate on the construction phase and not worry about manual site markups. This leads to an enhancement in their productivity. This study aims to improve the floor layout printing technique by introducing a framework that integrates building information modeling (BIM) and the Internet of Things (IoT), i.e., BIM–IoT and autonomous mobile robots (AMR). The development process focuses on three key components: a marking tool, an IoT-based AMR and BIM. The BIM-based tools extract and store coordinates on the cloud platform. The AMR, developed using ESP32 and connected to the Google Firestore cloud platform, leverages IoT technology to retrieve the data and draw site layout lines accordingly. Further, this research presents a prototype of an automated robot capable of accurately printing construction site layouts. A design science research (DSR) method is employed in this study that includes a comprehensive review of the existing literature and usage of AMRs in construction layout printing. Subsequently building upon the extant literature, an AMR is developed and experiments are conducted to evaluate the system’s performance. The experiment reveals that the system’s precision falls within a range of ±15 mm and its angle accuracy is within ±4 degrees. Integrating robotic automation, IoT and BIM technologies enhances the efficiency and precision of construction layout printing. The findings provide insights into the potential benefits of deploying AMRs in construction projects, reducing site layout errors and improving construction productivity. This study also adds to the body of knowledge around construction automation in line with Industry 4.0 and 5.0 endeavors.

Publisher

MDPI AG

Subject

Building and Construction,Civil and Structural Engineering,Architecture

Reference58 articles.

1. Construction Automation: Research Areas, Industry Concerns and Suggestions for Advancement;Chen;Autom. Constr.,2018

2. Changali, S., Mohammad, A., and Van Nieuwland, M. (2015). McKinsey Quarterly, McKinsey.

3. Can Robots Replace Human Beings?—Assessment on the Developmental Potential of Construction Robot;Ma;J. Build. Eng.,2022

4. Robotics in Civil Engineering;Haas;Comput. Aided Civ. Infrastruct. Eng.,1995

5. Productivity of Digital Fabrication in Construction: Cost and Time Analysis of a Robotically Built Wall;Hunhevicz;Autom. Constr.,2018

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