Advances in Automation and Intelligence in Construction

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: closed (10 January 2025) | Viewed by 3072

Special Issue Editor


E-Mail Website
Guest Editor
Construction Management Department of Engineering Technology, Sam Houston State University, Huntsville, TX 77340, USA
Interests: construction engineering; management sustainability; artificial intelligence applications in design and construction

Special Issue Information

Dear Colleagues,

Although construction industry is one the least digitized industries in the world, there are several advances in automation and intelligence are shaping the construction industry. 

Building Information Modeling (BIM) Enhancements: BIM continues to evolve, enabling more comprehensive and collaborative project management. Advances include the integration of augmented reality (AR) and virtual reality (VR) for enhanced visualization, clash detection, and real-time project monitoring.

Prefabrication and Modular Construction: Automation has facilitated the growth of prefabrication and modular construction. Robotics and automated assembly lines are being used to manufacture components off-site, leading to increased efficiency, reduced waste, and faster project timelines.

Construction Robotics: Robotics are being employed for tasks that are dangerous, repetitive, or labor-intensive. These robots can perform tasks such as bricklaying, concrete pouring, and even site cleanup. Drones are also used for site surveys, progress monitoring, and inspection.

Autonomous Heavy Equipment: Construction equipment is becoming increasingly automated and autonomous. Self-driving machinery like excavators, bulldozers, and dump trucks are being developed to optimize operations, enhance safety, and improve precision.

AI-Powered Project Management: Artificial intelligence is being used to analyze and predict project outcomes, optimize schedules, allocate resources efficiently, and identify potential risks. Predictive analytics help project managers make more informed decisions.

Construction Software Integration: Software platforms are becoming more integrated, allowing seamless data exchange between various tools used in construction, from design and planning to scheduling and cost estimation.

Internet of Things (IoT) Sensors: IoT sensors are being embedded in construction materials and equipment to monitor conditions such as temperature, humidity, stress, and structural integrity. This real-time data helps ensure quality and safety.

Construction Site Safety: Wearable technology and IoT devices are being used to monitor workers' health and safety conditions, alerting supervisors in case of accidents or hazardous conditions.

Material Optimization: Machine learning algorithms are being employed to analyze data on material properties and construction processes to optimize material usage, reduce waste, and enhance sustainability.

Digital Twin Technology: Digital twins replicate physical assets in a virtual environment. They enable real-time monitoring and simulation, helping stakeholders visualize, analyze, and manage construction projects throughout their lifecycle.

Automated Quality Control: Automated quality control systems use computer vision to detect defects in construction materials, structures, and components, improving overall project quality.

Smart Construction Equipment: Equipment and tools equipped with sensors and connectivity features enable real-time monitoring, preventive maintenance, and improved resource allocation.

Dr. Ebrahim Parvaresh Karan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence in construction
  • smart construction
  • Internet of Things (IoT) sensors in construction
  • autonomous heavy construction equipment
  • pre-fabrication and modular construction

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

14 pages, 1637 KiB  
Article
AIR Agent—A GPT-Based Subway Construction Accident Investigation Report Analysis Chatbot
by Lin Zhang, Yanan Hou and Fei Ren
Buildings 2025, 15(4), 527; https://doi.org/10.3390/buildings15040527 - 9 Feb 2025
Cited by 1 | Viewed by 843
Abstract
Subway construction accident reports often take a lot of time and personnel to analyze and contain a large amount of data that require professional identification, which increases the difficulty of the analysis. This study aims to use Generative Pre-trained Transformer (GPT) models for [...] Read more.
Subway construction accident reports often take a lot of time and personnel to analyze and contain a large amount of data that require professional identification, which increases the difficulty of the analysis. This study aims to use Generative Pre-trained Transformer (GPT) models for the automated analysis of subway construction accident investigation reports, with the goal of improving the efficiency of accident identification and analysis. By analyzing a dataset of 50 subway reports, this study developed the Accident Investigation Report (AIR) Agent, which utilizes GPTs to automatically identify accident types and extract key details from the reports. The chatbot is composed of three core modules: a conversation module, an instruction module, and a knowledge module. Ablation studies were performed to validate the AIR Agent’s efficiency, and the validation results show that the AIR Agent achieves an accuracy of 80.32% when analyzing new reports with a brief conclusion, demonstrating the AIR Agent’s ability to automatically format and structure reports in a consistent and correct manner. These findings suggest that the AIR Agent can significantly reduce the manual effort involved in accident investigation report analysis and enhance the overall efficiency of analyzing subway construction accident investigation reports, thereby improving the effectiveness of accident investigation and management. Full article
(This article belongs to the Special Issue Advances in Automation and Intelligence in Construction)
Show Figures

Figure 1

31 pages, 16018 KiB  
Article
Research on Positioning and Simulation Method for Autonomous Mobile Construction Platform
by Xinyu Shi, Chaoran Wang, Tyson Keen Phillips, Chengpeng Sun, Haining Zhou, Wenxuan Zhao, Weijiu Cui and Da Wan
Buildings 2024, 14(5), 1196; https://doi.org/10.3390/buildings14051196 - 23 Apr 2024
Cited by 2 | Viewed by 1525
Abstract
In the architecture, engineering, and construction (AEC) industry, the positioning technology for a mobile construction platform (MCP) is critical to achieve on-site, continuous, large-scale construction. During construction, MCP movement and construction actions seldom occur simultaneously. Therefore, this paper categorizes the MCP into stationary [...] Read more.
In the architecture, engineering, and construction (AEC) industry, the positioning technology for a mobile construction platform (MCP) is critical to achieve on-site, continuous, large-scale construction. During construction, MCP movement and construction actions seldom occur simultaneously. Therefore, this paper categorizes the MCP into stationary and moving states for positioning studies, respectively. When the platform is stationary, it is positioned using an improved ultra-wideband (UWB) sensor. When the platform is in motion, a single UWB positioning technique cannot meet the required accuracy for positioning, and fusion positioning using both UWB and an inertial measurement unit (IMU) is considered. The experimental results show that compared with only UWB positioning, the improved UWB positioning algorithm improves the positioning accuracy by 53% in the stationary state, and the fused UWB/IMU positioning improves the positioning accuracy by 46% in the moving state. As a result, the positioning accuracy of the MCP is significantly improved regardless of whether it is in a stationary or moving state. Furthermore, this paper integrates the positioning technique with the robotic arm construction technique to successfully simulate an on-site continuous construction of a wooden cabin, which provides the potential for large-scale continuous construction in real-world scenarios in the future. Full article
(This article belongs to the Special Issue Advances in Automation and Intelligence in Construction)
Show Figures

Figure 1

Back to TopTop