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Information and Communication Technology (ICT) and Optimization for Construction Project...
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Information and Communication Technology (ICT) and Optimization for Construction Project Management

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

Deadline for manuscript submissions: 10 February 2026 | Viewed by 2145

Special Issue Editors

Prof. Dr. Ren-Jye Dzeng

E-Mail Website
Guest Editor
Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
Interests: ICT; AI; IoT; construction management
Dr. Jacob J. Lin

E-Mail Website
Guest Editor
Department of Civil Engineering, National Taiwan University, Taipei 106319, Taiwan
Interests: visual data analytics; computer vision; BIM; project controls; lean construction

Special Issue Information

Dear Colleagues,

Effective decision making lies at the heart of successful construction project management amidst its inherent complexities. In recent times, the convergence of Information and Communication Technology (ICT) with optimization methodologies has shown considerable promise, offering pathways for further application in the realm of construction project management decision making.

This Special Issue aims to delve into the contemporary challenges and advancements in ICT applications and optimization methodologies tailored for construction project management. We invite contributions that explore various facets such as decision making frameworks, predictive modeling, simulation techniques, visualization tools, optimization algorithms and automation solutions.

We invite researchers, practitioners and industry experts to contribute to this Special Issue by sharing their insights, experiences and groundbreaking research findings. Together, let us explore and advance the frontier of ICT and optimization methodologies in construction project management. Authors are encouraged to submit original research, reviews, case studies or innovative methodologies that shed light on the latest developments, emerging trends and practical implications in this rapidly evolving field. Topics of interest include, but are not limited to:

  • Building information model (BIM);
  • Artificial intelligence;
  • Deep learning;
  • Big data;
  • Data mining;
  • Internet of Things (IoT);
  • Mobile applications;
  • VR/AR/MR (virtual reality, augmented reality, mixed reality);
  • Optimization algorithms;
  • Integration of optimization techniques;
  • Optimization applications;
  • Stochastic programming;
  • Predictive analytics;
  • Simulation models;
  • Sim2Real (Simulation to Reality);
  • Visualization tools for project monitoring and control.

Prof. Dr. Ren-Jye Dzeng
Dr. Jacob J. Lin
Guest Editors

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

  • construction project management
  • ICT
  • optimization
  • AI
  • deep learning
  • simulation
  • visualization

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

Published Papers (2 papers)

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Research

25 pages, 20040 KiB  
Article
Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers
by Ren-Jye Dzeng, Binghui Fan and Tian-Lin Hsieh
Buildings 2025, 15(1), 110; https://doi.org/10.3390/buildings15010110 - 31 Dec 2024
Viewed by 734
Abstract
The construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions, struck-by events, [...] Read more.
The construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions, struck-by events, and rollovers. While close collaboration among multiple equipment and humans is common, conventional collision alert mechanisms for equipment usually rely on distance sensors with static thresholds, often resulting in too many false alarms, causing drivers’ ignorance. Considering the collaborative operation scenario, this research proposes and develops a dynamic-threshold alert system by recognizing hazardous events based on the types of nearby objects with their orientation or postures and their distances to the system carrier equipment based on image-based recognition and Sim2Real techniques. Two experiments were conducted, and the results show that the system successfully reduced a large number of false near-collision alarms for the collaboration scenarios. Although the accuracy of object recognition and image-based distance estimation is feasible for practical use, it is also easily degraded in the self-obstruction scenario or for equipment with large and movable parts due to incorrect recognition of the bounding boxes of the target objects. Full article
(This article belongs to the Special Issue Information and Communication Technology (ICT) and Optimization for Construction Project Management)
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17 pages, 2139 KiB  
Article
Data-Driven Optimization for Low-Carbon Prefabricated Components Production Based on Ant Colony Algorithms
by Chun-Ling Ho, Chien-Chih Wang, Shenjun Qi and Zichen Zhang
Buildings 2024, 14(12), 4060; https://doi.org/10.3390/buildings14124060 - 21 Dec 2024
Viewed by 799
Abstract
The global industries are progressively transitioning towards low-carbon development; however, construction remains a significant contributor to energy consumption and carbon emissions. In promoting industrialized construction, the use of prefabricated buildings emerges as a crucial strategy for achieving environmental sustainability. This study initially examines [...] Read more.
The global industries are progressively transitioning towards low-carbon development; however, construction remains a significant contributor to energy consumption and carbon emissions. In promoting industrialized construction, the use of prefabricated buildings emerges as a crucial strategy for achieving environmental sustainability. This study initially examines the development and current status of prefabricated concrete component factories in Fujian Province, focusing on regional distribution and production conditions. It also gathers data on carbon emissions, time, and costs to formulate a multi-objective optimization model. Utilizing ant colony algorithms, the model aims to minimize costs while adhering to low-carbon principles and fostering the sustainable development of prefabricated buildings. The optimization results for slabs indicate a minimum production cost of RMB 5.7023 million, with associated carbon emissions of 1154.85 tons. Notably, a cost variation of RMB 10,000 can lead to a maximum difference of 50 tons in carbon emissions, emphasizing the importance of cost minimization as a primary objective. In comparison to conventional production, the optimization of collaborative production demonstrates reductions in both costs and carbon emissions. Furthermore, when focusing on normal and rush modes, costs can be reduced by over 20%, resulting in a potential decrease of up to 50% in carbon emissions. Consequently, effectively mitigating carbon emissions in component production is essential for enhancing the sustainability of the construction industry. Full article
(This article belongs to the Special Issue Information and Communication Technology (ICT) and Optimization for Construction Project Management)
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