AI Applications in Construction and Infrastructure

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 September 2024 | Viewed by 1040

Special Issue Editor


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Guest Editor
Department of Mechanical and Industrial Engineering, Marshall University, Huntington, WV 25755, USA
Interests: system resilience; system restoration modeling; disaster management; supply chain and logistics; extended reality

Special Issue Information

Dear Colleagues,

The journal Information is pleased to announce a Special Issue on "AI Applications in Construction and Infrastructure." This Special Issue aims to explore the advancements, challenges, and potential of artificial intelligence (AI) in revolutionizing the construction industry and infrastructure development.

AI is a transformative technology with the potential to streamline and enhance construction and infrastructure projects. By leveraging AI algorithms, machine learning, robotics, and data analytics, innovative solutions can be developed to improve the efficiency, productivity, safety, and sustainability of construction.

This Special Issue seeks high-quality, original research articles, reviews, technical notes, and case studies that address the utilization of AI in diverse areas related to construction and infrastructure. Topics of interest include, but are not limited to:

  • AI-assisted project planning and design;
  • Robotics and automation in construction tasks;
  • AI-powered monitoring and surveillance systems;
  • Safety and risk management using AI techniques;
  • AI-driven optimization in construction logistics and supply chain management;
  • Energy efficiency and sustainability using AI applications;
  • AI-based predictive maintenance and equipment optimization;
  • Virtual reality and augmented reality for construction visualization and simulation;
  • AI-enabled decision support systems for construction management;
  • Ethical, legal, and social implications of AI adoption in construction.

We look forward to receiving your valuable contributions and disseminating the latest research findings on AI applications in construction and infrastructure in this Special Issue of Information.

Dr. Sudipta Chowdhury
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. Information is an international peer-reviewed open access monthly 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 1600 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 (AI)
  • AI algorithms
  • AI decision support systems
  • construction
  • infrastructure design, planning, and monitoring
  • system-of-systems (SoS)

Published Papers (1 paper)

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Research

34 pages, 10124 KiB  
Article
Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering
by Hongxia Hu, Shouguo Jiang, Shankha Shubhra Goswami and Yafei Zhao
Information 2024, 15(5), 280; https://doi.org/10.3390/info15050280 - 14 May 2024
Viewed by 439
Abstract
This research paper presents a comprehensive study on optimizing the critical artificial intelligence (AI) factors influencing cost management in civil engineering projects using a multi-criteria decision-making (MCDM) approach. The problem addressed revolves around the need to effectively manage costs in civil engineering endeavors [...] Read more.
This research paper presents a comprehensive study on optimizing the critical artificial intelligence (AI) factors influencing cost management in civil engineering projects using a multi-criteria decision-making (MCDM) approach. The problem addressed revolves around the need to effectively manage costs in civil engineering endeavors amidst the growing complexity of projects and the increasing integration of AI technologies. The methodology employed involves the utilization of three MCDM tools, specifically Delphi, interpretive structural modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). A total of 17 AI factors, categorized into eight broad groups, were identified and analyzed. Through the application of different MCDM techniques, the relative importance and interrelationships among these factors were determined. The key findings reveal the critical role of certain AI factors, such as risk mitigation and cost components, in optimizing the cost management processes. Moreover, the hierarchical structure generated through ISM and the influential factors identified via MICMAC provide insights for prioritizing strategic interventions. The implications of this study extend to informing decision-makers in the civil engineering domain about effective strategies for leveraging AI in their cost management practices. By adopting a systematic MCDM approach, stakeholders can enhance project outcomes while optimizing resource allocation and mitigating financial risks. Full article
(This article belongs to the Special Issue AI Applications in Construction and Infrastructure)
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