Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.4
3.1
Journals
Buildings
Special Issues
Safety Management and Occupational Health in Construction
share announcement

Safety Management and Occupational Health 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: 30 September 2025 | Viewed by 1052

Special Issue Editors

Dr. Krishna Kisi

E-Mail Website
Guest Editor
Department of Engineering Technology, Texas State University, San Marcos, TX 78666, USA
Interests: construction labor productivity; human performance; ergonomics; construction safety; stem education; technology applications; workforce development and training; dispute resolution in engineering and construction
Dr. Kishor Shrestha

E-Mail Website
Guest Editor
Voiland College of Engineering and Architecture, Washington State University, Pullman, WA 99164, USA
Interests: injury prevention; construction engineering; transportation; road safety; traffic safety
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The construction industry remains one of the most hazardous sectors worldwide, with workers frequently exposed to risks that lead to injuries, illnesses, and fatalities. As construction projects become increasingly complex, ensuring effective safety management and occupational health practices is essential for safeguarding workers' well-being and maintaining project efficiency. This Special Issue focuses on advancing construction safety, occupational health, and risk management research to foster a safer and more sustainable work environment.

This Special Issue will bring together cutting-edge research, innovative methodologies, practical case studies, and practical applications of AI that enhance safety management strategies and occupational health frameworks in construction. We invite academics, researchers, industry professionals, and policymakers to contribute original research articles, reviews, and case studies addressing key challenges and solutions in construction safety. We also invite articles that explore how AI-powered technologies can enhance hazard detection, safety training, and decision-making in construction.

Topics of interest include, but are not limited to, the following:

  • Safety Management Systems: Development and implementation of safety policies, procedures, and compliance frameworks;
  • Occupational Health Risks: Identification and mitigation of work-related illnesses, such as musculoskeletal disorders (MSDs) and psychological stress;
  • Human Factors and Ergonomics: Understanding how physical and cognitive loads impact workers’ safety and performance;
  • Technology and Safety Innovations: Applications of artificial intelligence (AI), the Internet of Things (IoT), wearable sensors, and virtual/augmented reality (VR/AR) for safety training and hazard prediction;
  • AI-Enhanced Safety Management Systems: Implementation of AI-driven predictive analytics, machine learning models, and automation for proactive safety management;
  • Safety Culture and Behavioral Approaches: Exploring how leadership, training, and worker perceptions influence safety outcomes;
  • Computer Vision and Hazard Detection: Image and video analysis for identifying unsafe behaviors, PPE compliance, and hazardous conditions on-site;
  • Regulatory Compliance and Policy Impacts: Evaluating the effectiveness of occupational safety laws, standards, and enforcement mechanisms;
  • Life Cycle Safety Management: Integrating safety considerations from project design to demolition to enhance worker protection throughout the construction process.

We welcome interdisciplinary approaches that combine engineering, AI, safety science, management, and emerging technologies to advance knowledge in construction safety and occupational health. Contributions should provide practical insights, empirical evidence, or case studies that can improve industry practices and inform policy development.

Dr. Krishna Kisi
Dr. Kishor Shrestha
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 safety
  • occupational health
  • human factors
  • ergonomics
  • hazard detection
  • worker well-being
  • decision making
  • workplace monitoring
  • automation in safety management

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)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

18 pages, 242 KiB  
Article
Exploring Factors Impeding the Implementation of Health and Safety Control Measures in the South African Construction Industry
by Ndaleni Phinias Rantsatsi
Buildings 2025, 15(14), 2439; https://doi.org/10.3390/buildings15142439 - 11 Jul 2025
Viewed by 274
Abstract
Organisations have provided health and safety (H&S) control measures for construction activities, but the literature suggests that implementing these measures in the construction industry remains a challenge. This study aims to explore the factors impeding the implementation of H&S control measures (barriers). The [...] Read more.
Organisations have provided health and safety (H&S) control measures for construction activities, but the literature suggests that implementing these measures in the construction industry remains a challenge. This study aims to explore the factors impeding the implementation of H&S control measures (barriers). The study followed a qualitative research approach using interview form as a data collection tool designed to collect qualitative data on the factors impeding the implementation of H&S control measures. Purposive sampling method was adopted. The content analysis method was used to analyse the collected data. The findings reveal that the implementation of H&S control measures is affected by different barriers. The study uncovered eight main barriers (lack of management support and commitment, implementation costs, lack of training and education, language and cultural differences, time pressure, prioritisation of production over H&S issues, lack of worker involvement and participation and lack of communication) to the implementation of H&S control measures. Respondents were mainly from H&S background; it would be interesting to explore the perceptions of site managers, engineers, designers, supervisors and field workers through the use of a quantitative approach involving a larger sample. By identifying and understanding these barriers to the implementation of H&S control measures, construction organisations could be in a better position to control construction hazards. This paper adds value to construction organisations and professionals’ understanding of barriers to the implementation of H&S control measures on construction sites. The study also recommends measures to remove barriers or facilitate better implementation of H&S control measures on construction sites. Full article
(This article belongs to the Special Issue Safety Management and Occupational Health in Construction)
44 pages, 1470 KiB  
Article
GPT Applications for Construction Safety: A Use Case Analysis
by Ali Katooziani, Idris Jeelani and Masoud Gheisari
Buildings 2025, 15(14), 2410; https://doi.org/10.3390/buildings15142410 - 9 Jul 2025
Viewed by 558
Abstract
This study explores the use of Large Language Models (LLMs), specifically GPT, for different safety management applications in the construction industry. Many studies have explored the integration of GPT in construction safety for various applications; their primary focus has been on the feasibility [...] Read more.
This study explores the use of Large Language Models (LLMs), specifically GPT, for different safety management applications in the construction industry. Many studies have explored the integration of GPT in construction safety for various applications; their primary focus has been on the feasibility of such integration, often using GPT models for specific applications rather than a thorough evaluation of GPT’s limitations and capabilities. In contrast, this study aims to provide a comprehensive assessment of GPT’s performance based on established key criteria. Using structured use cases, this study explores GPT’s strength and weaknesses in four construction safety areas: (1) delivering personalized safety training and educational content tailored to individual learner needs; (2) automatically analyzing post-accident reports to identify root causes and suggest preventive measures; (3) generating customized safety guidelines and checklists to support site compliance; and (4) providing real-time assistance for managing daily safety tasks and decision-making on construction sites. LLMs and NLP have already been employed in each of these four areas for improvement, making them suitable areas for further investigation. GPT demonstrated acceptable performance in delivering evidence-based, regulation-aligned responses, making it valuable for scaling personalized training, automating accident analyses, and developing safety protocols. Additionally, it provided real-time safety support through interactive dialogues. However, the model showed limitations in deeper critical analysis, extrapolating information, and adapting to dynamic environments. The study concludes that while GPT holds significant promise for enhancing construction safety, further refinement is necessary. This includes fine-tuning for more relevant safety-specific outcomes, integrating real-time data for contextual awareness, and developing a nuanced understanding of safety risks. These improvements, coupled with human oversight, could make GPT a robust tool for safety management. Full article
(This article belongs to the Special Issue Safety Management and Occupational Health in Construction)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop