AI-Driven Innovations for Construction Safety, Health, and Productivity
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 974
Special Issue Editors
Interests: earthquake engineering; civil engimeerimg; seismic resilience evaluation; optimization modelling
Interests: seismic resilience; transportation system; post-earthquake functionality; recovery decision-making; resilience design and enhancement
Interests: disaster prevention and mitigation for ultra-high voltage transmission lines; prefabricated and composite foundation failure mechanisms; multi-disaster response of wind turbine towers
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The development of artificial intelligence (AI) is revolutionizing the design, construction, and operation of built environments and, consequently, this Special Issue focuses on harnessing AI-driven methodologies to address critical challenges in construction safety, occupational health, and productivity. We invite cutting-edge research that leverages computational intelligence—including machine learning, deep neural networks, and optimization algorithms—to develop predictive models, real-time monitoring systems, and decision-support frameworks.
Contributions should explore topics such as those related to the following innovations:
- AI-enhanced risk assessmentfor seismic and disaster-resilient infrastructure;
- Dynamic resource optimizationfor safe construction workflows and rapid post-disaster recovery;
- Intelligent monitoring systems detecting structural vulnerabilities or worker health hazards;
- Data-driven frameworksimproving productivity through automated planning and logistics.
Emphasis will be placed on interdisciplinary approaches that bridge civil engineering, computer science, and systems resilience, and submissions may include case studies validating AI applications in healthcare facilities, transportation networks, or other critical infrastructure, aligning with global goals for sustainable and adaptive built environments.
This Special Issue aims to compile pioneering solutions that transform construction practices into safer, healthier, and more efficient processes through the power of AI.
Dr. Shunshun Pei
Dr. Jie Hu
Dr. Wenming Wang
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 250 words) can be sent to the Editorial Office for assessment.
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
- construction safety
- structural health monitoring
- seismic resilience
- optimization algorithms
- disaster management
- smart infrastructure
- productivity enhancement
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