Intelligent Structural Fire Safety Monitoring: AIoT, Digital Twins, and Advanced Sensing Technologies
A special issue of Fire (ISSN 2571-6255). This special issue belongs to the section "Fire Risk Assessment and Safety Management in Buildings and Urban Spaces".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 2
Special Issue Editors
Interests: structural fire performance of bridges; fire dynamics simulation; intelligent disaster prevention of tunnel and bridge infrastructures
Special Issues, Collections and Topics in MDPI journals
Interests: fire resistance of building structures; disaster prevention and mitigation of major infrastructure; large-scale hydrogen storage and transportation
Interests: early warning of fire-induced collapse of large steel structures; shape and topology optimization of skeleton structures; reinforcement learning-driven automatic design of structures
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Fire safety is a critical global challenge, especially with recent urbanization, increasingly complex infrastructure constructions, and the exacerbating effects of climate change. Traditional fire detection methods often suffer from delayed alerts, high false alarm rates, and an inability to predict or mitigate evolving hazards. The rapid development of cutting-edge technologies—such as artificial intelligence of things (AIoT), digital twin (DT), and advanced sensing technologies—offers promising solutions. AIoT integrates edge computing and machine learning to enable real-time, intelligent decision-making from distributed sensor networks. Digital twins create dynamic virtual replicas of physical environments, simulating fire spread, structural integrity, and evacuation scenarios using real-time data. Enhanced sensing technologies capture environmental parameters, temperature gradients, toxic gas concentrations, and structural stress for instance. The application of these new technologies is vital for safeguarding lives, infrastructure, and ecosystems.
We are pleased to invite you to submit a paper to the Special Issue of Fire, entitled “Intelligent Structural Fire Safety Monitoring: AIoT, Digital Twins, and Advanced Sensing Technologies”. This Special Issue aims to compile recent advances in the innovative application of new technologies in fire safety monitoring and alerting, including artificial intelligence (AI), internet of things (IoT), digital twins, and advanced sensing systems. Fire scenarios may occur in a variety of settings, including buildings, bridges, metros, tunnels or other infrastructures, as well as in ships or chemical plants. The objectives of safety monitoring and alerting include achieving more accurate and timely fire detection, predicting fire spread, providing structural safety alerts, and forecasting structural behavior.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Intelligent monitoring and alerting methods in fire safety engineering.
- Application of artificial intelligence/machine learning/deep learning in fire safety engineering.
- Preparation and presentation of databases for fire detection training, validation, and testing.
- Fire monitoring and alerting methods validation and testing.
- Integrating artificial intelligence and internet of things in fire monitoring and safety alerting.
- Digital twin architecture enabling real-time visualization and simulation of fire dynamics.
- Advanced sensor networks for data collection or fire monitoring.
- Fire detection, monitoring, and alerting methods for fires occurring in buildings, bridges, metros, tunnels, ships, chemical plants, or other infrastructures.
Structural safety monitoring, alerting, and evaluation for buildings, bridges, metros, tunnels, or other infrastructures during fire events.
Dr. Xiqiang Wu
Prof. Dr. Jian Jiang
Dr. Shaojun Zhu
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. Fire 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 2400 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
- fire safety engineering
- structural fire safety
- artificial intelligence
- machine learning
- deep learning
- digital twin
- sensor network
- fire detection
- fire monitoring
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