Intelligent Fire Safety Solutions in Urban Architecture: Innovations and Challenges

Dear Colleagues,

The accelerating pace of global urbanization has precipitated a dramatic rise in high-rise buildings and densely populated urban environments, amplifying the complexity and possibility of fire-related risks. Traditional fire safety systems, reliant on reactive measures and fragmented data, struggle to address the dynamic threats posed by modern architectural designs, energy-intensive infrastructures, and complex human occupancy patterns. The scientific evolution toward intelligent fire safety solutions leverages cutting-edge technologies—such as artificial intelligence (AI), big data, digital twins, Internet of Things (IoT), cloud computing and advanced algorithms—to transform fire risk management from passive reaction to proactive response. These innovations are not merely incremental improvements but represent a paradigm shift in urban safety frameworks, enabling real-time risk assessment, autonomous decision-making, and adaptive evacuation planning in ways previously unattainable. As high-rise structures—characterized by elongated vertical escape routes, heterogeneous occupant mobility, and rapid fire-spread dynamics—have witnessed escalating incidents globally, the real-world imperative for such advancements is starkly evident. As cities march toward "smart urban futures", intelligent fire safety must transcend technological novelty to deliver scalable, human-centric resilience. It necessitates interdisciplinary collaboration—spanning data science, materials engineering, behavioral psychology, and policy reform—to turn theoretical innovations into lifesaving urban realities. The stakes are nothing less than the sustainable survival of our urban landscapes.

This Special Issue, "Intelligent Fire Safety Solutions in Urban Architecture: Innovations and Challenges", seeks to compile cutting-edge research and critical perspectives on the integration of advanced technologies—including AI, IoT, digital twins, and predictive analytics—into urban fire safety ecosystems. As cities worldwide grapple with escalating fire risks in high-density, complex-built environments, this Special Issue aims to carry out the following:

Disseminate Technological Innovations: Showcase novel frameworks for real-time fire detection, risk prediction, evacuation optimization, and resilient infrastructure design.

Address Multidisciplinary Challenges: Investigate technical bottlenecks (e.g., data fusion, system interoperability), human behavioral factors, regulatory gaps, and scalability barriers.

Bridge Theory and Practice: Highlight case studies validating intelligent systems’ efficacy in reducing response times, minimizing casualties, and enhancing urban safety governance.

Foster Cross-Domain Synergies: Promote dialog among researchers in computer science, civil engineering, urban planning, social sciences, and policymaking to co-design human-centric solutions.

By curating high-impact contributions, this Special Issue will chart a roadmap toward next-generation fire resilience—transforming urban landscapes into safer, more adaptive, and sustainable habitats. It exhibits strong thematic alignment with the expanded scope of Fire, which now explicitly encompasses building-scale fire science alongside its traditional focus on landscape fires. While the journal originated in fire ecology, its current mandate actively welcomes research on "technical solutions for fire safety" inside structures—including smart detection systems, smoke/heat modeling, and emerging risks like battery fires—directly overlapping with the Special Issue’s core focus on AI-driven urban fire resilience. Furthermore, the Special Issue bridges Fire’s interest in interdisciplinary science–policy interfaces by addressing human behavioral factors, regulatory frameworks, and community-centric evacuation strategies, resonating with the journal’s call for studies linking technology with governance and societal impacts. Crucially, it also supports Fire’s goal to "bridge vegetation/landscape fires and building fires" by exploring urban–wildfire interfaces (e.g., protecting smart buildings against ember attacks) and cross-applicable models (e.g., predictive algorithms adaptable to both forest fires and high-rise emergencies). Through empirical validations of intelligent systems—from digital twins to IoT-enabled evacuation—this Special Issue advances the journal’s mission to translate scientific innovation into actionable policies for safer communities and environments.

This Special Issue seeks cutting-edge contributions that advance AI-driven, IoT-enabled, and human-centric fire resilience in dense urban settings. Key topics include real-time fire prediction systems for high-rises and battery hazards, adaptive evacuation frameworks leveraging sensor networks and digital twins, and robotics for precision firefighting. We particularly encourage studies on fire–urban interface protection using smart technologies, cross-disciplinary fire models bridging building and landscape dynamics, and policy–socioeconomic analyses addressing regulatory gaps and scalability barriers. Submissions should validate intelligent solutions—from energy-efficient fire safety in sustainable architecture to cost-effective retrofitting of legacy infrastructure—while emphasizing empirical performance gains, human behavioral factors, and pathways toward scalable urban safety transformation. This Special Issue welcomes but is not limited to the following topics:

AI-Driven Fire Prediction in High-Density Urban Areas: Machine learning models for real-time fire risk assessment in skyscrapers, accounting for occupant behavior, building materials, and electrical/battery hazards.

IoT-Enabled Dynamic Evacuation Systems: Sensor networks and adaptive algorithms for optimizing escape routes in complex structures (e.g., hospitals, malls), integrating real-time smoke spread simulations.

Digital Twin Frameworks for Fire Resilience: Integration of BIM, GIS, and real-time monitoring to simulate fire scenarios, test interventions, and enhance structural response planning.

Human-Centric AI for Emergency Decision-Making: Behavioral psychology-informed AI systems that predict panic dynamics and customize alerts/guidance for diverse populations (elderly, disabled, children).

Battery Fire Mitigation in Smart Buildings: Early detection and containment strategies for Li-ion battery fires in EV charging stations, energy storage systems, and high-rise apartments.

Wildfire-Urban Interface (WUI) Protection via Smart Technologies: AI-powered ember detection, automated sprinkler systems, and fire-resistant materials for buildings in peri-urban zones vulnerable to landscape fires.

Robotics and Autonomous Systems for Firefighting: Drones/UAVs for indoor/outdoor fire mapping, heat-resistant robots for search/rescue, and human–robot collaboration in hazardous environments.

Data Fusion for Multi-Hazard Early Warning: Cross-domain sensor integration (fire, earthquake, flood) to prioritize responses and reduce false alarms in smart city infrastructures.

Policy and Regulatory Frameworks for Intelligent Fire Safety: Legal liability, standardization gaps, and governance models for deploying AI/IoT systems across jurisdictions.

Energy-Efficient Fire Safety in Sustainable Architecture: Conflict resolution between net-zero goals (e.g., timber construction) and fire safety, using predictive analytics to balance sustainability with risk.

Cost–Benefit Analysis of Smart Fire Solutions: Economic scalability of retrofitting legacy buildings with intelligent systems versus new constructions, especially in developing economies.

Cross-Disciplinary Fire Models: Unified computational frameworks adaptable to both urban fires (e.g., high-rise smoke transport) and landscape fires (e.g., wildfire ember propagation).

Based on the scope of the Special Issue, we mainly encourage full-length articles and communications. Review articles that contribute adequate scientific value may also be considered.

Dr. Xueming Shu
Prof. Dr. Changkun Chen
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.

• urban fire resilience
• smart firefighting
• fire hazard evaluation
• community risk reduction
• evacuation dynamics
• sustainable governance