Artificial Intelligence in 3D Fire Modeling and Simulation

Dear Colleagues,

Artificial Intelligence (AI) is increasingly used in 3D fire modeling and simulation to enhance fire safety, enabling real-time fire prediction, smoke movement analysis, and improved rescue plans. In fact, accurately predicting fire growth and exchanging real-time information about onsite conditions and resources are essential for improving fire risk monitoring and firefighting with increased intelligence and dependability. By using the most recent data communication and modeling techniques to create a functional and interactive virtual representation of real-world items or activities, digital twins offer a potential solution that replicates the geometrical or semantic qualities and behavior patterns of objects. Nonetheless, AI mathematical models, trained on simulated events and real-world data, can predict burning settings, flame dimensions, and spread in real-time scenarios. These models can visualize the 3D fire scene, thus assisting in firefighting and emergency safeguard actions. This is extremely important for critical occurrences with huge smoke layering phenomena.

Moreover, AI algorithms can be used in fire engineering design to predict smoke motion in structures with complex 3D shapes. AI models' assumptions may be compared with Computational Fluid Dynamics (CFD) role modeling to show their efficiency and accuracy.

This Special Issue invites submissions for papers that cover all elements of real-time fire prediction and model simulation, smoke movement analysis, early fire detection, as well as advanced artificial intelligence-based fire detection systems. The following topics are included but are not limited to:

1. Real-time Fire Prediction and Model Simulation: including AI-powered digital twins, visualizing 3D fire scenes, deep learning for fast processing, and AI-assisted design.
2. Smoke Movement Analysis: Predicting smoke flow: AI models trained on numerical databases of fire simulations to predict smoke movement in buildings and comparison with CFD modeling.
3. Early Fire Detection: AI-powered early detection systems with improved accuracy and segmentation models related to smoke and flame detection.
4. Smart building fire safety design: AI could be deployed to design smart building models with enhanced fire safety execution features.
5. Fire and cloud devices: AI may create smart egress systems and locate fire origins through using cloud-based residential and consumer devices. Data gathering and analysis: AI can be used to gather and examine fire-related data, resulting in improved comprehension and preventative measures. Behavioral models: AI may be used to simulate how people will behave in emergency situations, which can assist evacuation preparations to be more effective.

We look forward to receiving your contributions.

Dr. José M. P. do Nascimento
Dr. Houda Harkat
Dr. João Pedro Matos-Carvalho
Dr. Hasmath Farhana Thariq Ahmed
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.

• fire detection
• flames
• machine learning
• artificial intelligence
• 3D fire
• 3D shape
• digital twins