{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T18:21:49Z","timestamp":1775672509343,"version":"3.50.1"},"reference-count":78,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T00:00:00Z","timestamp":1736553600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001839","name":"University Grants Committee","doi-asserted-by":"publisher","award":["T22-505\/19-N"],"award-info":[{"award-number":["T22-505\/19-N"]}],"id":[{"id":"10.13039\/501100001839","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52108480"],"award-info":[{"award-number":["52108480"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004377","name":"Hong Kong Polytechnic University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004377","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1016\/j.aei.2025.103117","type":"journal-article","created":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T17:56:53Z","timestamp":1737482213000},"page":"103117","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":24,"special_numbering":"PA","title":["AIoT-powered building digital twin for smart firefighting and super real-time fire forecast"],"prefix":"10.1016","volume":"65","author":[{"given":"Weikang","family":"Xie","sequence":"first","affiliation":[]},{"given":"Yanfu","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Xiaoning","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Ho Yin","family":"Wong","sequence":"additional","affiliation":[]},{"given":"Tianhang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zilong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xiqiang","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Jihao","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Xinyan","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Fu","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Asif","family":"Usmani","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2025.103117_b0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102114","article-title":"An ontology-based methodology to establish city information model of digital twin city by merging BIM GIS and IoT","volume":"57","author":"Shi","year":"2023","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.aei.2025.103117_b0010","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2023.3278267","article-title":"Digital twin for safety and security: perspectives on building lifecycle","author":"Khajavi","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.aei.2025.103117_b0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102346","article-title":"Developing an integrative framework for digital twin applications in the building construction industry: a systematic literature review","volume":"59","author":"Long","year":"2024","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2023.104785","article-title":"Digital twinning of civil infrastructures: current state of model architectures, interoperability solutions, and future prospects","volume":"149","author":"Naderi","year":"2023","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2025.103117_b0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102485","article-title":"Application of artificial intelligence in digital twin models for stormwater infrastructure systems in smart cities","volume":"61","author":"Sharifi","year":"2024","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0030","article-title":"Digital twin-driven intelligent operation and maintenance platform for large-scale hydro-steel structures","volume":"62","author":"Li","year":"2024","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0035","doi-asserted-by":"crossref","first-page":"16221","DOI":"10.1038\/s41598-022-20178-8","article-title":"Towards a digital twin for supporting multi-agency incident management in a smart city","volume":"12","author":"Wolf","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.aei.2025.103117_b0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.101951","article-title":"Multi-domain ubiquitous digital twin model for information management of complex infrastructure systems","volume":"56","author":"Jiang","year":"2023","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102085","article-title":"Data-driven approaches to built environment flood resilience: a scientometric and critical review","volume":"57","author":"Rathnasiri","year":"2023","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0050","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.jnlssr.2021.05.002","article-title":"Multi-hazard disaster scenario method and emergency management for urban resilience by integrating experiment\u2013simulation\u2013field data","volume":"2","author":"Ba","year":"2021","journal-title":"J. Safe. Sci. Resilience"},{"key":"10.1016\/j.aei.2025.103117_b0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2019.102889","article-title":"IAFSS agenda 2030 for a fire safe world","volume":"110","author":"McNamee","year":"2019","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0060","series-title":"Intelligent Building Fire Safety and Smart Firefighting","author":"Huang","year":"2024"},{"key":"10.1016\/j.aei.2025.103117_b0065","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1016\/j.jpdc.2010.06.005","article-title":"FireGrid: An e-infrastructure for next-generation emergency response support","volume":"70","author":"Han","year":"2010","journal-title":"J. Parallel Distrib. Comput."},{"key":"10.1016\/j.aei.2025.103117_b0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijdrr.2022.103412","article-title":"A review of critical fire event library for buildings and safety framework for smart firefighting","volume":"83","author":"Khan","year":"2022","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"10.1016\/j.aei.2025.103117_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2022.105258","article-title":"A spatial temporal graph neural network model for predicting flashover in arbitrary building floorplans","volume":"115","author":"Tam","year":"2022","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.aei.2025.103117_b0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2022.103579","article-title":"Real-time forecast of compartment fire and flashover based on deep learning","volume":"130","author":"Zhang","year":"2022","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0085","doi-asserted-by":"crossref","DOI":"10.1007\/s10694-021-01139-5","article-title":"Multi-wavelength densitometer for experimental research on the optical characteristics of smoke layers","author":"W\u0119grzy\u0144ski","year":"2021","journal-title":"Fire Technol."},{"key":"10.1016\/j.aei.2025.103117_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2022.103724","article-title":"Research on multi-detector real-time fire alarm technology based on signal similarity","volume":"136","author":"Yu","year":"2023","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0095","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1121\/10.0001415","article-title":"Change in acoustic impulse response of a room due to a fire","volume":"147","author":"Abbasi","year":"2020","journal-title":"J. Acoust. Soc. Am."},{"key":"10.1016\/j.aei.2025.103117_b0100","article-title":"Smart evaluation of building fire scenario and hazard by attenuation of alarm sound field","volume":"51","author":"Xiong","year":"2022","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0105","article-title":"Predicting transient building fire based on external smoke images and deep learning","volume":"47","author":"Wang","year":"2022","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.107939","article-title":"Forecasting backdraft with multimodal method: fusion of fire image and sensor data","volume":"132","author":"Zhang","year":"2024","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.aei.2025.103117_b0115","doi-asserted-by":"crossref","unstructured":"Schifiliti RP, Custer RLP, Meacham BJ. Design of Detection Systems. SFPE Handbook of Fire Protection Engineering, Fifth Edition, 2016, p. 1\u20133493.","DOI":"10.1007\/978-1-4939-2565-0_40"},{"key":"10.1016\/j.aei.2025.103117_b0120","article-title":"Generating synthetic sensor data to facilitate machine learning paradigm for prediction of building fire hazard","author":"Tam","year":"2020","journal-title":"Fire Technol."},{"key":"10.1016\/j.aei.2025.103117_b0125","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.1007\/s10694-023-01461-0","article-title":"Revisiting alpert\u2019s correlations: numerical exploration of early-stage building fire and detection","volume":"59","author":"Zeng","year":"2023","journal-title":"Fire Technol"},{"key":"10.1016\/j.aei.2025.103117_b0130","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1007\/s10694-022-01347-7","article-title":"Hybrid ensemble based machine learning for smart building fire detection using multi modal sensor data","volume":"59","author":"Jana","year":"2023","journal-title":"Fire Technol."},{"key":"10.1016\/j.aei.2025.103117_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.tust.2022.104639","article-title":"Numerical analysis of the performance of a PID control based real-time mechanical ventilation system to prevent smoke back-layering in tunnel fires","volume":"128","author":"Hong","year":"2022","journal-title":"Tunn. Undergr. Space Technol."},{"key":"10.1016\/j.aei.2025.103117_b0140","doi-asserted-by":"crossref","first-page":"3125","DOI":"10.1007\/s10694-020-01054-1","article-title":"Measuring water flow rate for a fire hose using a wireless sensor network for smart fire fighting","volume":"57","author":"Brown","year":"2021","journal-title":"Fire Technol."},{"key":"10.1016\/j.aei.2025.103117_b0145","doi-asserted-by":"crossref","unstructured":"Vigne G, Cantizano A, Ayala P, Rein G. Experimental and computational study of smoke dynamics from multiple fire sources inside a large-volume building 2021:1147\u201361.","DOI":"10.1007\/s12273-020-0715-1"},{"key":"10.1016\/j.aei.2025.103117_b0150","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.firesaf.2018.01.003","article-title":"A field experiment on fire spread within a group of model houses","volume":"96","author":"Himoto","year":"2018","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0155","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/0379-7112(94)90006-X","article-title":"The fire environment in a multi-room building\u2014comparison of predicted and experimental results","volume":"23","author":"Luo","year":"1994","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0160","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.jlp.2016.09.017","article-title":"A CFD based model to predict film boiling heat transfer of cryogenic liquids","volume":"44","author":"Ahammad","year":"2016","journal-title":"J. Loss Prev. Process Ind."},{"key":"10.1016\/j.aei.2025.103117_b0165","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1016\/S0360-1285(01)00005-3","article-title":"Computational fluid dynamics modeling of compartment fires","volume":"27","author":"Novozhilov","year":"2001","journal-title":"Prog. Energy Combust. Sci."},{"key":"10.1016\/j.aei.2025.103117_b0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2019.102854","article-title":"Compartment fire predictions using transpose convolutional neural networks","volume":"108","author":"Hodges","year":"2019","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0175","article-title":"AIoT-enabled digital twin system for smart tunnel fire safety management","volume":"18","author":"Zhang","year":"2024","journal-title":"Dev. Built Environ."},{"key":"10.1016\/j.aei.2025.103117_b0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.ssci.2021.105414","article-title":"Big data in safety management: An overview","volume":"143","author":"Wang","year":"2021","journal-title":"Saf. Sci."},{"key":"10.1016\/j.aei.2025.103117_b0185","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1139\/er-2020-0019","article-title":"A review of machine learning applications in wildfire science and management","volume":"28","author":"Jain","year":"2020","journal-title":"Environ. Rev."},{"key":"10.1016\/j.aei.2025.103117_b0190","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1016\/j.ijdrr.2017.09.037","article-title":"Emergency decision making for natural disasters: an overview","volume":"27","author":"Zhou","year":"2018","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"10.1016\/j.aei.2025.103117_b0195","series-title":"Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures","article-title":"Perspectives of Using Artificial Intelligence in Building Fire Safety","author":"Huang","year":"2022"},{"key":"10.1016\/j.aei.2025.103117_b0200","article-title":"Intelligent emergency digital twin system for monitoring building fire evacuation","volume":"77","author":"Ding","year":"2023","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0205","article-title":"Building Artificial-Intelligence Digital Fire (AID-Fire) system: a real-scale demonstration","volume":"62","author":"Zhang","year":"2022","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0210","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102030","article-title":"Digital twin and its potential applications in construction industry: State-of-art review and a conceptual framework","volume":"57","author":"Su","year":"2023","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0215","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102614","article-title":"Automated fire risk assessment and mitigation in building blueprints using computer vision and deep generative models","volume":"62","author":"Chen","year":"2024","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102097","article-title":"Fire propagation-driven dynamic intelligent evacuation model in multifloor hybrid buildings","volume":"57","author":"Li","year":"2023","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0225","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.aei.2018.04.015","article-title":"A BIM-based visualization and warning system for fire rescue","volume":"37","author":"Chen","year":"2018","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0230","doi-asserted-by":"crossref","first-page":"2292","DOI":"10.1016\/j.comnet.2008.04.002","article-title":"Wireless sensor network survey","volume":"52","author":"Yick","year":"2008","journal-title":"Comput. Netw."},{"key":"10.1016\/j.aei.2025.103117_b0235","series-title":"Handbook of Modern Sensors: Physics, Designs, and Applications","author":"Fraden","year":"2010"},{"key":"10.1016\/j.aei.2025.103117_b0240","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1111\/j.1551-2916.2009.02990.x","article-title":"Negative temperature coefficient resistance (NTCR) ceramic thermistors: an industrial perspective","volume":"92","author":"Feteira","year":"2009","journal-title":"J. Am. Ceram. Soc."},{"key":"10.1016\/j.aei.2025.103117_b0245","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.autcon.2013.09.005","article-title":"Measurement of the smoke layer interface in fires","volume":"37","author":"Yao","year":"2014","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2025.103117_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2022.112394","article-title":"Investigation of calibration equations for NTC thermistors utilized in the deep-ocean temperature range","volume":"207","author":"Li","year":"2023","journal-title":"Measurement"},{"key":"10.1016\/j.aei.2025.103117_b0255","doi-asserted-by":"crossref","first-page":"3104","DOI":"10.3923\/jas.2011.3104.3116","article-title":"Wireless sensor actor network based on fuzzy inference system for greenhouse climate control","volume":"11","author":"Naseer","year":"2011","journal-title":"J. Appl. Sci."},{"key":"10.1016\/j.aei.2025.103117_b0260","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1109\/MCOM.2010.5473869","article-title":"Wireless home automation networks: a survey of architectures and technologies","volume":"48","author":"Gomez","year":"2010","journal-title":"IEEE Commun. Mag."},{"key":"10.1016\/j.aei.2025.103117_b0265","doi-asserted-by":"crossref","DOI":"10.1016\/j.adhoc.2021.102625","article-title":"Energy-aware system design for batteryless LPWAN devices in IoT applications","volume":"122","author":"Yuksel","year":"2021","journal-title":"Ad Hoc Netw."},{"key":"10.1016\/j.aei.2025.103117_b0270","doi-asserted-by":"crossref","DOI":"10.1016\/j.ssci.2023.106363","article-title":"Machine learning and deep learning for safety applications: Investigating the intellectual structure and the temporal evolution","volume":"170","author":"Leoni","year":"2024","journal-title":"Saf. Sci."},{"key":"10.1016\/j.aei.2025.103117_b0275","doi-asserted-by":"crossref","DOI":"10.1016\/j.combustflame.2021.111934","article-title":"An improved approach towards more robust deep learning models for chemical kinetics","volume":"238","author":"Han","year":"2022","journal-title":"Combust. Flame"},{"key":"10.1016\/j.aei.2025.103117_b0280","doi-asserted-by":"crossref","unstructured":"Zhang J, Zheng Y, Qi D, Li R, Yi X. DNN-based prediction model for spatio-temporal data. Proceedings of the 24th ACM SIGSPATIAL international conference on advances in geographic information systems, 2016, p. 1\u20134.","DOI":"10.1145\/2996913.2997016"},{"key":"10.1016\/j.aei.2025.103117_b0285","article-title":"Enabling fire source localization in building fire emergencies with a machine learning-based inverse modeling approach","volume":"78","author":"Fang","year":"2023","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0290","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2021.103469","article-title":"Development of a machine-learning approach for identifying the stages of fire development in residential room fires","volume":"126","author":"Fang","year":"2021","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0295","article-title":"Smart fire detection analysis in complex building floorplans powered by GAN","volume":"79","author":"Zeng","year":"2023","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0300","doi-asserted-by":"crossref","first-page":"4115","DOI":"10.1016\/j.proci.2022.07.062","article-title":"Predicting real-time fire heat release rate by flame images and deep learning","volume":"39","author":"Wang","year":"2023","journal-title":"Proc. Combust. Inst."},{"key":"10.1016\/j.aei.2025.103117_b0305","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.neucom.2017.04.083","article-title":"Early fire detection using convolutional neural networks during surveillance for effective disaster management","volume":"288","author":"Muhammad","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.aei.2025.103117_b0310","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1007\/s10694-020-00985-z","article-title":"Smart detection of fire source in tunnel based on the numerical database and artificial intelligence","volume":"57","author":"Wu","year":"2021","journal-title":"Fire Technol."},{"key":"10.1016\/j.aei.2025.103117_b0315","article-title":"AI-powered fire engineering design and smoke flow analysis for complex-shaped buildings","author":"Zeng","year":"2024","journal-title":"J. Comput. Des. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0320","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.119899","article-title":"Real-time flashover prediction model for multi-compartment building structures using attention based recurrent neural networks","volume":"223","author":"Tam","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.aei.2025.103117_b0325","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S1474-0346(02)00009-5","article-title":"Probabilistic inference with maximum entropy for prediction of flashover in single compartment fire","volume":"16","author":"Lee","year":"2002","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0330","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2022.113298","article-title":"Phenomenological characteristics and flame radiation of dynamically evolving oil spill fires in a sealed ship engine room","volume":"267","author":"Liu","year":"2023","journal-title":"Ocean Eng."},{"key":"10.1016\/j.aei.2025.103117_b0335","article-title":"Real-time spatiotemporal forecast of natural gas jet fire from offshore platform by using deep probability learning","author":"Xie","year":"2024","journal-title":"Ocean Eng."},{"key":"10.1016\/j.aei.2025.103117_b0340","article-title":"Real-time plume tracking using transfer learning approach","volume":"108172","author":"Shi","year":"2023","journal-title":"Comput. Chem. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0345","unstructured":"Grieves M. Digital twin of physical systems: opportunities and challenges. Proceedings of the ASME 2002 International Mechanical Engineering Congress and Exposition, 2002, p. 17\u201322."},{"key":"10.1016\/j.aei.2025.103117_b0350","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.jmsy.2020.06.017","article-title":"Review of digital twin about concepts, technologies, and industrial applications","volume":"58","author":"Liu","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.aei.2025.103117_b0355","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.procir.2017.03.309","article-title":"M2DDM\u2013a maturity model for data-driven manufacturing","volume":"63","author":"Weber","year":"2017","journal-title":"Procedia CIRP"},{"key":"10.1016\/j.aei.2025.103117_b0360","article-title":"Digital twin empowered industrial IoT based on credibility-weighted swarm learning","author":"Xiang","year":"2023","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.aei.2025.103117_b0365","doi-asserted-by":"crossref","DOI":"10.1016\/j.cma.2020.112907","article-title":"A machine-learning framework for rapid adaptive digital-twin based fire-propagation simulation in complex environments","volume":"363","author":"Zohdi","year":"2020","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0370","article-title":"A real-time intelligent monitoring method for indoor evacuee distribution based on deep learning and spatial division","volume":"92","author":"Han","year":"2024","journal-title":"J. Build. Eng."},{"key":"10.1016\/j.aei.2025.103117_b0375","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.enbuild.2014.02.083","article-title":"Influence of fire power and window position on smoke movement mechanisms and temperature distribution in an emergency staircase","volume":"79","author":"Shi","year":"2014","journal-title":"Energ. Build."},{"key":"10.1016\/j.aei.2025.103117_b0380","unstructured":"McGrattan K, Hostikka S, McDermott R, Floyd J, Weinschenk C, Overholt K. Fire Dynamics Simulator User\u2019s Guide, FDS Version 6.2. 0, SVN Repository Revision: 22352. NIST Special Publication 2015;1019."},{"key":"10.1016\/j.aei.2025.103117_b0385","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2023.103891","article-title":"Automatic real-time fire distance , size and power measurement driven by stereo camera and deep learning","volume":"140","author":"Wang","year":"2023","journal-title":"Fire Saf. J."},{"key":"10.1016\/j.aei.2025.103117_b0390","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10694-021-01153-7","article-title":"Automation in fire safety engineering using BIM and generative design","volume":"58","author":"Lovreglio","year":"2022","journal-title":"Fire Technol."}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034625000102?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034625000102?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T20:32:05Z","timestamp":1762547525000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034625000102"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":78,"alternative-id":["S1474034625000102"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2025.103117","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2025,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"AIoT-powered building digital twin for smart firefighting and super real-time fire forecast","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2025.103117","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"103117"}}