{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:58:24Z","timestamp":1785459504391,"version":"3.56.0"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:00:00Z","timestamp":1780358400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Array"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.array.2026.100983","type":"journal-article","created":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T15:45:24Z","timestamp":1780760724000},"page":"100983","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A resource-efficient system for rapid and accurate forest fire smoke detection using Video-based Multiple Object Kinetic Emission Detection"],"prefix":"10.1016","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8280-7011","authenticated-orcid":false,"given":"Vinh","family":"Vu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8924-4356","authenticated-orcid":false,"given":"Dat","family":"Tran-Anh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9467-4978","authenticated-orcid":false,"given":"Cong","family":"Tran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"13","key":"10.1016\/j.array.2026.100983_b1","doi-asserted-by":"crossref","DOI":"10.1029\/2022GL100687","article-title":"Human-driven fire regime change in the seasonal tropical forests of central Vietnam","volume":"50","author":"Nguyen","year":"2023","journal-title":"Geophys Res Lett"},{"key":"10.1016\/j.array.2026.100983_b2","series-title":"International conference on innovative computing and communications: proceedings of ICICC 2018, volume 1","first-page":"323","article-title":"Forest fire detection system using IoT and artificial neural network","author":"Dubey","year":"2019"},{"key":"10.1016\/j.array.2026.100983_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.scs.2020.102332","article-title":"An integrated fire detection system using IoT and image processing technique for smart cities","volume":"61","author":"Sharma","year":"2020","journal-title":"Sustain Cities Soc"},{"key":"10.1016\/j.array.2026.100983_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.nanoen.2020.104843","article-title":"Self-powered forest fire alarm system based on impedance matching effect between triboelectric nanogenerator and thermosensitive sensor","volume":"73","author":"Liu","year":"2020","journal-title":"Nano Energy"},{"key":"10.1016\/j.array.2026.100983_b5","series-title":"2019 1st international conference on industrial artificial intelligence","first-page":"1","article-title":"A deep learning based forest fire detection approach using UAV and YOLOv3","author":"Jiao","year":"2019"},{"key":"10.1016\/j.array.2026.100983_b6","doi-asserted-by":"crossref","DOI":"10.1016\/j.imavis.2019.08.007","article-title":"Intelligent and vision-based fire detection systems: A survey","volume":"91","author":"Bu","year":"2019","journal-title":"Image Vis Comput"},{"key":"10.1016\/j.array.2026.100983_b7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.comcom.2019.10.007","article-title":"Unmanned aerial vehicle (UAV) based forest fire detection and monitoring for reducing false alarms in forest-fires","volume":"149","author":"Sudhakar","year":"2020","journal-title":"Comput Commun"},{"issue":"7","key":"10.1016\/j.array.2026.100983_b8","doi-asserted-by":"crossref","first-page":"4345","DOI":"10.1016\/j.jksuci.2021.04.013","article-title":"Classification of bird sounds as an early warning method of forest fires using convolutional neural network (CNN) algorithm","volume":"34","author":"Permana","year":"2022","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"10.1016\/j.array.2026.100983_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2024.104511","article-title":"YOLO-EPF: Multi-scale smoke detection with enhanced pool former and multiple receptive fields","volume":"149","author":"Yin","year":"2024","journal-title":"Digit Signal Process"},{"issue":"1","key":"10.1016\/j.array.2026.100983_b10","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s42408-022-00165-0","article-title":"Forest fire and smoke detection using deep learning-based learning without forgetting","volume":"19","author":"Sathishkumar","year":"2023","journal-title":"Fire Ecol"},{"issue":"6","key":"10.1016\/j.array.2026.100983_b11","doi-asserted-by":"crossref","first-page":"1841","DOI":"10.1007\/s11676-022-01461-w","article-title":"Smoke root detection from video sequences based on multi-feature fusion","volume":"33","author":"Lou","year":"2022","journal-title":"J For Res"},{"key":"10.1016\/j.array.2026.100983_b12","doi-asserted-by":"crossref","first-page":"154732","DOI":"10.1109\/ACCESS.2019.2946712","article-title":"An attention enhanced bidirectional LSTM for early forest fire smoke recognition","volume":"7","author":"Cao","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.array.2026.100983_b13","series-title":"2021 international conference on information and communication technology convergence","first-page":"593","article-title":"Investigation of deep learning method for fire detection from videos","author":"Vu","year":"2021"},{"issue":"7","key":"10.1016\/j.array.2026.100983_b14","doi-asserted-by":"crossref","first-page":"10261","DOI":"10.1007\/s11042-021-11766-3","article-title":"STCNet: spatiotemporal cross network for industrial smoke detection","volume":"81","author":"Cao","year":"2022","journal-title":"Multimedia Tools Appl"},{"issue":"22","key":"10.1016\/j.array.2026.100983_b15","doi-asserted-by":"crossref","first-page":"29283","DOI":"10.1007\/s11042-018-5978-5","article-title":"Real-time video fire smoke detection by utilizing spatial-temporal ConvNet features","volume":"77","author":"Hu","year":"2018","journal-title":"Multimedia Tools Appl"},{"issue":"13","key":"10.1016\/j.array.2026.100983_b16","doi-asserted-by":"crossref","first-page":"9349","DOI":"10.1007\/s00521-023-08260-2","article-title":"A hybrid method for fire detection based on spatial and temporal patterns","volume":"35","author":"de Ven\u00e2ncio","year":"2023","journal-title":"Neural Comput Appl"},{"issue":"13","key":"10.1016\/j.array.2026.100983_b17","doi-asserted-by":"crossref","first-page":"4374","DOI":"10.3390\/s24134374","article-title":"A lightweight cross-layer smoke-aware network","volume":"24","author":"Wang","year":"2024","journal-title":"Sensors"},{"issue":"5","key":"10.1016\/j.array.2026.100983_b18","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1007\/s10694-020-00986-y","article-title":"Video flame and smoke based fire detection algorithms: A literature review","volume":"56","author":"Gaur","year":"2020","journal-title":"Fire Technol"},{"key":"10.1016\/j.array.2026.100983_b19","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s10846-018-0803-y","article-title":"Learning-based smoke detection for unmanned aerial vehicles applied to forest fire surveillance","volume":"93","author":"Yuan","year":"2019","journal-title":"J Intell Robot Syst"},{"key":"10.1016\/j.array.2026.100983_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2019.105029","article-title":"Real-time forest smoke detection using hand-designed features and deep learning","volume":"167","author":"Peng","year":"2019","journal-title":"Comput Electron Agric"},{"key":"10.1016\/j.array.2026.100983_b21","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1007\/s11554-020-01044-0","article-title":"Real-time video fire\/smoke detection based on CNN in antifire surveillance systems","volume":"18","author":"Saponara","year":"2021","journal-title":"Comput Electron AJ Real-Time Image Process Gric"},{"key":"10.1016\/j.array.2026.100983_b22","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108219","article-title":"Fast forest fire smoke detection using MVMNet","volume":"241","author":"Hu","year":"2022","journal-title":"Knowl-Based Syst"},{"key":"10.1016\/j.array.2026.100983_b23","article-title":"Advanced wildfire detection using generative adversarial network-based augmented datasets and weakly supervised object localization","volume":"114","author":"Park","year":"2022","journal-title":"Int J Appl Earth Obs Geoinf."},{"issue":"6","key":"10.1016\/j.array.2026.100983_b24","doi-asserted-by":"crossref","first-page":"2085","DOI":"10.1007\/s11554-021-01094-y","article-title":"A real-time video smoke detection algorithm based on Kalman filter and CNN","volume":"18","author":"Gagliardi","year":"2021","journal-title":"Comput Electron AJ Real-Time Image Process Gric."},{"key":"10.1016\/j.array.2026.100983_b25","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.isprsjprs.2022.01.013","article-title":"A survey on vision-based outdoor smoke detection techniques for environmental safety","volume":"185","author":"Chaturvedi","year":"2022","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"10.1016\/j.array.2026.100983_b26","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.firesaf.2019.03.004","article-title":"Video smoke detection based on deep saliency network","volume":"105","author":"Xu","year":"2019","journal-title":"Fire Saf J"},{"issue":"11","key":"10.1016\/j.array.2026.100983_b27","doi-asserted-by":"crossref","first-page":"8539","DOI":"10.1007\/s00521-021-06606-2","article-title":"QuasiVSD: efficient dual-frame smoke detection","volume":"34","author":"Cao","year":"2022","journal-title":"Neural Comput Appl"},{"key":"10.1016\/j.array.2026.100983_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.124783","article-title":"Fire and smoke detection from videos: A literature review under a novel taxonomy","volume":"255","author":"Gragnaniello","year":"2024","journal-title":"Expert Syst Appl"},{"key":"10.1016\/j.array.2026.100983_b29","series-title":"Wildfire rank definitions","author":"Government of British Columbia","year":"2025"},{"key":"10.1016\/j.array.2026.100983_b30","series-title":"PP-YOLOE: An evolved version of YOLO","author":"Xu","year":"2022"},{"key":"10.1016\/j.array.2026.100983_b31","series-title":"International workshop on deep learning in medical image analysis","first-page":"240","article-title":"Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations","author":"Sudre","year":"2017"},{"key":"10.1016\/j.array.2026.100983_b32","series-title":"YOLOv5: A state-of-the-art real-time object detection system","author":"Ultralytics","year":"2021"},{"key":"10.1016\/j.array.2026.100983_b33","series-title":"European conference on computer vision","first-page":"1","article-title":"YOLOv9: Learning what you want to learn using programmable gradient information","author":"Wang","year":"2024"},{"key":"10.1016\/j.array.2026.100983_b34","series-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"}],"container-title":["Array"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626003061?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626003061?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:01:59Z","timestamp":1785456119000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2590005626003061"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":34,"alternative-id":["S2590005626003061"],"URL":"https:\/\/doi.org\/10.1016\/j.array.2026.100983","relation":{},"ISSN":["2590-0056"],"issn-type":[{"value":"2590-0056","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A resource-efficient system for rapid and accurate forest fire smoke detection using Video-based Multiple Object Kinetic Emission Detection","name":"articletitle","label":"Article Title"},{"value":"Array","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.array.2026.100983","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"100983"}}