Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning

dc.authorscopusid59347773900
dc.authorscopusid57189388538
dc.authorscopusid57209876827
dc.contributor.authorOzel, Berk
dc.contributor.authorAlam, Muhammad Shahab
dc.contributor.authorKhan, Muhammad Umer
dc.contributor.otherMechatronics Engineering
dc.date.accessioned2024-11-05T20:18:59Z
dc.date.available2024-11-05T20:18:59Z
dc.date.issued2024
dc.departmentAtılım Universityen_US
dc.department-temp[Ozel, Berk; Khan, Muhammad Umer] Atilim Univ, Dept Mechatron Engn, TR-06830 Ankara, Turkiye; [Alam, Muhammad Shahab] Gebze Tech Univ, Def Technol Inst, TR-41400 Gebze, Turkiyeen_US
dc.description.abstractFire detection and extinguishing systems are critical for safeguarding lives and minimizing property damage. These systems are especially vital in combating forest fires. In recent years, several forest fires have set records for their size, duration, and level of destruction. Traditional fire detection methods, such as smoke and heat sensors, have limitations, prompting the development of innovative approaches using advanced technologies. Utilizing image processing, computer vision, and deep learning algorithms, we can now detect fires with exceptional accuracy and respond promptly to mitigate their impact. In this article, we conduct a comprehensive review of articles from 2013 to 2023, exploring how these technologies are applied in fire detection and extinguishing. We delve into modern techniques enabling real-time analysis of the visual data captured by cameras or satellites, facilitating the detection of smoke, flames, and other fire-related cues. Furthermore, we explore the utilization of deep learning and machine learning in training intelligent algorithms to recognize fire patterns and features. Through a comprehensive examination of current research and development, this review aims to provide insights into the potential and future directions of fire detection and extinguishing using image processing, computer vision, and deep learning.en_US
dc.description.sponsorshipThis research received no external funding.en_US
dc.description.woscitationindexEmerging Sources Citation Index
dc.identifier.doi10.3390/info15090538
dc.identifier.issn2078-2489
dc.identifier.issue9en_US
dc.identifier.scopus2-s2.0-85205255797
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.3390/info15090538
dc.identifier.urihttps://hdl.handle.net/20.500.14411/10253
dc.identifier.volume15en_US
dc.identifier.wosWOS:001323578100001
dc.institutionauthorKhan, Muhammad Umer
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectartificial intelligenceen_US
dc.subjectdeep learningen_US
dc.subjectdetectionen_US
dc.subjectfireen_US
dc.subjectflameen_US
dc.subjectforest fireen_US
dc.subjectsmokeen_US
dc.subjectwildfireen_US
dc.titleReview of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learningen_US
dc.typeReviewen_US
dspace.entity.typePublication
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relation.isOrgUnitOfPublication.latestForDiscoverycfebf934-de19-4347-b1c4-16bed15637f7

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