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Computer Vision for Fire Detection on UAVs—From Software to Hardware

Computer Science Department, International Hellenic University, 65404 Kavala, Greece
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Academic Editors: Remus Brad and Arpad Gellert
Future Internet 2021, 13(8), 200; https://doi.org/10.3390/fi13080200
Received: 17 June 2021 / Revised: 29 July 2021 / Accepted: 29 July 2021 / Published: 31 July 2021
(This article belongs to the Special Issue Computer Vision, Deep Learning and Machine Learning with Applications)
Fire hazard is a condition that has potentially catastrophic consequences. Artificial intelligence, through Computer Vision, in combination with UAVs has assisted dramatically to identify this risk and avoid it in a timely manner. This work is a literature review on UAVs using Computer Vision in order to detect fire. The research was conducted for the last decade in order to record the types of UAVs, the hardware and software used and the proposed datasets. The scientific research was executed through the Scopus database. The research showed that multi-copters were the most common type of vehicle and that the combination of RGB with a thermal camera was part of most applications. In addition, the trend in the use of Convolutional Neural Networks (CNNs) is increasing. In the last decade, many applications and a wide variety of hardware and methods have been implemented and studied. Many efforts have been made to effectively avoid the risk of fire. The fact that state-of-the-art methodologies continue to be researched, leads to the conclusion that the need for a more effective solution continues to arouse interest. View Full-Text
Keywords: UAV; Computer Vision; fire detection; wildfire; smoke UAV; Computer Vision; fire detection; wildfire; smoke
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MDPI and ACS Style

Moumgiakmas, S.S.; Samatas, G.G.; Papakostas, G.A. Computer Vision for Fire Detection on UAVs—From Software to Hardware. Future Internet 2021, 13, 200. https://doi.org/10.3390/fi13080200

AMA Style

Moumgiakmas SS, Samatas GG, Papakostas GA. Computer Vision for Fire Detection on UAVs—From Software to Hardware. Future Internet. 2021; 13(8):200. https://doi.org/10.3390/fi13080200

Chicago/Turabian Style

Moumgiakmas, Seraphim S., Gerasimos G. Samatas, and George A. Papakostas 2021. "Computer Vision for Fire Detection on UAVs—From Software to Hardware" Future Internet 13, no. 8: 200. https://doi.org/10.3390/fi13080200

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