Analysis of Machine Learning Methods for Wildfire Security Monitoring with an Unmanned Aerial Vehicles

The article is about the methods of machine learning, designed for the detection of wildfires using unmanned aerial vehicles. In the article presented the review of machine learning methods, described the motivation part of machine learning usage and comparison of fire and smoke detection is made. T...

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Bibliographic Details
Published inProceedings of the XXth Conference of Open Innovations Association FRUCT pp. 3 - 9
Main Authors Alexandrov, Dmitriy, Pertseva, Elizaveta, Berman, Ivan, Pantiukhin, Igor, Kapitonov, Aleksandr
Format Conference Proceeding
LanguageEnglish
Published FRUCT 01.04.2019
Subjects
Deep learning
Drones
Microsoft Windows
Monitoring
Neural networks
Task analysis
Online AccessGet full text
ISSN2305-7254
DOI10.23919/FRUCT.2019.8711917

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Summary:The article is about the methods of machine learning, designed for the detection of wildfires using unmanned aerial vehicles. In the article presented the review of machine learning methods, described the motivation part of machine learning usage and comparison of fire and smoke detection is made. The research was focused on machine learning application for monitoring task with a restrictions according to scenarios of a real monitoring. The results of experiments with demonstration of effectiveness of detection are presented in the conclusion part.
ISSN:2305-7254
DOI:10.23919/FRUCT.2019.8711917