ForestML: A Real-Time Solution Proposal for UAV acquired Multispectral Imagery Analysis using Machine Learning

被引:0
作者
Cruz, Mario [1 ]
Miragaia, Rolando [1 ]
Ramos, Joao [1 ]
Pereira, Antonio [1 ,2 ]
机构
[1] Polytech Univ Leiria, Comp Sci & Commun Res Ctr, Leiria, Portugal
[2] INOV INESC INNOVATION, Leiria, Portugal
来源
2024 9TH INTERNATIONAL CONFERENCE ON SMART AND SUSTAINABLE TECHNOLOGIES, SPLITECH 2024 | 2024年
关键词
Machine Learning; Multispectral; Prediction; Real-Time; UAVs; Wildfire;
D O I
10.23919/SpliTech61897.2024.10612566
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The escalating threat of wildfires in Mediterranean Europe, particularly in Portugal, highlights the urgent need for innovative fire prediction and forest surveillance approaches. This paper introduces ForestML, a real-time architecture leveraging Unmanned Aerial Vehicles (UAVs) equipped with multispectral cameras and machine learning algorithms to forecast and analyze forests from an aerial perspective. This promising ForestML, which comprises Ground Station, Backstation, and Web Server components, facilitates real-time wildfire risk assessment and prediction, enabling timely decision-making to mitigate fire-related risks.
引用
收藏
页数:6
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