Bee2Fire: A Deep Learning Powered Forest Fire Detection System

被引：10

作者：

Valente de Almeida, Rui ^{[1
,2
]}

Crivellaro, Fernando ^{[1
]}

Narciso, Maria ^{[1
]}

Isabel Sousa, Ana ^{[1
]}

Vieira, Pedro ^{[1
]}

机构：

[1] FCT NOVA, Phys Dept, Campus Caparica, P-2829516 Caparica, Portugal

[2] Compta SA, Alameda Fernao Lopes 12,10th Floor, P-1495190 Alges, Portugal

来源：

ICAART: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 2 | 2020年

关键词：

Forest Fire Detection; Deep Learning; PyTorch; FastAI; IBM Watson;

D O I：

10.5220/0008966106030609

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Bee2Fire is a commercial system for forest fire detection, inheriting from the Forest Fire Finder System. Designed in Portugal, it aims to address one of Southern Europe's main concern, forest fires. It is a well known fact that the sooner a wildfire is detected, the quicker it can be put out, which highlights the importance of early detection. By scanning the landscape using regular cameras and Deep Artificial Neural Networks, Bee2Fire searches for smoke columns above the horizon with a image classification approach. After these networks were trained, the system was deployed in the field, obtaining a sensitivity score between 74% and 93%, a specificity of more than 99% and a precision of around 82%.

引用

页码：603 / 609

页数：7

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