TY - GEN
T1 - Early Detection of Forest Fire Based on Unmaned Aerial Vehicle Platform
AU - Yang, Xingsha
AU - Tang, Linbo
AU - Wang, Hongshuo
AU - He, Xinxin
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - As a kind of natural resources, forest is vital to our survival. Once the fire happening in forest is not found in time, it can cause a huge loss. Accurate real-time monitoring of forest fires is not only an important part of forest fire prevention, but also an important means to effectively control the spread of forest fires and reduce economic losses. Forest areas are often geographically widely distributed and inefficient in manual inspections. Therefore, we need a highly mobile early forest fire warning system to ensure the safety of forest resources. UAVs serve as a highly mobile inspection tool to meet inspection requirements of forest fires. Besides, the early flame characteristics are not obvious, and the single source fire detection is easy to false alarm. In view of this, we propose a forest fire detection method that uses optical images to detect smoke and infrared images to detect fire.
AB - As a kind of natural resources, forest is vital to our survival. Once the fire happening in forest is not found in time, it can cause a huge loss. Accurate real-time monitoring of forest fires is not only an important part of forest fire prevention, but also an important means to effectively control the spread of forest fires and reduce economic losses. Forest areas are often geographically widely distributed and inefficient in manual inspections. Therefore, we need a highly mobile early forest fire warning system to ensure the safety of forest resources. UAVs serve as a highly mobile inspection tool to meet inspection requirements of forest fires. Besides, the early flame characteristics are not obvious, and the single source fire detection is easy to false alarm. In view of this, we propose a forest fire detection method that uses optical images to detect smoke and infrared images to detect fire.
KW - UAV
KW - forest fire
KW - smoke
UR - http://www.scopus.com/inward/record.url?scp=85091952414&partnerID=8YFLogxK
U2 - 10.1109/ICSIDP47821.2019.9173181
DO - 10.1109/ICSIDP47821.2019.9173181
M3 - Conference contribution
AN - SCOPUS:85091952414
T3 - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
BT - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Y2 - 11 December 2019 through 13 December 2019
ER -