Open AccessSimulation implementation of air pollution traceability algorithm based on unmanned aerial vehicle
Author(s) -
Shuyu Zhang,
Zhenguo Liu,
Jinbao Liu,
Tao Ding,
Shuncheng Wei
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/675/1/012012
Subject(s) - traceability , pollution , air pollution , trace (psycholinguistics) , computer science , climb , environmental science , matlab , field (mathematics) , noise pollution , tracing , algorithm , real time computing , simulation , remote sensing , engineering , aerospace engineering , artificial intelligence , noise reduction , ecology , geography , linguistics , philosophy , mathematics , software engineering , pure mathematics , biology , operating system
Air pollution has serious harm to the ecological environment and human health. However, current ground monitoring methods and mobile robot traceability methods are difficult to accurately and quickly trace air pollution sources after pollution events. To solve this problem, this paper proposes an air pollution traceability algorithm based on unmanned aerial vehicle (UAV), which combines the mobile and flexible UAV with the hill climb traceability algorithm to realize the monitoring and tracking of air pollution source in a large area. Gaussian concentration field and turbulent concentration field are built by MATLAB, and the simulation experiment is carried out in these two concentration fields. Experimental results show that the algorithm can trace air pollution sources quickly and accurately.