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Forest Fire Detection System

This ROS package is designed for early wildfire detection, geolocation and monitoring.

System architecture

system architecture

Functions

Early Wildfire Flame and Smoke Segmentation

functions results
path planning path
forest fire image classification path
forest fire image segmentation path
gimbal control path
fire point geolocation path

Multi-view Geometry-based Wildfire Spot Geolocation

Early wildfire spot perception methods

functions
Attention gate U-net wildfire segmentation path
Trianglulation-based wildfire point depth estimation path
Visible-infrared camera system calibration path
Model-based wide fire point registration path

Wildfire Local Environment 3D reconstruction

You can also compare the reconstruction results with google earth.

SFM with colmap Reconstruction with OpenMVS
img img
img img

Outdoor Flight Test Videos

M300 drone flies along the defined zigzag path, while the attention gate U-net is implemented to detect and segment the suspect wildfire.

  1. Once the suspect fire is detected, M300 will fly from left to the right. In the meantime, a monocular SLAM is running to acquire the precise camera pose, the GPS information is used to correct the scale of the poses.
  2. Based-on the triangulation of the fire zone, the distance can be estimated. Then, the fire can be geolocated by with the gimbal angle.

Finally, M300 will fly along a circle shape of the flight path to record the scene of the local environment around the wildfire spot with the H20T zoom camera.

Related Paper

@INPROCEEDINGS{9836119,
  author={Li, Shun and Qiao, Linhan and Zhang, Youmin and Yan, Jun},
  booktitle={2022 International Conference on Unmanned Aircraft Systems (ICUAS)}, 
  title={An Early Forest Fire Detection System Based on DJI M300 Drone and H20T Camera}, 
  year={2022},
  volume={},
  number={},
  pages={932-937},
  doi={10.1109/ICUAS54217.2022.9836119}}

Copyright

Copyright (C) 2021 Concordia NAVlab. All rights reserved.