Paper
16 January 2025 Research and development of plateau portable landslide detection equipment based on Jetson Nano
Jianyu Xu, Siwei Cheng, Libin Su, Yonggang Guo
Author Affiliations +
Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 134470R (2025) https://doi.org/10.1117/12.3044965
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China
Abstract
In response to the problems that landslides occur in remote locations, are difficult to monitor and landslide target detection is not easily deployed at the embedded end, a landslide detection device based on the Jetson nano edge device is developed. The technology detects information of landslide feature objects through YOLOV5m technology, and is able to output landslide area information as well as geographic location information while accurately detecting landslide targets. A dataset of 25,000 landslide images is used to build the data set, and the training and validation sets are divided 9:1. A deep learning network is used to extract landslide features and build a landslide target detection model. After that, the train.py file is placed on the cloud server for training, and the best.pt file is migrated to Jetson Nano and tested on the embedded platform. The experimental results show that the average running time of single frame of YOLOV5mmodel in the embedded device is 100ms, and the detection accuracy can be maintained above 80%, which can achieve accurate detection and information acquisition of landslide target on Jetson Nano device, and lay the foundation for the development of edge device module for landslide detection later.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jianyu Xu, Siwei Cheng, Libin Su, and Yonggang Guo "Research and development of plateau portable landslide detection equipment based on Jetson Nano", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 134470R (16 January 2025); https://doi.org/10.1117/12.3044965
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KEYWORDS
Cameras

Network landslides

Target detection

Object detection

Detection and tracking algorithms

Distortion

Image processing

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