Nanshui Reservoir plays a key role in energy production and sustainable development. However, traditional operation and maintenance methods often face the problems of untimely information and low efficiency of data processing. To solve this problem, an automatic inspection method of reservoir area based on edge intelligence and unmanned aerial vehicle was proposed. Firstly, the edge calculation box and flight control system were designed. Then the automatic route planning algorithm and camera linkage control algorithm were studied. Finally, the experimental verification was carried out in Nanshui Reservoir. The results show that this method can improve the operation and maintenance efficiency of the reservoir area.
Aiming at the problem of road landslide classification in Nanshui Reservoir area, a new solution was proposed by combining unmanned aerial vehicle inspection technology, deep learning and analytic hierarchy process. Firstly, the high-resolution road image data in the reservoir area was obtained by unmanned aerial vehicle inspection, and then the image segmentation was carried out by deep learning algorithm. Finally, the road landslide was graded by analytic hierarchy process, and the severity and maintenance priority of the landslide were evaluated. The experimental results show that this method can effectively realize the classification of road landslides in Nanshui Reservoir area. This study can provide scientific basis and guidance for the operation and maintenance of the Nanshui Reservoir, in order to promote traffic safety and maintenance work in the reservoir area.
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