Artificial Intelligence Patrol Technology for Unmanned Aerial Vehicles (UAVs) on the Whole Tower and Line Based on Neural Network

The tower line inspection task in the power industry is crucial for ensuring the safe operation of transmission lines and towers. However, traditional inspection methods have problems such as low efficiency, high cost, and unstable reliability. This article proposes a neural network-based artificial intelligence patrol technology for UAVs on the entire tower line, aiming to solve the challenges of traditional patrol methods. This technology utilizes advanced neural network algorithms and unmanned aerial vehicle (UAV) platforms to achieve efficient, accurate, and automated tower line patrol task execution. By collecting and analyzing a large amount of image feature data, neural networks can identify and locate potential problems on transmission lines and towers in real-time, such as damage, corrosion, and weed coverage. Through on-site testing and verification, it has been proven that this technology can effectively improve the efficiency and quality of patrol task execution. In addition, strategies for further optimizing the model and strengthening data processing were explored to enhance the performance and practicality of the technology. The artificial intelligence patrol technology based on neural networks for UAVs on the entire tower line provides a new solution for patrol tasks in the power industry, with broad promotion and application prospects.