Advanced Tunnel Inspections for Lighting and Electrical System Assessment with AI-Powered Drones and Cloud Technology

Traditional techniques of inspecting tunnel lighting and electrical systems may be time-consuming and prone to error, yet they are essential for keeping operations safe and running smoothly. This paper introduces a novel method for improving inspection efficiency that uses cloud computing, YOLO (You Only Look Once) object identification algorithms and drones driven by artificial intelligence (AI). Aerial images of tunnel infrastructure are potentially made by drones armed with high-resolution cameras. The next step is to use YOLO algorithms for real-time object identification, which accurately identifies and evaluates the state of electrical components and illumination. By spotting outliers and possible problems in real-time, this analysis helps to minimize the potential of system failures and enables quick response. Data processing, storage, and management are all handled by a cloud platform, which allows for centralized access, constant monitoring, and thorough analysis. Compared to more conventional approaches, this cutting-edge inspection technique significantly decreases inspection durations while increasing tunnel inspections' accuracy and efficiency. This method offers improved accuracy and operational advantages for critical infrastructure management by combining cloud technology with AI-driven image analysis; it is a significant leap compared to conventional tunnel maintenance approaches.