Amirkabir University of Technology Advances in Energy Sciences and Technologies 3115-9117 1 2 2025 09 01 RoboPV: A modular system for enhancing the efficiency of autonomous aerial monitoring of photovoltaic plants 215 225 5849 10.22060/aest.2025.5849 EN Amir Mohammad Moradi Sizkouhi Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada Mohammadreza Aghaei Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), Ålesund, Norway; Department of Sustainable Systems Engineering (INATECH), Albert Ludwigs University of Freiburg, Freiburg, Germany Mahdi Karimkhani Department of Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran Sayyed Majid Esmailifar Department of Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran Journal Article 2025 07 23 This paper presents RoboPV, an innovative embedded software for autonomous aerial monitoring of photovoltaic (PV) plants. RoboPV automates monitoring with features like optimal trajectory planning, image processing, and real-time fault detection through four integrated components: boundary area detection, path planning, dynamic processing, and fault analysis. A specialized encoder-decoder deep learning model processes aerial images to identify plant boundaries, while a unique path planning algorithm ensures complete area coverage. During flights, a neural network analyzes images for automatic fault detection. RoboPV also includes decision-making algorithms for various flight conditions, is compatible with low-power micro-computers, and supports the MAVLink protocol for multi-rotor operations. A six-degrees-of-freedom dynamic model was tested in a SIMULINK environment, achieving 93% accuracy in autonomous inspections of large-scale PV installations. https://aest.aut.ac.ir/article_5849_1b388c8b7c863fde3f559142fdc123b0.pdf