Framework for autonomous inspection of PV plants using IoT
This article presents a novel autonomous inspection framework for PV installations using on-board electronics of PV panels (IoT Modules) and a UAV fleet. The IoT Modules are in charge of
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Towards autonomous photovoltaic panels health monitoring: UAV
Key innovations discussed include advanced machine learning algorithms and specialized imaging techniques, such as thermal, visual, and electroluminescence (EL) imaging, selected for their
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Towards a Holistic Approach for UAV-Based Large-Scale Photovoltaic
It examines key components of UAV-based PV inspection, including data acquisition protocols, panel segmentation and geolocation, anomaly classification, and optimizations for model
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Solar UAV for the Inspection and Monitoring of Photovoltaic (PV
This paper aims to design and fabricate a prototype of a solar-powered, fixed-wing, Unmanned Aerial Vehicle (UAV) with energy harvesting capabilities that can inspect and monitor
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LFS-YOLO: A PV Panel Defect Detection Algorithm for Drone Infrared
In this article, a hot spot defect detection algorithm according to infrared images of aerial PV is proposed for practical engineering problems such as defects with different morphology, unclear
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A Lightweight Model for Infrared Photovoltaic Panel Defect
In this study, a lightweight real-time detection model, TA-YOLOv11, is proposed for UAV-based IR PV panel defect identification.
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Photovoltaic plant monitoring and inspection through synergic
Our system employs a dynamic online planning algorithm that allows for real-time task allocation and inspection on a per-panel basis. In this paper, we propose a new approach where each panel is
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GitHub
The RTPV-YOLO algorithm is designed to work with UAV platforms, which are equipped with thermal and RGB cameras for data collection during PV panel inspections.
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Method of UAV Inspection of Photovoltaic Modules Using
In this paper, we presented a comprehensive, integrated framework for UAV-based PV inspection that successfully addresses the critical challenges of representation robustness, multi
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Vision-Based Object Detection for UAV Solar Panel Inspection
A custom dataset, annotated in the COCO format and specifically designed for solar panel defect and contamination detection, was developed alongside a user interface to train and evaluate the models.
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