Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Assessing Acetabular Index Angle in Infants: A Deep Learning-Based Novel Approach.

Journal of imaging·2023

Same author

Joint Diagnosis of Pneumonia, COVID-19, and Tuberculosis from Chest X-ray Images: A Deep Learning Approach.

Diagnostics (Basel, Switzerland)·2023

Same author

Development and Validation of Embedded Device for Electrocardiogram Arrhythmia Empowered with Transfer Learning.

Computational intelligence and neuroscience·2022

Same author

Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning.

Sensors (Basel, Switzerland)·2022

Same author

ECG Classification for Detecting ECG Arrhythmia Empowered with Deep Learning Approaches.

Computational intelligence and neuroscience·2022

Same author

IoMT-Based Osteosarcoma Cancer Detection in Histopathology Images Using Transfer Learning Empowered with Blockchain, Fog Computing, and Edge Computing.

Sensors (Basel, Switzerland)·2022

Same journal

Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.

Journal of imaging·2026

Same journal

Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.

Journal of imaging·2026

Same journal

YoLeTooth: A Unified Framework for Joint Tooth Segmentation and Periapical Lesion Detection in Panoramic Radiographs.

Journal of imaging·2026

Same journal

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences.

Journal of imaging·2026

Same journal

Cutaneous Thermography in Arthropathies: Quantitative Imaging, Machine Learning, and Clinical Translation.

Journal of imaging·2026

Same journal

Two-Stage Dynamic Synergistic Segmentation Method for Myocardial Pathology.

Journal of imaging·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 16, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

Solar Panel Surface Defect and Dust Detection: Deep Learning Approach.

¹Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.

Journal of Imaging

|September 26, 2025

Summary

This summary is machine-generated.

This study presents an automated system using deep learning for solar panel defect detection, improving efficiency and reducing maintenance costs. The AI model achieves over 95% accuracy in identifying issues like dust and physical damage.

Keywords:

Saudi Vision 2030 YOLOv11 computer vision deep learning proactive maintenance real-time monitoring renewable energy solar panel defect detection

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

Related Experiment Videos

Last Updated: Jan 16, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

Area of Science:

Renewable Energy
Artificial Intelligence
Computer Vision

Background:

Maintaining solar panel efficiency is crucial for sustainable energy.
Extreme environmental conditions pose challenges to photovoltaic (PV) system performance.
Automated defect detection is needed to reduce costs and downtime.

Purpose of the Study:

To develop an automated defect detection pipeline for photovoltaic surfaces.
To identify and classify five anomaly types: Non-Defective, Dust, Defective, Physical Damage, and Snow.
To enhance the reliability and cost-effectiveness of solar energy systems through continuous monitoring.

Main Methods:

A heterogeneous dataset of 8973 images was curated and augmented.
A YOLOv11-based deep learning model was trained and fine-tuned.
The model was integrated into an interactive dashboard for real-time processing and alerts.

Main Results:

The YOLOv11 model achieved a mean Average Precision (mAP@0.5) of 85%.
Accuracy, recall, and F1-score exceeded 95% across various conditions.
The system demonstrated superior precision and inference speed compared to manual inspection and older models.

Conclusions:

Automated visual inspection reduces labor costs and operational downtime for solar installations.
The developed pipeline offers a scalable solution for proactive maintenance and enhanced PV system longevity.
This approach improves the overall reliability and cost-effectiveness of large-scale solar energy systems.