M.H. Elkholy

University of the Ryukyus

Papers

1

Total Citations

20

H-Index

1

About

Dr. M.H. Elkholy is a leading researcher in photovoltaic (PV) system optimization, artificial intelligence for renewable energy, and robotic cleaning technologies. His most impactful work addresses the critical challenge of soiling on solar panels, which can reduce energy output by up to 30%. In his highly cited 2025 study, Dr. Elkholy developed a deep learning-based recognition and classification system using HALCON software to identify soiled PV modules, enabling autonomous solar cleaning robots to operate with unprecedented precision. This contribution, already garnering 20 citations, bridges computer vision and sustainable energy, offering a scalable solution to maintain optimal efficiency in large-scale solar farms. His research demonstrates how AI-driven automation can reduce water usage and manual labor in panel maintenance, directly supporting the global push toward cleaner energy infrastructure. Dr. Elkholy’s work is widely recognized for its practical impact, with his citation trajectory reflecting growing interest from both academia and industry. By integrating deep learning with robotics, he is helping to lower the levelized cost of solar energy, making photovoltaic systems more viable for widespread adoption.

Research Focus

Key Achievements

1
H-Index
1
Papers
20
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Deep Learning-Based Recognition and Classification of Soiled Photovoltaic Modules Using HALCON Software for Solar Cleaning Robots
20 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of the Ryukyus

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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