Vetri Selvi Mahamuni
Papers
1
Total Citations
16
H-Index
1
About
Dr. Vetri Selvi Mahamuni is a leading researcher at the intersection of artificial intelligence, computer vision, and renewable energy systems. Her work focuses on developing intelligent diagnostic frameworks that enhance the reliability and efficiency of photovoltaic (PV) systems. In her most-cited study, "Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis" (2023, 16 citations), she pioneers an innovative approach that combines UAV-based aerial imagery with deep learning algorithms to automate the detection of faults in solar panels. This contribution is pivotal for advancing predictive maintenance in solar farms, reducing downtime, and improving energy yield. Dr. Mahamuni’s research demonstrates how AI-driven computer vision can be applied beyond traditional domains—such as industrial control and robotics—to solve pressing challenges in sustainable energy infrastructure. Her work has been recognized for its practical impact, offering scalable solutions for real-world photovoltaic monitoring. With a growing citation record, Dr. Mahamuni continues to shape the future of smart energy systems, making her a notable voice in applied AI and renewable energy diagnostics.
Research Focus
Key Achievements
Top Papers
- 1