J. Jerome Vasanth
Papers
1
Total Citations
16
H-Index
1
About
J. Jerome Vasanth is a researcher at the forefront of integrating artificial intelligence with renewable energy systems, with a primary focus on photovoltaic module fault diagnosis. His most cited work, "Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis" (2023), has already garnered 16 citations, demonstrating its immediate impact on the field. Vasanth's major contribution lies in pioneering the use of unmanned aerial vehicles combined with advanced deep learning algorithms for automated solar panel inspection, addressing the critical challenge of detecting faults in large-scale solar installations efficiently. This innovative approach bridges computer vision, robotics, and sustainable energy, offering a practical solution for maintenance and reliability in photovoltaic systems. His work is particularly notable for its potential to transform traditional manual inspection methods into scalable, AI-driven processes, reducing downtime and operational costs. Vasanth's research is essential reading for students and engineers interested in the intersection of artificial intelligence, computer vision, and renewable energy technologies, showcasing how deep learning can enhance the performance and longevity of critical energy infrastructure.
Research Focus
Key Achievements
Top Papers
- 1