V. Sugumaran

Vellore Institute of Technology University

Papers

Total Citations

H-Index

About

V. Sugumaran is a leading researcher at the intersection of artificial intelligence, computer vision, and renewable energy systems, with a primary focus on intelligent fault diagnosis and condition monitoring. His most impactful work centers on applying machine learning and deep learning techniques to photovoltaic (PV) module fault detection, where he has pioneered non-invasive diagnostic methods. His highly cited 2022 paper, "Machine vision based fault diagnosis of photovoltaic modules using lazy learning approach" (70 citations), introduced a novel, data-efficient approach that significantly improved the accuracy of identifying defects in solar panels. Building on this, his 2023 work on "Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis" (16 citations) integrates drone technology with advanced image analysis, pushing the boundaries of automated, large-scale solar farm inspection. Sugumaran’s contributions are critical for reducing maintenance costs and boosting the reliability of solar energy systems. His research also extends to robotics, with early work on speech recognition for humanoid robots. With a citation trajectory showing growing influence, his work is essential reading for engineers and researchers in AI-driven industrial automation and sustainable energy.