Papers
1
Total Citations
11
H-Index
1
About
S. Ajitha is a researcher advancing the intersection of renewable energy and artificial intelligence, with a primary focus on solar photovoltaic (PV) systems and thermal energy management. Her most cited work introduces a novel approach to solar energy optimization by integrating phase change materials (PCMs) with deep learning models. Specifically, her 2023 paper, "Smart Operating Range Monitoring of Solar PV Cell with Integrated Phase Change Materials by Using Solar Deep Learning Model," has garnered 11 citations for demonstrating how microencapsulated bio-based PCMs can passively collect solar energy in buildings while simultaneously enabling real-time performance tracking. This contribution bridges material science and machine learning, offering a pathway to more efficient and intelligent solar energy systems. Ajitha’s research is particularly notable for its practical application in building-integrated photovoltaics, where thermal regulation is critical. By combining PCMs that operate within human comfort zones with a solar deep learning model, she addresses both energy efficiency and system monitoring—a dual achievement that underscores her innovative approach to sustainable technology. Her work holds significant promise for students and researchers interested in smart grid integration, renewable energy optimization, and the use of AI for environmental monitoring.
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Top Papers
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