How to remotely identify RISO faults through Artificial Intelligence so as to eliminate physical inspection or use of any hardware/equipment to detect it.

How to identify and develop module-level fault detection frameworks with classification techniques to build low-cost edge-devices (IoT Sensors) that could be deployed at large scale in low-power-output PV arrays.

Explore the sensitivity of the PV Modules towards rising temperature that negatively impacts the electrical conversion efficiency of a PV module and thus overall performance of the plant.

How to predict solar irradiance and wind speed/flow accurately using AI-based framework to automatically select the best models, factors, and their combinations to optimize the overall accuracy of the predictions.