Published Paper Details:

Renewable energy efficiency depends on precise solar radiation estimation together with agricultural output and sustainable environmental practices. The research establishes an innovative hybrid method for solar radiation forecasting by combining live meteorological data including temperature as well as humidity and wind speed metrics and with analytical sky visuals. The system uses advanced image recognition methods for cloud coverage determination and quantifies sunlight obstruction while applying sine altitude calculations for solar geometry analysis. The analyses from observed data merge with established empirical models to produce accurate solar radiation forecasts. Sunlight blockage statistics along with sky image processing results solar geometry parameters and solar radiation predictions appear as the system output data. Standard solar datasets and constants provide confirmation of both accuracy and the system's reliable performance. The research demonstrates how time-tested solar prediction approaches merge effortlessly with innovative computational systems to create an easy-to-use interface for solar energy users. Our upcoming strategy will use mobile platform deployment to extend accessibility while enabling users to enhance their energy planning and participate better in sustainability initiatives.