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@article{187846,
        author = {Aravind T and Avinash Dubey and Aryan and Chirayu N Hudhar and Asst Professor Niveditha V  K},
        title = {A PREDICTIVE FRAMEWORK FOR DUST ACCUMULATION AND EFFICIENCY LOSS IN SOLAR- PV SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {7027-7033},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187846},
        abstract = {This study presents a method to predict how dust collects on solar photovoltaic (PV) modules and how this buildup lowers their electrical output. Dust forms a barrier betweenincoming sunlight and the panel surface, gradually reducing the amount of usable light. To predict this decline, the proposed method includes environmental factors like humidity, temperature, wind conditions, and airborne particle levels into a machine learning-based forecasting model. The system forecasts both the rate of dust buildup and the resulting drop in performance. This enables operators to make better decisions about cleaning schedules and maintenance planning. Experimental results show that dust forecasting can notably improve the accuracy of estimating power loss and cut unnecessary operational costs, providing a practical way to incorporate smart monitoring into modern PV setups.},
        keywords = {},
        month = {November},
        }