Rainfall Prediction using Open Weather API

Rainfall Prediction using Open Weather API

Author Name : Prof. Swati Dronkar, Vaidehi Gotmare, Shrutika Kumbhare, Shikhar Pathak, Vaishali Bisne, Shreyash Rahangdale

DOI: https://doi.org/10.56025/IJARESM.2023.120124296

ABSTRACT This study proposes a novel approach for rainfall prediction leveraging reverse engineering of longitude and latitude coordinates. By integrating historical rainfall data with corresponding geographical coordinates, a spatially-aware predictive model is developed to estimate precipitation levels across diverse geographic regions. The methodology involves preprocessing of meteorological and geographic datasets, feature engineering to capture spatial relationships, and model training using machine learning algorithms. Spatial interpolation techniques and terrain characteristics are considered to enhance prediction accuracy. The proposed approach offers a promising solution for localized and accurate rainfall predictions, with potential applications in agriculture, water resource management, and disaster preparedness. Experimental results demonstrate the effectiveness of the methodology in providing actionable insights for decision-making in various geographical contexts.