@article {10.3844/jcssp.2025.1526.1538,
article_type = {journal},
title = {Smart Weather Data Management System for Sustainable Agriculture in Maharashtra Using Machine Learning},
author = {Kadu, Aishwarya V. and Reddy, Kuraparthi Tirumala V.},
volume = {21},
number = {7},
year = {2025},
month = {Jul},
pages = {1526-1538},
doi = {10.3844/jcssp.2025.1526.1538},
url = {https://thescipub.com/abstract/jcssp.2025.1526.1538},
abstract = {Agriculture will benefit greatly from efficient weather data sustainable management. Data can be utilized to schedule the prediction yield, crop growth, and irrigation. This paper collects real-time meteorological station data via APIs, primarily focusing on the weather data sustainable management system and data related to Maharashtra Wardha, India, which is involved in a live series period. Agriculture can make potential through the growth of Smart Weather Data Management (SWDM) platforms. Real-time data from India, combined with intelligent insights, can be used to propose innovative and sustainable solutions. Four layers are involved: i. Acquisition ii. Storage iii. Application iv. Processing. ML checks for errors and missing values based on Land-Wardha reanalysis once the information is obtained. To assess the accuracy of the Temperature, Humidity, and Rainfall approximations with the use of some evaluation metrics with coefficients of determination (R2-Scores), (RMSE), and (MSE). The system's services include weather forecast time series, meteorological data visualization and analysis, and ML-based evaluation. Real-time services for temperature, humidity, wind speed, and cloud cover given the prediction for the Previous /Next five days in Maharashtra, Wardha, India. The platform is built with the aim of providing services and solutions that can assist both farmers and representatives.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}