Paper Title :Integrated Meteorological Sensing: A Synergistic Framework of Iot-Driven Weather Stations and Advanced Machine Learning Algorithms

Author :Stmanav Verma, Ndsakshi Kumari, Rdrishav Kumar, Thabhishek Kumar Rai , Thanupam Shahi

Article Citation :Stmanav Verma ,Ndsakshi Kumari ,Rdrishav Kumar ,Thabhishek Kumar Rai ,Thanupam Shahi , (2024 ) " Integrated Meteorological Sensing: A Synergistic Framework of Iot-Driven Weather Stations and Advanced Machine Learning Algorithms " , International Journal of Soft Computing And Artificial Intelligence (IJSCAI) , pp. 59-64, Volume-12,Issue-1

Abstract : This research focuses on the implementation of an automated weather forecast station using IoT technology. The system uses advanced forecasting methodologies like ARIMA and deep learning to provide immediate insights into weather conditions. The system uses environmental sensors for seamless data gathering and an intuitive user interface. The research extends its application to smart urban centers and industrial sectors, prioritizing safety and resilience in the context of climate change. K-Medoids clustering, Naïve Bayes algorithm, and ARIMA models enhance the system’s resilience. This research contributes to the advancement of weather forecasting technologies and fostering a resilient society. Keywords - IoT (Internet of Things), ARIMA, Deep learning, Weather forecasting, EDS (Exploratory Data Analysis), Random Forest, Convolutional Neural Networks

Type : Research paper

Published : Volume-12,Issue-1

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