IoT Based Machine Learning Weather Monitoring and Prediction Using WSN

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Published: Sep 21, 2023
DOI: https://doi.org/10.17762/ijritcc.v12i1.7990
Keywords:
Internet of Things, Machine Learning, Wireless Sensor Network, Decision System

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Sanjeev Singh
Department of Electronics and Communication Engineering, M.B.S. College of Engineering and Technology, Jammu, Jammu and Kashmir, INDIA
Amrik Singh
Department of Computer Science & Engineering, M.B.S. College of Engineering and Technology, Jammu, Jammu and Kashmir, INDIA
Suresh Limkar
Department of Artificial Intelligence & Data Science, AISSMS Institute of Information Technology, Pune, Maharashtra, INDIA

Abstract

A novel approach to analysis and prediction is provided by the internet of things-based time monitoring and prediction system using wireless sensor networks (WSN) and machine learning techniques (ML). To give accurate meteorological data in real time, the integrated system uses IoT, WSN, and ML. Making informed decisions requires these insights. Includes strategically positioned infrared points that are used to gather meteorological information, such as temperature, humidity, pressure, and wind speed, among other things.The machine's automatic data processing methods are then used in a central processing unit to collect and analyse the data. By seeing patterns and drawing diagrams utilising previously collected data, ML models are able to comprehend intricate temporal dynamics. An important development in this system is its predictive capabilities. Artificial intelligence has the processing power to precisely forecast short-term weather patterns, enabling the rapid transmission of warnings for extreme localised events and the reduction of potential dangers.The combination of historical data, real-time sensor inputs, and automated analysis produces the predictive potential. The "Internet of Things" architecture used to develop this system makes it simpler to gather meteorological data. A number of industries, including as agriculture, transportation, emergency management, and event planning, are encouraged to make data-based decisions since users can quickly obtain current meteorological conditions and forecasts through user-friendly web interfaces or mobile applications.

Article Details

How to Cite
Singh, S. ., Singh, A. ., & Limkar, S. . (2023). IoT Based Machine Learning Weather Monitoring and Prediction Using WSN. International Journal on Recent and Innovation Trends in Computing and Communication, 12(1), 112–123. https://doi.org/10.17762/ijritcc.v12i1.7990
Issue
Vol. 12 No. 1 (2024)
Section
Articles

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