IoT-Enabled Weather Monitoring and Rainfall Prediction using Machine Learning Algorithm

The proposed weather monitoring system utilizes the Internet of Things (IoT) to make real-time data accessible to everyone. Various sensors are deployed to gather weather-related information such as temperature, humidity, wind speed, rainfall, and atmospheric pressure. The collected data is transmitted to a cloud server through the IoT, where it is stored and processed. Web page users from any global location may view the uploaded information. Support Vector Machine (SVM) then analyzes the data and predicts rainfall patterns based on historical records and current weather conditions. The data is then represented graphically and displayed for the user. Integrating machine learning algorithms enhances the accuracy of rainfall predictions, allowing for better preparation and planning in various sectors such as agriculture, weather stations, water resource management, marine industries, and disaster response. For improving weather forecasting systems, enabling more informed decision-making and proactive measures in various domains impacted by weather conditions.