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How do sensor-based applications contribute to the advancement of weather forecasting and prediction? 


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Sensor-based applications play a crucial role in advancing weather forecasting and prediction. These applications utilize IoT sensors to collect real-time data on atmospheric parameters, such as temperature, humidity, air pressure, wind speed, and direction . The collected data is then processed and analyzed using various algorithms, including machine learning, to determine weather conditions and predict weather patterns . By combining sensor data with satellite data and operational models, the accuracy of weather predictions is enhanced . Additionally, mobile sensors are used to obtain estimated weather observations, which are incorporated into climatological databases to generate more accurate weather forecasts . The integration of sensor networks with communication and data processing systems enables the timely transmission of weather data, contributing to the prevention of natural disasters . Overall, sensor-based applications provide real-time data, enhance accuracy, and expedite weather predictions, making them essential tools for weather monitoring and forecasting .

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The provided paper does not mention how sensor-based applications contribute to the advancement of weather forecasting and prediction. The paper focuses on the development of an IoT-based weather monitoring system for smart agriculture.
The paper describes the use of mobile sensors to obtain weather observations and incorporate them into a database for enhancing climatological databases. These sensor-based applications contribute to the generation of more accurate weather forecasts.
The provided paper does not specifically mention how sensor-based applications contribute to the advancement of weather forecasting and prediction.
The paper mentions that IoT sensors, combined with satellite data and operational models, enhance accuracy and expedite weather predictions.

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