Dr Rana Hamza Shakil thank you for your contribution to the discussion

Machine learning techniques like regression, neural networks, and ensemble methods forecast weather. Advanced tech, such as satellites, radar, and weather stations, monitor conditions. 🌦️ AI predicts, tech checks - together, they make meteorology a digital dance! 💃🌍

Recurrent Neural Networks are the best way for multivariate weather forecasting or prediction. Neural network with data processing is suitable for weather forecasting. RNN using time series along with a linear SVC and a five-layered neural network is used to predict the weather. The results of these models are analyzed and compared on the basis of Root Mean Squared Error between the predicted and actual values. IoT system for weather monitoring uses sensors to monitor and adjust environmental parameters such as temperature, CO levels, and relative humidity. Then, it sends the data to a web page to plot the sensor data, shown as graphical statistics. Weather forecasting works by taking in large amounts of data about the current atmospheric conditions and analyzing that data to figure out the most likely outcome. That data comes from sensors connected to computers. Those sensors measure everything from temperature to wind speed to humidity and pressure. Weather monitoring sensors are one of the key components of a solar power plant that collect various weather data. The key function of WMS function is to gather the data of weather parameters such as solar radiation, Module surface temperature, ambient temperature, wind speed etc. The system constantly monitors temperature using temperature sensor, humidity using humidity sensor and also for rain. Weather monitoring system deals with detecting and gathering various weather parameters at different locations which can be analyzed or used for weather forecasting. A thermometer for measuring air and sea surface temperature and barometer for measuring barometric pressure/air pressure and hygrometer for measuring humidity and an anemometer for measuring wind speed. Tools used to discuss current weather conditions are outdoor thermometers (air temperature), barometers (air pressure), anemometers (wind speed and direction), and hygrometers (humidity). Radar is used to detect objects in the air, mainly precipitation; however, it has been known to reflect mass clusters of insects. Most people know that high and white clouds suggest a bright and sunny day, low black clouds are a sign of rain, and a gray veil in the sky means a big storm is imminent. The bottom of clouds can also help predict the weather. The more ragged the bottom of a cloud, the more likely it will rain.

Hi, please check this recent research in this field, using PCA as unsupervised ML method:

Article Abaxial leaf surface-mounted multimodal wearable sensor for ...

Dr Sina Jamalzadegan thank you for your contribution to the discussion

Weather forecasters use all kinds of tools to achieve this goal. We have instruments called barometers to measure air pressure, radar to measure the location and speed of clouds, thermometers to measure temperature, and computer models to process data accumulated from these instruments. Deep learning models can be built to find weather patterns of cloud behavior by training it with satellite imagery. This means a model does not try to reproduce entire weather systems via simulations, but instead is trained to focus its compute power on seeing visual patterns from a mosaic of pixels. RNN using time series along with a linear SVC and a five-layered neural network is used to predict the weather. The results of these models are analyzed and compared on the basis of Root Mean Squared Error between the predicted and actual values. The prediction is made based on sliding window algorithm. The monthwise results are being computed for three years to check the accuracy. The results of the approach suggested that the method used for weather condition prediction is quite efficient with an average accuracy of 92.2%. We can use that knowledge in our project of Rainfall Prediction System as it will help a lot of people. Various Machine Learning algorithms such as Logistic Regression, Decision Tree, K-Nearest Neighbor, and Random Forest are compared to find the most accurate model. The machine learning algorithm called linear regression is used for predicting the rainfall using important atmospheric features by describing the relationship between atmospheric variables that affect the rainfall. The IoT based Weather Monitoring system features to monitor temperature and humidity level, Barometric pressure, light intensity, air quality and rainfall. The required hardware includes Raspberry Pi, Arduino Mega, DHT11, Light intensity sensor BH1750, MQ-135, BME-280, and raindrop sensor. The Ambient Weather WS-2000 is our recommendation for the best home weather station. It features a highly accurate sensor array that's also easy to set up, a fantastic full color display, and gives you the option to add more sensors later if you need them. Weather monitoring sensors are one of the key components of a solar power plant that collect various weather data. The key function of WMS function is to gather the data of weather parameters such as solar radiation, Module surface temperature, ambient temperature, wind speed etc. India Meteorological Department (IMD) uses the INSAT series of satellites hovering in the geosynchronous orbit along with the Real-Time Analysis of Products and Information Dissemination (RAPID), a weather data explorer application that acts as a gateway and provides quick interactive visualization. Weather forecasting, which used to be done by hand and was focused mostly on variations in barometric pressure, existing weather patterns, and sky state or cloud cover, is now done using computer-based models that account for a variety of atmospheric variables. Geostationary satellites orbit the Earth at over 35 000 km above the Equator, spinning at the same speed as the Earth. This allows them to appear to hover over the same portion of the Earth and to provide constant monitoring of rapidly developing weather. Humidity (unit: % of r.H. relative humidity), Wind direction (unit: 0-360 °< angle of direction), Global radiation (unit: W/m2) is measuring the amount of Sun's energy received by a surface per unit area, Rainfall sensor (unit: mm) measuring the quantity of rainfall.