Personalized Weather Station With Machine Learning Based Rainfall Predictor
In one sentence. Low-cost sensor weather station feeds machine learning to predict local rainfall from temperature, pressure, humidity and wind data.
Abstract
Weather changes have been happening all around the world. And it has become quite a task to predict weather over a particular area. Weather stations are places equipped with instruments necessary for measuring atmospheric conditions. These stations study weather patterns and climatic conditions to provide weather forecasts. The proposed system is a weather station used to monitor the climatological data over a particular petit are a like households and farms that predicts the current weather condition. This system includes different sensors to sense various parameters like temperature, pressure, humidity, wind speed and wind direction. For a long-term basis, the collected data is subjected to machine learning algorithms to predict rainfall. This helps people to take preventive measures and to estimate risks to life and property.
Labels
- Topic
- Local & station forecasting
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.48175/ijarsct-1075 OpenAlex:W3162205745
- Added
- 2026-10-22
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