Sensors, Vol. 25, Pages 3432: New Model for Weather Stations Integrated to Intelligent Meteorological Forecasts in Brasilia

Sensors doi: 10.3390/s25113432

Authors:
Thomas Alexandre da Silva
Andre L. M. Serrano
Erick R. C. Figueiredo
Geraldo P. Rocha Rocha Filho
Fábio L. L. de Mendonça
Rodolfo I. Meneguette
Vinícius P. Gonçalves

This paper presents a new model for low-cost solar-powered Automatic Weather Stations based on the ESP-32 microcontroller, modern sensors, and intelligent forecasts for Brasilia. The proposed system relies on compact, multifunctional sensors and features an open-source firmware project and open-circuit board design. It includes a BME688, AS7331, VEML7700, AS3935 for thermo-hygro-barometry (plus air quality), ultraviolet irradiance, luximetry, and fulminology, besides having a rainfall gauge and an anemometer. Powered by photovoltaic panels and batteries, it operates uninterruptedly under variable weather conditions, with data collected being sent via WiFi to a Web API that adapts the MZDN-HF (Meteorological Zone Delimited Neural Network–Hourly Forecaster) model compilation for Brasilia to produce accurate 24 h multivariate forecasts, which were evaluated through MAE, RMSE, and R2 metrics. Installed at the University of Brasilia, it demonstrates robust hardware performance and strong correlation with INMET’s A001 data, suitable for climate monitoring, precision agriculture, and environmental research.

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Thomas Alexandre da Silva www.mdpi.com