Introduction: Conventional stations become obsolete, compromising data collection for teaching and research. The proposed solution is an automated station with open-source hardware (Arduino, Raspberry Pi) and temperature, humidity, atmospheric pressure and precipitation sensors. Performance tests showed that the DHT22 sensor had average deviations of ±1. 5 °C for temperature and ±5% for relative humidity, and BMP280 maintained deviations below 2 hPa. The digital rain gauge was effective in long-term measurements but limited in low-intensity rainfall. The system operated continuously and autonomously, powered by solar energy. The mean square error (RMSE) ranged between 1. 5 and 5. 0 for the main variables, validating its use in educational applications and non-critical monitoring. The total cost of the prototype was approximately R 4, 259. 04, but the project is modular and scalable, allowing replicability and integration of additional sensors (wind, solar radiation, air quality). In addition to resuming the systematic collection of meteorological data, the initiative promotes the practical application of interdisciplinary concepts and contributes to the teaching, research and development of sustainable technological solutions. Theoretical Framework: The meteorological ministration is extremely important to act in a preventive way in climate variations, to reduce the impacts on society. Method: The methodology adopted for the development of the meteorological ministration was divided into four main stages: (1) diagnosis of the current station, (2) requirements gathering, (3) development and assembly of the system and (4) testing and validation of the data. Results and Discussion: The proposed station is a flexible, scalable, and replicable platform that contributes to both teaching and applied research in climate monitoring. Research Implications: The research provides subsidies for the construction of a meteorological ministration with the appropriate instrumentation for the necessary surveys of weather variations. Originality/Value: The study contributes to the understanding of temporal variables and their interrelation, helping to determine the most relevant variables.
Gonçalves et al. (Mon,) studied this question.