Prototype of a self-sustainable weather station for real-time monitoring of climate variables in Salinas
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This research proposes the development of a low-cost weather station prototype integrating microcontrollers, environmental sensors, and IoT technology, aiming to evaluate its measurement accuracy through comparison with official data from Ecuador’s National Institute of Meteorology and Hydrology (INAMHI). The study examines key meteorological variables, including temperature, humidity, UV-A radiation, air quality, atmospheric pressure, and wind speed/direction, employing an experimental quantitative methodology structured in sequential phases: technological architecture design, system implementation, and data validation. For data validation, rigorous statistical methods were applied, including: individual error determination, standard deviation analysis, margin of error calculation, and Mean Absolute Percentage Error (MAPE)1. Results demonstrate acceptable error margins across critical variables: temperature measurements showed a mean error of ±0.3°C (MAPE: 1.15%), humidity displayed a -2.8% bias (MAPE: 6.7%), while atmospheric pressure achieved exceptional precision (MAPE: 0.034%). This work validates the prototype’s technical feasibility. It establishes a methodological framework for optimizing meteorological sensors in coastal environments like Santa Elena, Ecuador, ultimately contributing to more accessible and reliable environmental monitoring systems.
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