Calibração de sensores capacitivos de baixo custo utilizando a plataforma arduíno

Abstract

At a time of extreme concern about water scarcity, the use of sensors to estimate soil water content is of great importance. Quick decisions, using instant data, are the basis for managing water resources and making decisions in the multiple uses of water. However commercial platforms are still very expensive and the development of more accessible systems is essential. In this way, the objective of the study was to verify factors that interfere in the calibration of capacitive sensors v1.2 to estimate the water content in the soil using the Arduino platform. Firstly, a sensor calibration bench was built, consisting of a total of 18 sets (sensors + soil sample) for data collection and storage. After this step, three types of soil were collected at two different depths and three different volumes of samples, where they were later saturated and left to dry on balances on the calibration bench. To evaluate the results obtained, statistical resources were used, such as: Pearson Correlation Analysis (r), Simple Linear Regression, 2nd Order Polynomial Regression, Root Mean Square Error (RMSE), Willmott Index (Iw) and Performance Index ( Id). It was possible to verify that factors such as soil type, sample volume and the time interval between collections affect the final result in the performance of these sensors.