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Water is an essential resource for human life and for agricultural food production, climate change and the increased demand for water resources, has already impacted the availability of this resource in the world, in view of future forecasts of scarcity its rational use will be increasingly demanded. Thus, more efficient irrigation systems that optimize water use and reduce water loss will be important tools to help agriculture in the future. This work aims to develop and calibrate an intelligent and autonomous system for determining reference evapotranspiration (ETo), and precise irrigation control optimized for IoT operation, with data storage in a cloud database. Intelligent system integrates: mechanical weighing lysimeter; sensors and actuators commanded by a digital controller based on a microcontroller platform, connected to the internet through a Wi-Fi communication interface to cloud computing services models: platform as a service (PaaS) and software as a service (SaaS). The operation test results reveal that the system is capable of accurately measuring ET O values, consistent with the values estimated by the FAO-56 standard method, with high sensitivity and precision for determining mass variations, with an R² Correlation coefficient = 0.999321, and coefficient of determination of adjusted R² of 0.999321. Being a viable option for application in precision agriculture.
Arruda et al. (Fri,) studied this question.
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