Irrigation advisory services (IAS), as well as decision supports systems (DSS) designed for irrigation support, are powerful management instruments used to improve efficiency in irrigation water use. In this context, a preliminary research was conducted in an open field asparagus crop in order to: evaluate Ploovium, a DSS based on IoT, artificial intelligence and machine learning, for a predictive optimization of irrigation. This study was carried out in collaboration with LAORE (Agricultural Development Regional Agency of Sardinia Region), and AGRIS Research Centre, on an asparagus in a farm in Villasor (CA). Experimental activities were carried out from August 01 2018 to July 24 2019. Ploovium is an innovative cloud-based solution, able to produce provisional data on the soil’s water behaviour by the following equipment: i) a weather station for measuring rain, air temperature and humidity; ii) a datalogger with soil water sensors at two different depths (30 cm and 80 cm). Ploovium allowed to optimize water consumption and, consequently, to manage the crop in a more efficient way, and to prevent any possible risk with a degree of reliability normally higher than 99%. Ploovium has proved to be a low cost and know-how solution to support the users to save water and irrigation-related costs and to provides precise hints about the texture of the soil.
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