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.

Ploovium: a decision support system for increasing water use efficiency of irrigated crops / Martelli, A; Altobelli, F; Dalla Marta, A; Ciarletti, M. - ELETTRONICO. - (2020), pp. 328-332. (Intervento presentato al convegno International Workshop on Metrology for Agriculture and Forestry tenutosi a Trento nel 4-6 Nov. 2020).

Ploovium: a decision support system for increasing water use efficiency of irrigated crops

Dalla Marta, A;
2020

Abstract

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.
2020
2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
International Workshop on Metrology for Agriculture and Forestry
Trento
4-6 Nov. 2020
Martelli, A; Altobelli, F; Dalla Marta, A; Ciarletti, M
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1239596
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