R. (2016). A decision support system for managing irrigation in agriculture.

Water is the main limiting factor in agricultural production as well as a scarce resource that needs to be optimized. The measurement of soil water with sensors is an efficient way for optimal irrigation management. However, commercial sensors are still too expensive for most farmers. This paper presents the design, development and calibration of a new capacitive low-cost soil moisture sensor that incorporates SDI-12 communication, allowing one to select the calibration equation for different soils. The sensor was calibrated in three different soils and its variability and accuracy were evaluated. Lower but cost-compensated accuracy was observed in comparing it with commercial sensors. Field tests have demonstrated the temperature influence on the sensor and its capability to efficiently detect irrigation and rainfall events.

a b s t r a c tWater is an essential resource for the development of agriculture. In several locations like the southeast of Spain water is scarce and its cost is high, so optimal management of this important resource is essential. Therefore, the application of irrigation strategies to improve the watering process, affects the profitability of crops quite significantly. It is necessary to carry out the instrumentation of the variables that affect the growing process of the crop (soil, water and plant) and use the techniques associated with this instrumentation to take actions to optimize the production. The system proposed in this paper uses information and communication technologies, allowing the user to consult and analyze the information obtained by different sensors from any device (computer, mobile phone or tablet) in an easy and comfortable way. The proposed architecture is based on different wireless nodes equipped with GPRS connectivity. Each wireless node is completely autonomous and makes use of solar energy, giving it virtually unlimited autonomy. Different commercial sensors for measuring the wide range of parameters of the soil, plant and atmosphere can be connected to the nodes. The data is sent and processed on a remote server, which stores the information of the sensors in a database, allowing further consultation and analysis of data in a simple and versatile way.

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