Abstract:

Digital transformation is a reality in the primary sector. The agriculture and agri-food sectors are adapting to the Information Society, i.e, the monitoring of farms and agri-food industries through use of sensors, the Internet of Things (loT), Decision Support Systems (DDS) and the phenomenon of Big Data platforms among others.

Due to the intense and rapid changes observed in these sectors and the high demand for professionals that can adapt to the ever-evolving needs of the market, universities are making a concerted effort to produce professionals who have the necessary skills needed to meet growing corporate demands.

Consequently, the students at the Higher Technical School of Agricultural Engineering of Ciudad Real (ETSIA-CR) will optimize resources by applying new technologies in agriculture through the use of sensors. Four different types of soil moisture capacitive probes (FDR) representative of the current best known commercial brands with their corresponding data loggers were installed in different horticultural and woody crops located at ETSIA-CR.

Students complemented their training, learning in detail the implementation of sensors, operation, technical characteristics, advantages and disadvantages of each one of them, data downloading, the type of soil recommended and, most importantly, the evaluation and interpretation of the results. The monitoring included measurements of soil water content, soil temperature and soil electrical conductivity.

This formative activity links the knowledge learned throughout their studies in subjects such as New Technologies in Agronomy, Irrigation Engineering and Phytotechnology. The objective was to introduce students to the use of digital technology and the interpretation of the data obtained to acquire the skills needed to meet the challenges of today's industry. Thanks to the visualization and knowledge of the water dynamics in the soil it can be to achieve significant savings in water consumption.

Keywords:

precision farming, sensor, soil water content monitoring, smart farming, data-driven agriculture