Development of an application to make knowledge available to the farmer: Detection of the most suitable crops for a more sustainable agriculture

Abstract

Precision agriculture has different strategies to collect, process and analyze data of different types and nature to be able to make decisions that improve the efficiency, productivity, quality, profitability and sustainability of an agricultural production. Specifically, crop sustainability is directly related to reducing costs for farmers and minimizing environmental impact. In this paper an application to help in the decision making about the most convenient type of crop to plant in a certain zone is developed, taking into account the climate conditions of that zone, in order to make the crop sustainable. This application is integrated within an Internet of Things system, which is adaptable and parameterized for any type of crop and zone. The components of the Internet of Things system are described in detail and a fuzzy clustering model is proposed for the intelligent module of the system. This fuzzy model focuses on making a grouping of zones (zone management), taking into account the climatic conditions of a zone. The model manages fuzzy data, which allows for more extensive information and more natural treatment of the data. Finally, a real study case for the application proposed is presented using data from Region of Murcia (Spain). For this study case it has been described the whole deployed Internet of Things system. Also, the intelligent fuzzy clustering model to create similar areas in terms of meteorology has been validated and evaluated. In addition, the recommendation and decision support module has been implemented, taking into account real production data and resources needed for the crops in the Region of Murcia (Spain).