Novel Sustainability-Driven IoT Prescriptive Analytics for Improving Irrigation Practices in Fruit Trees

The Internet of Things (IoT) and data analytics are disruptive technologies that can contribute to the sustainable development goals defined by the United Nations in 2015, e.g., by improving water-use efficiency and maximize agricultural production. However, the combination of these technologies is still very limited in agriculture. In this project, we develop innovative sustainability-driven IoT prescriptive analytics techniques that can provide irrigation advice with the main objective of maximizing sustainability, i.e., maximize production and minimize irrigated water. To achieve this, we will first predict the Stem Water Potential (SWP) from real-time data collected using wireless (IoT) soil sensors and weather stations. In spite of being considered to be one of the best indicators of crop water status, the SWP can only be measured manually in a reliable way. Irrigation advice will then be given to keep the predicted SWP at the appropriate level. Our novel analytics techniques will be built for the specific cases of pears and citrus, two very relevant cases worldwide for which we already have very rich data sets and that provide enough similarities and differences to enable a further generalization of the results.