Agro 4.0: A data science-based information system for sustainable agroecosystem management

One of the solutions for handling and treating the diverse data related to the sustainability of an agroecosystem is the use of Information Systems and Internet of Things. In this work, we adopt a methodology called Indicators of Sustainability in Agroecosystems (Indicadores de Sustentabilidade em Agroecossistemas – ISA), implement an information system based on Internet of Things and apply Data Science and simulation techniques over the gathered data, from 100 real rural properties. As a result, we have developed a set of tools for data collection, processing, visualization, simulation and analysis of the sustainability of a rural property or region, following the ISA methodology. Two experiments were applied on the dataset collected by the tools: environmental change scenarios simulations on targeted agroecosystems to predict how they affect two ISA scores (Soil Fertility and Water Quality) of involved agroecosystems; Evaluation of Feature Selection models searching for subsets of features good enough to predict the two ISA scores for the dataset with a smaller amount of data necessary. We have that with only 7 of the 21 Indicators present in ISA we can identify the level of sustainability in more than 90% of cases, allowing for a new discussion about shrinking the amount of data needed for the computation of ISA, or remodeling the final computation of the Sustainability Index so other Indicators can be more expressive. Users of the solutions developed in this work can identify best practices for sustainability in participating agroecosystems.