Data Integration for Precision Agriculture - Challenges and Opportunities for the Database community
Resumo
The last years the precision agriculture transformed one of the most ancient activities into a humongous source of data. This can happen by means of sensors that monitor continuously the physical environment (e.g., satellite imagery, high technology machinery, micro weather stations) producing large quantities of data in an unprecedented pace. Although there are many papers describing how to use this data (e.g., in modern Big Data systems, as the input of Machine Learning pipelines), today this is a virtually impossible task without a huge effort conciliation and integration. There are many research opportunities that emerge from this scenario, for instance data accessibility through integration methods, new tools (e.g., visualization, ETL tools), and novel datasets and benchmarks. This is specially interesting in the Brazilian context, our country have more than 800 thousand of hectares of arable land and the agribusiness represents almost 30% of our Gross Domestic Product (GDP). This paper presents the experience of four years of working at Leaf Agriculture, the goal is to list the challenges and opportunities for data integration in the precision agriculture.
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