Building an Interoperable IoT Ecosystem for Data-Driven Agriculture

Climate change with its extreme weather conditions and the shift to organic farming pose new challenges for crop production in Europe. Continuous and dense monitoring of crop condition and environmental parameters in the fields using various Internet of Things (IoT) devices creates Big Data for data-driven agriculture and provides the opportunity to address the above challenges. However, it is extremely complex to develop a large-scale system that integrates a variety of heterogeneous data sources to provide farmers and agronomists with simple and usable tools, such as assessing current field conditions, estimating crop stress levels, or determining the best time to apply certain cultivation practice. One of the solutions of this problem is to design and implement an interoperable IoT ecosystem for data-driven agriculture that turns the data from multiple sources into knowledge, giving rise to valuable insights and appropriate decisions based on the analysis of sensor measurements delivered from IoT devices. The paper presents the architecture and design of an ecosystem for data-driven agriculture which includes a cloud-native and microservice-based IoT platform. The novel contribution of our proposed approach is the IoT platform with effective interoperability solutions for integrating different types of edge devices used in agricultural practices for continuous monitoring of agrometeorological and crop conditions, as well as with flexible means for integrating different analytical and data visualization services ensured by strict access control mechanisms.