Reference architecture design for developing data management systems in smart farming
Ngakan Nyoman Kutha Krisnawijaya, Bedir Teki̇nerdoğan, Cagatay Catal, P.P.J. van der Tol
Abstract
The traditional data management systems prove inadequate to handle the volume, velocity, and variety of the data within farm business processes. Smart farming technologies offer advanced data management systems as a practical solution to these challenges. However, data is complex and originates from many sources; hence many aspects of data must be considered during the data management design of smart farming systems. This study proposes a reference architecture for data management in smart farming, developed through domain analysis and architecture modeling approaches. The domain analysis provides insights into the common and variant features and modules of the smart farming system, resulting in a blueprint representing family features across various smart farming domains. The effectiveness of the proposed reference architecture has been evaluated through two case studies, demonstrating its efficacy in designing data management systems for smart farming. The study found that the percentage of reused modules in the case studies, compared to the provided reference architecture, was 82.6%. The outcomes of this research will pave the way for further exploration in smart farming, particularly addressing data management issues within smart farming systems. • Feature-driven domain analysis on data management systems in smart farming. • A feature-driven architecture design approach for data management systems. • Architecture modeling of data management systems using multiple architecture views. • Approach is evaluated using case studies from large research and industrial project. • Important lessons learned and challenges are discussed.