Hypermedia Multi-Agents, Semantic Web, and Microservices to Enhance Smart Agriculture Digital Twin

Yogeswaranathan Kalyani, Rem W. Collier

Abstract: In recent years, Digital Twin (DT) technology has gained a lot of interest due to its potential for improving efficiency, reducing costs, and optimizing processes in a variety of industries, including manufacturing, healthcare, and agriculture. However, in the agriculture field, DT technology is still in its early stages. In this paper, we propose a novel approach for developing digital twins that leverages a suite of microservices and multi-agent systems to integrate cognitive decision-making capabilities with the concepts of Hypermedia agents, semantic web, and multi-agent microservices (MAMS). This approach involves implementing digital twins as collections of small, independent services that can be combined and customized to support a wide range of applications and scenarios.