Organic Computing for Intelligent Agricultural Technology: Perspective and Case Study

Organic Computing (OC) refers to a systems engineering paradigm for designing intelligent technical systems which are deployed in complex real-world environments. With a focus on nature-inspired mechanisms, OC aims at the transfer of principles observable in nature to complex technical systems to endow them with lifelike qualities such as intelligence, flexibility, robustness, and the ability to self-organize. Agricultural engineering develops highly automated and autonomous technology for sustainable agricultural production which must work reliably in dynamic real-world environments. Higher degrees of systems’ autonomy and intelligence require an increasing number of information technology components to Mein Standortinteract over various system levels what in turn increases system complexity. In this article, we cast light on the suitability of the OC paradigm for designing Intelligent Agricultural Technology systems. In a case study, we adopt an OC approach for the optimization of secondary tillage and report on promising empirical results from integrating contemporary artificial intelligence methods into a multi-level system architecture to achieve an intelligent tractor control.