Study on Expert Strategic Management Systems in Precision Farming

Abstract

When assessing the modern Internet of Things market, one should consider equipment, solutions, applications connected into a single network along the entire product chain, including the end user. In this work, such linking is carried out on the basis of cloud information technologies. Through these technologies, the intellectualization of agricultural technology management is implemented by creating expert management decision support systems (DSS). The aim of the work is to consider the methodology for constructing the DSS of strategic management in precision farming systems, where this type of management has not been implemented to date. We refer to this type of management the task of forming strategies for the introduction of mineral fertilizers and ameliorants of prolonged action for all years of crop rotations of various types. To solve the problem, an algorithm for the formation of optimal strategies for the introduction of mineral fertilizers and ameliorants is substantiated, which is implemented in the analytical automated control system for agricultural technologies (ACSAT), through which a knowledge base (KB) is formed, transmitted from the cloud system to local DSS. The pattern recognition method is used to select the best option from the knowledge base. The technique is tested on arbitrary initial conditions of local systems, including extreme combinations of initial conditions. Based on the analysis of optimality losses associated with the mismatch of the initial conditions on local DSS and knowledge base, a methodology for controlling the formation of knowledge base, aimed at reducing these losses, has been substantiated.