Expert Systems of Program Management in Precision Farming

Abstract

In agriculture, the volume and quality of the use of modern technologies, including systems for collecting, storing and processing data, is noticeably growing. This increases both the amount of data and the need for high-quality processing and reliable conclusions that you can rely on when making decisions. The lack of information for decision making leads to the fact that in the process of cultivating crops, up to 40 % of the crop is lost. Further automation of processes at all stages of the production cycle represents a higher level of digital integration, which affects the most complex organizational changes in the agricultural business, but their implementation can dramatically affect profit and competitiveness of products. The modernization of the agricultural sector is based on the transition to «intelligent agriculture». The greatest interest to science and practice is the intellectualization of agricultural technology management, where the basis is expert systems in which management decisions are made through knowledge bases (KB), formed through analytical control systems located in data centers. In this paper, we consider expert systems for the state control of spring wheat. To this type of management we attribute the task of preliminary formation of the sequence of technological operations on one growing season. In the cloud information system, the generated knowledge bases are transferred from the data center to local management systems at the request of consumers.

Digital Technologies, Internet of Things and Cloud Computations Used in Agriculture: Surveys and Literature in Russian

“…One of the most promising areas for improving the efficiency of agricultural production planning is the use of intelligent technologies to systematize agro-technological knowledge by creating a specialized software package for receiving, primary processing, formalization, storage and presentation of knowledge in the field of crop production. The lack of information for decisionmaking leads to the fact that up to 40% of the crop is lost in the process of cultivating [107]. The structure of such a database and its attributive information, which is necessary for decision-making in the production of crop products, is considered in detail in [108].…”

“…The works [107,114,115] propose a method for building expert decision support systems (DSS) in precision farming. The methodology provides for the use of local DSS and a cloud-based knowledge base (KB).…”

“…This KB is transferred to the local DSS. The proposed method has been tested for solving the following problems: the formation of strategies for applying mineral fertilizers and long-acting ameliorants in crop rotations of various types [114], managing the state of spring wheat by forming a sequence of technological operations in one growing season [107], choosing the optimal date for harvesting fodder from perennial grasses [115]. When solving the first problem, an algorithm was developed in [114] that minimize the risk of crop losses and overspending of mineral fertilizers and ameliorants.…”

“…To select the best option from the KB e, the pattern recognition method is used. To form a KB cloud for managing the state of spring wheat, in [107], algorithms were developed for the formation of optimal programs that minimize the risks of losses in the spring wheat crop. The local DSS selects from the obtained KB the closest optimal programs for the application of mineral fertilizers and irrigation during the growing season.…”