STRUCTURAL AND ALGORITHMIC FORMALISATION OF SOFTWARE FOR COMPREHENSIVE TRANSFORMATION OF SPATIAL AND TEMPORAL DATA OF AGRICULTURAL MONITORING

Abstract

This article addresses a relevant scientific and practical problem arising from the need for highly efficient information-oriented solutions for transforming spatial and temporal agromonitoring data received in real time from distributed field devices. The aim of the study is to substantiate and formalise a structural and algorithmic model of software that enables multilevel aggregation and processing of agromonitoring results within an integrated information technology framework, based on event-driven analytical principles and a fog computing architecture. The research presents both contextual and functional diagrams of the software and algorithmic infrastructure for agricultural yield prediction systems, encompassing the key stages of data acquisition, statistical and intelligent processing and generation of interpretable decisions. The study also describes the operational foundations of the structural and functional interaction model across computational levels and synthesises sequence diagrams for data exchange and activity diagrams for software modules. A generalised formal expression of the logic for the comprehensive software-based transformation of agromonitoring data has been proposed. The obtained results provide a functional basis for implementing intelligent information and digital solutions in agriculture, particularly in deploying automated decision support systems operating in real-time environments. The prospects and importance of further research on the synthesis of software and algorithmic support for information-oriented crop yield forecasting are substantiated on the basis of the proposed formalized description of the process of intellectual transformation of agromonitoring data using modern intelligent information and digital technologies.