DESIGNING AN AGRICULTURAL ADVISORY SYSTEM USING MACHINE LEARNING

Abstract

A draft advisory system is presented that should use machine learning algorithms. These algorithms will allow analyzing the data obtained by various sensors, processing them and making accurate consultations to an agronomist, indicating the names of plant species that are appropriate or inappropriate for growing in the type of soil under study. To implement the project, a number of machine learning algorithms, various libraries of the Python programming language, and the PostgreSQL database management system were studied, Preliminary data were also collected and processed using various sources (for example, a table of the placement of the main types of soil and growing plant species in the agro-climatic zones of Republic of Armenia).