SOFTWARE AND HARDWARE OF THE MONITORING AND CONTROL COMPUTER-INTEGRATED SYSTEM OF GREENHOUSE SOIL HUMIDITY BASED ON FUZZY LOGIC

Abstract

Relevance. Irrigation of the greenhouse soil plays an important role in the cultivation of greenhouses plants. Given the significant number of existing systems and methods on monitoring and irrigation of soil in the world, there are almost no systems that are based on fuzzy logic taking into account the growing season plants factor. Consequently, an urgent scientific task arises on developing of the monitoring a method of the greenhouse soil moisture content taking into account the types and periods of the greenhouse crops growing season. Purpose. Development of the method and implementation of the system prototype on monitoring and control of the greenhouse soils moisture content based on the fuzzy logic rules taking into account the types and periods of plants vegetation. Methodology. In course of the research, the following methods have been used: analysis and systematization of well-known scientific and applied results, experimental tests of computer-integrated equipment, synthesis and testing of hardware and software computer models on systems automation, comparative analysis of the modeling and experimental tests results. Results. The main scientific and applied results include: the algorithm and model for assessing plant parameters from the growing season, the mathematical model of the soil moisture dynamics, the fuzzy rules base for moisture control taking into account the types and periods of the agricultural crops, an experimental full-scale model of the computer-integrated system. Scientific novelty. The method of the computer-integrated monitoring and control of the greenhouse soils moisture content based on fuzzy logic has been developed, which, unlike the known ones, takes into account the influence of types and periods of growing crops, which allows precision control of relative humidity in real time. Practical significance. The mathematical model of the soils moisture dynamics, the structural diagram and algorithm of the system’s operation, the fuzzy logic rules base, the program code of the system and experimental model of the system have been obtained. All of these results can be scaled and modified depending on plant types, soil type and volume, planted surface area and fuel pump capacity. Figures 15, tables 7, references 22.