A REVIEW OF METHODS AND DEVELOPMENT PERSPECTIVES FOR INFORMATION-MEASURING AND CONTROL SYSTEMS FOR URBAN PLANTING

Abstract

Background. To enhance efficiency in obtaining plant biomass via the research into existing techniques and development of novel ones is a challenging task. The purpose of the work is to explore increasing productivity and efficiency of nutrient absorption by means of artificial intelligence algorithms and biosensors in the information-measuring and aeroponic cultivation control system for growing plants in urban areas. Materials and methods. Artificial neural network algorithms along with specialized sensors inserted in the root zone of control plants have been proposed. Results. The review analysis results for the existing methods of growing plants have been presented. Major advantages and disadvantages of these methods in terms of specific parameters have been considered. The most effective method has been identified, and novel techniques to increase the efficiency in obtaining plant biomass have been proposed. Artificial intelligence architecture for the information-measuring and aeroponic cultivation control system for growing plants in urban areas has been developed. Conclusions. It has been revealed that provided the proposed techniques were implemented, it would advance the aeroponic method for growing plants in urban areas. The use of artificial intelligence algorithms and specialized sensors in the information-measuring and aeroponic cultivation control system for growing plants would ensure increased productivity and efficiency of nutrient absorption, and reduce maintenance requirements.

Keywords

• information-measuring and control systems for growing plants
• aeroponics
• artificial intelligence
• artificial neural network
• biosensor