Xinfa W. Environmental coupled multi-factor precise regulation and optimization for an artificial light plant factory based on a growth model

The dissertation is dedicated to solving an urgent scientific and technological problem in the field of Mechanization and automation of agricultural in modern agricultural production: innovating multi factor coupling precise regulation and optimization technology for the environment inside artificial light plant factories, in order to improve comprehensive resource utilization and reduce crop’s industrial production costs. To meet the requirements of energy conservation and environmental protection and not be affected by external climate and land limitations, the construction of an artificial light plant factory in an enclosed and insulated chamber should be the best option. After research, we took the lead in proposing the concepts of modern building greenhouses and intelligent building greenhouses, and recommended building artificial light plant factories in urban areas and constructing larger scale intelligent building greenhouses plant factories to improve the building performance of plant factories, thereby ensuring permanent use and long-term production and operation. The urban intelligent plant factory is a highly intensive modern agricultural production system that can continuously provide the most suitable environment for plant growth and achieve high-quality and efficient production of plant products through precise environmental regulation techniques and mechanization, automation, digitization, intelligence, industrialization and factory technology. Moreover, this production method can adopt a "local production, local sales" operating model, continuously producing organic, green, clean, pollution-free, and fresh-eating plant products throughout the year, improving people's living standards, and ensuring the safety of the "vegetable basket" and food security. This is very important for modern Ukraine, for China, and even for all countries in the world. Object of research - theories and methods for constructing plant growth models based on deep learning algorithms; the overall composition, program architecture and development prospects of an artificial light plant factory; and the techniques and methods for mechanization, automation and intelligent regulation and optimization of the production environment. The subject of research - is the design and development of mechanized, intelligent, industrialized, factorized, periodical and modern plant production systems that can be built in urban areas, and the analysis and study of their system composition and architecture; the studies of the theories and methods for building plant growth models based on IoT, big data technologies and deep learning algorithms, which are different from traditional mathematical algorithms; the studies of the machines, means and methods for the coupled multi-factor precise regulation and optimization of the environments in the artificial lighting factory based on a plant growth model. The purpose of the work is to create and improve modern, intensive plant production complexes and systems that can be constructed in urban areas, independent of geo-climatic and land resource constraints, and to study the theory, law, methodology, and technology of mechanized, automated, intelligent, and precise control and optimization of plant growth and production environments of artificial light plant factories in buildings. The ultimate goal is to improve and optimize regulation strategies of the environment through intelligent and precise environmental regulation technologies, increase resource utilization efficiency, and reduce the cost of plant industrial production products.