Design and research of digital twin system for multi-environmental variable mapping in plant factory

Abstract

Internet of Things (IoT) technology develops rapidly and is increasingly used in the field of facility agriculture, the emergence of digital twin technology provides a possibility for the intelligent management of facility agriculture. In this study, IoT and digital twin technologies are combined to design a digital twin system for mapping multiple environmental variables in plant factories to realize the intelligent management and help plant factory managers make intelligent decision-making management schemes. The system includes a multi-environmental variable parameter acquisition system and an environment variable control system based on Arduino, a multi-environmental variable data monitoring and remote environment control system based on Android, and a multi-environmental variable mapping digital twin model. IoT and computer development technologies are used to monitor environmental parameters and control the state of various equipment in plant factories and realize the connection between things and networks. Digital twin technology maps the multi-environmental variables of plant factories to digital twin and intuitively feeds back the parameters of the multi-environmental variables to the plant factory managers, completing the connection between people and things. By combining the IoT technology with digital twin technology, a digital twin system based on multi-environmental variable mapping in plant factory is established, so that the parameters of environmental variables such as CO2, temperature and humidity in plant factory can be accurately adjusted according to the different needs of different stages of plant growth, and it can help plant factory managers to realize intelligent decision-making.