Study Of Predicting Greenhouse Energy Consumption And Crop Yield And Design Of Android Monitoring System

The environment control method has been one of the most important techniques in modern greenhouse,which can promote sustainable development of agriculture in China.In order to improve the efficiency of agricultural production and increase the economic inco me,the Intelligent monitoring of greenhouse is required to realize a greenhouse with high yield,high quality.Greenhouse intelligent monitoring method builds a mathematical model of crop growth as a theoretical basis to develop a greenhouse expert control system.This study designs a greenhouse intelligent monitoring system as guidance of greenhouse heating and predicts the crop yield,which considers the relationship between Greenhouse heating energy consumption and the crop yield.According to the green house energy and material balance principle,the greenhouse energy flow model of a Venlo type greenhouse was established.And a material flow model is developed by considering the photosynthesis,respiration of the crop,and distribution of the material flow process.In order to improve the accuracy of the greenhouse model,the material energy flow model is established by using optimization algorithm for parameter identification.Compares the advantages and the disadvantages of traditional genetic algorithm and particle swarm optimization algorithm,a modified hybrid algorithm of particle swarm optimization and genetic algorithm(improved PSO-GA)was presented to identify the parameters of the model.The PSO-GA algorithm uses the self-adaptive operator to improve the convergence speed and convergence precision of the algorithm,which can avoid trapping in local optimum.Comparing with the GA algorithm,the improved PSO-GA has the advantage of convergence speed.The greenhouse energy flow model uses three kinds of algorithms to identify the parameter by considering the environment and greenhouse energy consumption data of the experimental greenhouse.The results confirm that the identification speed and identification precision of improved PSO-GA algorithm is 23% and 1.5% better than GA and PSO algorithm respectively.The simulated Greenhouse heating energy consumption of greenhouse energy flow model has the same trend of the experimental greenhouse energy consumption.The difference between simulated energy consumption and tested energy consumption is limited in 8.9%,which proves that the greenhouse energy flow model can used for the future research.The material flow model was used to study the relationship between temperature and crop yield in greenhouse.The results show that the crop yield increased by 24.5% with the average temperature increased from 14.9 ? to 25.9?,and the energy consumption increased more than 100%.A greenhouse remote monitoring system based on Android platform is presented by using the greenhouse energy flow model and the material flow model.The system includes the embedded system based on CAN bus,local greenhouse monitoring host and Android remote client.