Research On Building Greenhouse Monitoring System And Temperature Random Model Of Greenhouse Based On Internet Of Things

Since the 21 st century,the application of Internet of Things technology in many industries has made great progress.In the intelligent management of modern greenhouse environment,how to apply this technology to it well has a milestone significance for the improvement of the intelligent level of facility agriculture.Combining Internet of Things technology and modern greenhouse,this paper builds an intelligent greenhouse which can collect real-time data.Based on the heterogeneous network of Zig Bee and GPRS,this paper effectively combines the characteristics of low power consumption and low cost of Zig Bee network with the long transmission distance of GPRS network,so as to realize the function of greenhouse remote and real-time monitoring environment.The data collected by remote greenhouse is processed and displayed by the host computer,which realizes the functions of automatic monitoring of greenhouse environment,data management and remote viewing of greenhouse real-time status.Greenhouse uses film-covered materials to isolate the external environment and form its own space to construct a special microclimate environment.Sunshine radiation,air temperature and humidity,carbon dioxide concentration and air circulation conditions all affect the greenhouse microclimate environment at all times.Temperature is one of the leading factors that have far-reaching impact on the greenhouse microclimate environment.How to construct a scientific and effective greenhouse temperature control system has far-reaching significance for reducing greenhouse energy consumption and promoting plant growth and development.Because the greenhouse microclimate environment has the characteristics of non-linearity,time-varying and strong lag,it is difficult for the general greenhouse temperature control system to effectively control the greenhouse microclimate.It is necessary to determine the greenhouse temperature change model in order to effectively predict and achieve the purpose of accurate control.Therefore,it is necessary to model the greenhouse temperature control system before it is established.Traditional control methods require accurate mathematical models based on controlled objects.Therefore,for the realization of greenhouse environmental control,the establishment of greenhouse environmental model is an indispensable prerequisite.In the past decades,a lot of research work has been done on the greenhouse climate simulation system,and many research results on this issue have been put forward.Generally,there are two different ways to calculate greenhouse models.One is the mechanism modeling method based on physical change process,the other is the identification modeling method based on input-output data analysis.On the other hand,stochastic modeling has played an important role in many fields of science and engineering.Real benefits can be achieved by using stochastic models rather than deterministic models.Firstly,the real life is basically stochastic rather than deterministic,and the stochastic model can be more in line with the actual situation of greenhouse temperature changes;secondly,stochastic disturbances may help stabilize the system in some cases.However,the stochastic model of greenhouse temperature system has not been properly studied,and it is still an interesting and challenging research topic.Based on this situation,this paper considers the problem of stochastic modeling of greenhouse temperature,considering that ventilation is disturbed by white noise,assuming that the disturbance is independent and uniformly distributed white noise,establishes a stochastic differential equation model of greenhouse temperature system;furthermore,according to the maximum likelihood estimation method,the unknown parameters of drift term and diffusion term are obtained by using observed data;finally,through the method of maximum likelihood estimation,the drift term and Comparisons of numerical simulation for predicting and measuring temperature.