Study On Key Technology Of Water Quality Monitoring Of Crayfish(Procambarus Clarkii) In Rice Field

In recent years,crayfish(scientific name K.serrata)has become the main force of freshwater aquaculture in China because of its advantages of easy feeding,unique taste and rich nutrition.However,the culture of freshwater crayfish requires higher water quality,and the quality of water directly affects the healthy growth and development of crayfish.The use of Internet of Things technology to monitor,predict and predict the water quality of lobster culture,and timely grasp the changes in water quality during the breeding process is of great significance for avoiding breeding risks and increasing lobster production.In this paper,the water temperature,dissolved oxygen and PH values of key parameters of rice crayfish culture were studied.The water quality data pretreatment method and water quality prediction model were studied by using sensors,wavelet analysis and circulating neural network.The main research work of the thesis is summarized as follows:(1)Designed the overall architecture of water quality monitoring system of rice crayfish proposed acquisition of data based on ZigBee technology and GPRS technology methods.Aiming at the problems of complex lobster breeding environment and difficult analysis of water quality parameters,a three-layer water quality monitoring system architecture of sensing layer,data transmission layer and data processing application layer was constructed.The ZigBee technology is used to build the sensing layer of the water quality monitoring system by short-distance,low-power,fast self-organizing network,and the data is collected by the sensor module of the terminal node,and the data is collected to the coordinator node through the ZigBee network.A transmission module is established between the ZigBee coordinator and GPRS,and the water quality data is transmitted through the remote transmission technology GPRS.(2)Research on pretreatment technology of water quality monitoring data for rice grayfish farming.Water quality data were measured using the Grubbs criteria to eliminate bad data.An adaptive weighted data fusion method is realized by using data fusion technology.Experimental results show that this method can obtain better fusion data.The data denoising is realized by wavelet analysis method.The experimental results show that the data denoising process is performed by the cmddnoise function of Matlab software,and the noise reduction effect is obvious.(3)Research on water quality prediction model based on cyclic neural network.In order to predict and predict the water quality data of lobster culture,a water quality prediction model WOP based on cyclic neural network was proposed.The model uses water temperature,pH and dissolved oxygen as input data to predict the dissolved oxygen and pH values of water in real time.The experimental results show that the WOP model can predict water quality data in real time.(4)Implementation of water quality monitoring system for rice paddy shrimp.Based on the above research results,a water quality monitoring system for rice paddy shrimp was constructed.It realizes the data collection of parameters such as temperature,PH value and dissolved oxygen rate of water parameters of ZigBee network,remote transmission of data by GPRS network,water quality data preprocessing,water quality data prediction and other functions.The operation of the system verifies the effectiveness of the appeal research method and model.