Design Of Information Management System For Freshwater Fish Aquaculture

The development of smart agriculture has optimized the traditional agricultural production mode and improved the efficiency of production management,which has been gradually applied to actual production.Domestic scholars’ research on smart agriculture mostly focuses on the fields of planting and animal husbandry.In view of the low degree of digitalization and the lack of aquaculture information management platform in the aquaculture field,this thesis used Web technology to develop a set of freshwater fish aquaculture information management system,established a water quality meteorological information prediction model,and conducted functional tests and performance tests.The main findings were as follows:(1)A freshwater fish farming information management system was developed.Using the Express.js back-end framework in Web development technology,the Vue.js front-end framework and My SQL database technology,the freshwater fish farming information management system was developed,including the login module,base information display page,farmer module,daily record module,production management module,equipment module,material management module,environmental monitoring module,knowledge base module and expert consultation module.It realizes the functions of real-time monitoring of water quality and meteorological information of breeding environment,management of daily affairs of breeding,production records,equipment maintenance and management,remote control of equipment,breeding consultation and query of breeding specifications.(2)A water quality meteorological prediction model was established.The ARIMA/ARMA,VAR,VECM water quality meteorological information prediction model was established through Python,and the values of ten indicators such as water temperature and dissolved oxygen were predicted in the next 8h by using the historical data of water quality meteorological within 7d.The results show that in terms of water quality prediction,the VAR model has high prediction accuracy for dissolved oxygen,ammonia nitrogen and turbidity,and the average relative errors are 0.323%,2.250% and 0.002% respectively;The ARIMA/ARMA model has high accuracy in predicting water temperature,with a relative error average of 0.454%;The VECM model has a high accuracy for predicting p H,and the average relative error is 0.547%.In terms of meteorological prediction,the VECM model has a high prediction accuracy for air pressure,with a relative error average of 0.020%,the VAR model has a high accuracy for rainfall prediction,the absolute error average is0.005 mm,and the average minimum relative error of temperature,wind speed and optical radiation is 5.993%,30.506% and 33.830% respectively.By comparing the prediction results of the model with the measurement accuracy of the sensor,the results show that the relative and absolute errors of the prediction of seven indicators of dissolved oxygen,water temperature,ammonia nitrogen,turbidity,p H,air pressure and rainfall meet the requirements,while the prediction accuracy of the three indicators of air temperature,wind speed and optical radiation is low and does not meet the accuracy requirements of the sensor.(3)The functional and non-functional performance of the system was tested.Through the Chrome browser,the Postman interface test software carried out functional and nonfunctional tests of the freshwater fish farming information management system.The result of the functional test is: each interface of the system has passed the test,and the interface can be successfully requested in the corresponding page at the front end of the system,the correct content can be displayed,and the corresponding function can be realized,that is,the function of the system can be used normally,which meets the design requirements.As a result of the non-functional test,the system passed the reliability test and the safety test.In summary,the freshwater fish farming information management system developed in this thesis can realize the information management of farming information data,which can assist the actual production and improve the production management efficiency,and has certain promotion value.