Design And Implementation Of Intelligent Monitoring System For Fishery Water Quality Based On NB-IoT

China is a large country in fish farming,and the farming scale and output are among the highest in the world,and the quality of fishery water quality is directly related to the efficiency of fishery aquaculture.In the context of the modern interconnection of all things,the introduction of new technologies of narrow-band Internet of Things into fish farming,and the realization of prediction and early warning of fishery water quality,and the improvement of fish farming water quality conditions,will promote the development of informatization and intelligence in fish farming.This paper designed an intelligent monitoring system for fishery water quality based on narrow-band Internet of Things(NB-IoT),which realized real-time monitoring and dynamic prediction and early warning of water environment parameters in the process of fish farming,and automatically adjusted the fishery water quality.At the same time,the system could adjust the water quality in advance according to the dynamic prediction and early warning information to ensure the safety and stability of fishery water quality.This paper mainly did the following work:(1)Designed the monitoring terminal of fishery water quality,proposed and adopted NB-IoT to build a distributed monitoring network of fishery water quality,and completed the system hardware design.The field terminal equipment included water quality collection terminal and control terminal.Utilized the wide coverage,low power consumption and massive connection of NB-IoT,the information interaction between the field terminal and the remote server was realized.The system hardware circuit adopted modular design,including NB-IoT wireless communication module,core controller module based on STM32 and related peripheral interface circuits,which will facilitate later upgrade and maintenance to ensure the stable operation of the system.(2)System software design was completed based on application requirements,mainly included embedded software design,cloud server design,and mobile clientsoftware design.The embedded software design was based on STM32 to realize the information interaction between the field terminal and the cloud server and field device control.In the cloud server part,the communication server was established to realize the instant interaction between the bottom device and the upper application.Based on the relational database MySQL,the system database design was completed.The database interface program was designed to achieve water quality data query,analysis and other functions.At the same time,the mobile client was designed to achieve water quality data query,prediction and early warning information query,control and management of field terminal equipment and other functions.(3)A prediction and early warning model of fishery water quality was constructed.Aimed at the problem of low accuracy of support vector regression(SVR)in the prediction of fishery water quality,the EEMD-GWO-SVR combined model prediction method was proposed and adopted,based on ensemble empirical model decomposition(EEMD),grey wolf optimizer(GWO),and SVR.The combined model prediction method established a prediction model of fishery water quality.The test results showed that the model had better forecasting ability,met the actual demand of online prediction of fishery water quality and provided data support for water quality early warning control.Based on the prediction of fishery water quality,a early warning model of fishery water quality was established.(4)Completed system deployment and testing.According to the overall design requirements of the system,the system was installed,deployed,and tested as a whole.The test results showed that the on-site NB-IoT signal quality was good and the signal was stable,the system communication was stable and reliable,and the data monitoring was accurate and timely.At the same time,the mobile phone client test proved that the system function was complete and stable,and the on-site water quality was safe and stable,which met the demand of monitoring fishery water quality.