摘要
针对传统水产养殖水质监测系统不能提前预警和通信延迟高的问题,提出一种带有溶氧预测的低延迟无线传感水质监测平台。本研究搭建了4个水质监测节点,通过LoRa模块与汇聚模块进行通信,实现了水质数据的实时监测。应用边缘计算的策略,将云服务器的计算和系统控制任务卸载到上位机来降低系统延迟。上位机更新本地和云服务器的数据,同时基于小波变换和长短期记忆网络(WT-LSTM)模型实现溶氧预测功能。结果显示:与其他预测模型相比,WT-LSTM模型效果更好;pH、温度、溶氧、电导率和氨氮监测数据的相对误差,分别小于1.4%、0.7%、0.2%、12%、5%;基于评测系数分析,溶氧1 h的预测结果比较准确,可作为溶氧预警的参考。本平台可以在低成本、低延迟的情况下,实现水质数据的实时监控,并完成1 h内溶氧的预测,使得系统对增氧机的控制更加合理化、智能化。
In order to solve the problems that the traditional aquatic water quality monitoring system could not give early warning and the communication delay of the system was high,a low delay wireless sensing water quality monitoring platform with dissolved oxygen prediction was proposed.In this study,four water quality monitoring nodes were set up,and the real-time monitoring of water quality data was realized through the communication between the LoRa module and the convergence module.To reduce the system delay,the strategy of edge computing is applied to offload the computing and system control tasks of cloud server to the upper computer,which updates the data of local and cloud server,and realizes the prediction function of dissolved oxygen based on the wavelet transform and the Long Short-Term Memory(WT-LSTM)model.The experimental results show that,compared with other prediction models,WT-LSTM model has better effect;the relative errors of pH,temperature,dissolved oxygen,conductivity and ammonia nitrogen in monitoring data are less than 1.4%,0.7%,0.2%,12%and 5%,respectively;based on the evaluation coefficient analysis,the prediction result of dissolved oxygen at 1 h is more accurate,which can be used as a reference for dissolved oxygen early warning.The platform can realize the real-time monitoring of water quality data and complete the prediction of dissolved oxygen in 1 h under the condition of low cost and low delay,which makes the control of the aerator more reasonable and intelligent.
作者
翁正
陈明
池涛
刘亚蕊
WENG Zheng;CHEN Ming;CHI Tao;LIU Yarui(College of Information Technology,Shanghai Ocean University,Shanghai 201306,China;Key Laboratory of Fisheries Information,Ministry of Agriculture and Rural Affairs,Shanghai 201306,China)
出处
《渔业现代化》
CSCD
2021年第4期43-50,共8页
Fishery Modernization
基金
江苏现代农业产业关键技术创新项目(CX(20)2028)。
关键词
水质监测
低延迟
溶氧预测
水产养殖
传统养殖
氨氮
温度
water quality monitoring
low latency
dissolved oxygen prediction
aquaculture
traditional aquaculture
ammonia nitrogen
temperature
