期刊论文

中文

农业工程

2095-1795

2019

9

8

31-34

10.3969/j.issn.2095-1795.2019.08.011

湖南农业大学创新试验项目（项目编号:XCX18049）；

本校为第一机构

为应对湖泊日益加重的水质污染问题,方便管理人员及时查看水质信息,应用灰色理论建立水质参数预测模型,设计了一款基于Python Flask框架的水质污染监测预测的Web系统,实现了对水域水质参数的监测与预测。系统通过无线传感器网络实时采集水域水质数据,并传输到One Net云端; Web系统访问云端,将云端数据转存到远程服务器的数据库上;用户通过浏览器访问Web系统,实时监测水域水质;同时通过灰色模型的预测算法,计算出水质参数中短期变化值,最后将数据以图形形式向用户进行可视化展现。测试结果表明,系统数据传输准确,功能运行可靠,具有较好的实用性与应用价值。

In order to address increasing severe water pollution issues,as well as allowing relative technician better knowreal time water parameters information,a water monitor system was put forward,which was developed base on Python Flask,a microframework for website and apply grey model theory,a water parameters early warning model was established.System was able to collect real time water parameters’data via wireless sensor network,then upload collected data into One Net cloud.Web system was deployed on a local server,programed to access the cloud p...