基于KNN算法的仪表实时监控边缘平台

为了对旧式仪表进行改造、升级,实现数字化、智能化的实时监控,文章提供了一种基于KNN算法的仪表实时监控边缘平台。首先,我们对其整体架构进行设计,使用树莓派模块实现图像采集、图像传输边缘计算功能,在云端服务器使用OpenCV集成的算法对图像进行预处理:灰度化、降噪、旋转、边缘线条提取、滤波、二值化处理。接着,采用KNN算法进行数字的智能识别,并将结果反馈到客户终端中。结果表明,可以智能化的对仪表盘数值进行实时的监控、统计、报警等功能,满足了仪表盘数字化、智能化的管理需求。

In order to transform and upgrade the old instrument and realize digital and intelligent real-time monitoring,this paper provides a real-time monitoring edge platform based on KNN algorithm.First of all,the overall architecture is designed,and the Raspberry Pi module is used to achieve the functions of image acquisition and edge calculation of image transmission.In the cloud server,the integrated algorithm of OpenCV is used to preprocess the image:graying,noise reduction,rotation,edge line extraction,filtering,and binarization processing.Then,the KNN algorithm is used to intelligently identify the numbers,and the results are fed back to the customer terminal.The results show that it can intelligently monitor,count and alarm the values of the dashboard in real time,which meets the needs of digital and intelligent management of the dashboard.