巴基斯坦中小企业低成本数据采集系统的设计与实现

Q4 Physics and Astronomy
Muhammad Imran Majid, Ejaz Malik, Tahniyat Aslam, Osama Mahfooz, Fatima Maqbool
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引用次数: 0

摘要

本文主要针对国内制造业努力实现“工业4.0”的目标和效益,提出了基于工业物联网的低成本、健壮的数据采集系统的开发。本建议旨在促进投资能力有限的巴基斯坦中小企业在传统制造过程中整合DAQ系统。所提出的方法包括Arduino及其物联网数据采集功能,以及自行开发的基于PC的数据采集、图形用户显示和本地SQL数据库中存储收集数据的集中式软件。在传统的低成本数据采集系统中,基于PC的软件取代了多种软件的需求,如用于从工业硬件收集数据的OPC软件,基于Java或PHP的任何GUI和SQL数据存储。工作分析是在消息队列遥测传输(MQTT)协议的帮助下完成的。与市场上昂贵的商业解决方案相比,该项目将在进一步的阶段进行评估,以增加监控功能,以及成本增加最少的数据采集硬件,并进一步升级PC软件,以增加工业4.0的更多功能。利用机器学习算法k近邻算法对敏感数据和非敏感数据进行分类,提高云安全。k近邻算法又称KNN算法,是一种监督式机器学习分类器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of Low-Cost Data Acquisition System for Small and Medium Enterprises (SMEs) of Pakistan
This paper presents the development of low-cost and robust industrial IoT based data acquisition system primarily focused on domestic manufacturing industries striving to achieve goals and benefits of “Industrial 4.0”. This proposes aims to promote DAQ System integration in traditional manufacturing process of the small and mid-sized industries of Pakistan with limited capacity of investment. Proposed method comprises of Arduino and it’s IoT features for Data Collection, along with a self-developed PC based Centralized Software for Collection of Data, Graphical User Display and Storing collected Data in Local SQL Database. PC based Software replaces requirement of multiple software in case of traditional low-cost DAQ systems, like OPC Software for collecting data from industrial hardware, Java or PHP based any GUI and SQL Data storage. The analysis of work is done with the help of the Message Queue Telemetry Transport (MQTT) protocol. This project will be in further stages evaluated to add features of Supervisory Control, along with Data Acquisition hardware with minimum increase in cost and further upgrading PC Software to add more features of Industry 4.0, as compared to costly commercial solutions available in the market. A machine learning algorithm, k-nearest neighbors algorithm has been used to classify sensitive and non-sensitive data for improvising cloud security. K-Nearest Neighbors is also called KNN algorithm which is supervised machine learning classifier.
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来源期刊
Proceedings of the Pakistan Academy of Sciences: Part A
Proceedings of the Pakistan Academy of Sciences: Part A Computer Science-Computer Science (all)
CiteScore
0.70
自引率
0.00%
发文量
15
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