Big Data Platform for Intelligence Industrial IoT Sensor Monitoring System Based on Edge Computing and AI

Sothearin Ren, Jaesung Kim, W. Cho, Saravit Soeng, Sovanreach Kong, Kyung-Hee Lee
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引用次数: 7

Abstract

The cutting edge of Industry 4.0 has driven everything to be converted to disruptive innovation and digitalized. This digital revolution is imprinted by modern and advanced technology that takes advantage of Big Data and Artificial Intelligence (AI) to nurture from automatic learning systems, smart city, smart energy, smart factory to the edge computing technology, and so on. To harness an appealing, noteworthy, and leading development in smart manufacturing industry, the modern industrial sciences and technologies such as Big Data, Artificial Intelligence, Internet of things, and Edge Computing have to be integrated cooperatively. Accordingly, a suggestion on the integration is presented in this paper. This proposed paper describes the design and implementation of big data platform for intelligence industrial internet of things sensor monitoring system and conveys a prediction of any upcoming errors beforehand. The architecture design is based on edge computing and artificial intelligence. To extend more precisely, industrial internet of things sensor here is about the condition monitoring sensor data — vibration, temperature, related humidity, and barometric pressure inside facility manufacturing factory.
基于边缘计算和人工智能的智能工业物联网传感器监控系统大数据平台
工业4.0的前沿推动一切都转变为颠覆性创新和数字化。这场数字革命以现代先进技术为印记,利用大数据和人工智能(AI)培育从自动学习系统、智慧城市、智慧能源、智能工厂到边缘计算技术等。大数据、人工智能、物联网、边缘计算等现代工业科学技术必须协同融合,才能引领智能制造产业发展,引领智能制造产业发展。在此基础上,提出了整合的建议。本文描述了智能工业物联网传感器监控系统大数据平台的设计与实现,并对可能出现的错误进行了预先预测。架构设计基于边缘计算和人工智能。更准确地说,这里的工业物联网传感器是关于设备制造工厂内部的状态监测传感器数据-振动,温度,相关湿度和气压。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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