Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory

Abstract

Industrial IoT data analysis is an essential means of obtaining important information in efficient smart factory operation. IoT devices connected to Smart Factory produce large amount of data from variety of mechanical facilities that actually operate. Because the collected data can be analyzed in real time, optimizing plant operations can be optimized, predicting maintenance schedules for mechanical facilities or quickly replacing equipment with faulty ones. In addition, various information needed for efficient operation can be obtained, such as improving the quality of the products produced. Using 5G wireless network and fog node and cloud computing, this paper introduces a new platform that supports efficient analysis of big data collected in smart factories. Leveraging various resources of 5G wireless network, it provides an optimized environment for collecting IoT data such as size, speed, delay and variety. It also provides big data analytic services through fog nodes and cloud computing and addresses various requirements for data collection, processing, analysis and management. This paper describes the requirements and design components of the proposed platform. Introduce case studies using data sets obtained from smart factories to validate the platform and provide meaningful results. The experimental results clearly show the benefits and practicalities of the platform.