scholarly journals How to Prepare Students for the 4th Industrial Revolution Society

2020 ◽  
Vol 7 ◽  
pp. 17-27
Author(s):  
Eunjoo Oh
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Augmented Reality ◽  
Internet Of Things ◽  
Mobile Devices ◽  
Curriculum Design ◽  
Industrial Revolution ◽  
Survey Method ◽  
Knowledge And Skills ◽  
Research Goal

This paper aims to examine how universities prepare students for meeting the job needs in the 4th industrial revolution society and suggest a curriculum to meet the students’ needs. In order to achieve the research goal, a survey method was used. According to Wikipedia, the 4th industrial revolution consists of various technological components such as mobile devices, Internet of things Platforms, big data, and augmented reality. This study attempted to determine whether the university’s curriculum is designed to prepare students for obtaining the knowledge and skills necessary in society. It also examined how students perceive their abilities to handle technologies and get jobs in the changing society. Based on the data analysis, suggestions were made to adjust a curriculum design for future changes.

scholarly journals A monitoring method of semiconductor manufacturing processes using Internet of Things–based big data analysis

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772181 ◽  
Author(s):  
Seok-Woo Jang ◽  
Gye-Young Kim
Keyword(s):  
Time Series ◽  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Real Time ◽  
Semiconductor Manufacturing ◽  
Reference Model ◽  
Big Data Analysis ◽  
Monitoring Method ◽  
Manufacturing Equipment

This article proposes an intelligent monitoring system for semiconductor manufacturing equipment, which determines spec-in or spec-out for a wafer in process, using Internet of Things–based big data analysis. The proposed system consists of three phases: initialization, learning, and prediction in real time. The initialization sets the weights and the effective steps for all parameters of equipment to be monitored. The learning performs a clustering to assign similar patterns to the same class. The patterns consist of a multiple time-series produced by semiconductor manufacturing equipment and an after clean inspection measured by the corresponding tester. We modify the Line, Buzo, and Gray algorithm for classifying the time-series patterns. The modified Line, Buzo, and Gray algorithm outputs a reference model for every cluster. The prediction compares a time-series entered in real time with the reference model using statistical dynamic time warping to find the best matched pattern and then calculates a predicted after clean inspection by combining the measured after clean inspection, the dissimilarity, and the weights. Finally, it determines spec-in or spec-out for the wafer. We will present experimental results that show how the proposed system is applied on the data acquired from semiconductor etching equipment.

Records Management in the Fourth Industrial Revolution

2021 ◽  
pp. 1-24
Author(s):  
Adeyinka Tella ◽  
Oluwakemi Titilola Olaniyi ◽  
Aderinola Ololade Dunmade
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Industrial Revolution ◽  
Records Management ◽  
Technological Advancement ◽  
Fourth Industrial Revolution ◽  
Industrial Revolutions ◽  
The Way

The chapter looked at records management in the fourth industrial revolution (4IR) with the challenges and the way forward. The chapter discussed the industrial revolutions, records management, and the fourth industrial revolution (4IR), and described the advancement in records management in the 4IR based on the 4IR tools and technologies including artificial intelligence, blockchain, internet of things (IoT), robotics, and big data. The chapter also identified and discussed the benefits of technological advancement in the management of records; challenges of records management at the wake of 4IR and charted the way forward. In the context of document and records management, and taking into account all characteristics of the 4IR technologies and tools as well as its underlying technologies and concepts, the chapter concluded that the 4IR tools can be used to save time to create and process records, secure records from being damaged or destroyed, confirm the integrity of records, among others.

Price Versus Performance of Big Data Analysis for Cloud Based Internet of Things Networks

2018 ◽  
Vol 24 (3) ◽  
pp. 1078-1094 ◽  
Author(s):  
Khalim Amjad Meerja ◽  
Praveen V. Naidu ◽  
Sri Rama Krishna Kalva
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Big Data Analysis

The Role of Visual Assessment of Clusters for Big Data Analysis: From Real-World Internet of Things

2020 ◽  
Vol 6 (4) ◽  
pp. 45-53
Author(s):  
Marimuthu Palaniswami ◽  
Aravinda S. Rao ◽  
Dheeraj Kumar ◽  
Punit Rathore ◽  
Sutharshan Rajasegarar
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Real World ◽  
Visual Assessment ◽  
Big Data Analysis

scholarly journals IoT-Fog-Cloud system architecture for big data analysis and cybersecurity systems: a review of fog computing, the introduction to the Internet of Things audit

2020 ◽  
Author(s):  
D. R. Kolisnyk ◽  
◽  
K. S. Misevych ◽  
S. V. Kovalenko
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
System Architecture ◽  
Fog Computing ◽  
Big Data Analysis ◽  
Future Research ◽  
The Internet ◽  
Security Issues ◽  
The Internet Of Things

The article considers the issues of system architecture IoT-Fog-Cloud, considers the interaction between the three levels of IoT, Fog and Cloud for the effective implementation of programs for big data analysis and cybersecurity. The article also discusses security issues, solutions and directions for future research in the field of the Internet of Things and nebulous computing.

scholarly journals Namur Open Architecture

atp magazin ◽  
2017 ◽  
Vol 59 (01-02) ◽  
pp. 17 ◽  
Author(s):  
Christian Klettner ◽  
Thomas Tauchnitz ◽  
Ulrich Epple ◽  
Lars Nothdurft ◽  
Christian Diedrich ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Mobile Devices ◽  
Industrie 4.0 ◽  
Open Architecture ◽  
Neue Technologien

Die durch die klassische Namur-Pyramide beschriebene Automatisierungsstruktur ist bewährt und ermöglicht langjährige Betriebssicherheit. Allerdings fehlt den Systemen die Offenheit, neue Technologien werden erst spät verwendet und die Kosten sind hoch, was angesichts der rasanten Entwicklungen im Bereich von Internet of Things, Industrie 4.0, Mobile Devices und Big Data nutzvolle Innovationen verhindert. In diesem Beitrag wird das im Namur-Arbeitskreis 2.8 Automatisierungsnetzwerke und -dienste entwickelte Konzept Namur Open Architecture (NOA) vorgestellt. Das Konzept bietet sowohl für Bestands- als auch für Neuanlagen Möglichkeiten, um Anlagen effizient für kommende Innovationen zu ertüchtigen. Die Kernidee ist, die Daten der bisherigen Kern-Automatisierungswelt durch offene Schnittstellen wie beispielsweise OPC UA in die Systemwelt für Monitoring- und Optimierungsaufgaben zu exportieren und dabei die Kernautomatisierung weitgehend unverändert zu belassen. Alternativ kann über einen zweiten Kommunikationskanal direkt auf die bestehenden Feldgeräte zugegriffen werden.

scholarly journals Big Data, Internet of Things, Augmented Reality: technology convergence in visualization issues

2019 ◽  
pp. 432-444
Author(s):  
D A Smuseva ◽  
A Y Rolich ◽  
L S Voskov ◽  
I Y Malakhov
Keyword(s):  
Big Data ◽  
Augmented Reality ◽  
Internet Of Things ◽  
Data Visualization ◽  
Data Transfer ◽  
Base Station ◽  
Time Data ◽  
Experimental Stand ◽  
Big Data Visualization ◽  
Standby Mode

The paper reviews the current situation of the Augmented Reality and Internet of Things markets. The implementing possibilities of AR for Big Data visualization from IoT devices are considered in this paper. The review and the analysis of methods, tools, products and data system of the visualization are presented. The paper provides an overview of the programs and devices of Augmented Reality, and an overview of development environments. The paper presents the existing classifications of computerized data visualization tools and proposes new classification, which takes into account interactive visualization, the purpose of the tool, the type of software product, the availability of ready-made templates, and other characteristics. The article proposes the architecture of the system for collecting data from IoT endpoint devices based on the Heltec modules. Experiments based on the developed experimental stand were carried out with Heltec devices of both versions to determine the number of losses with increasing distance between the sending device and the receiving device. The results of measuring the power consumption of these devices are presented in two modes: in standby mode and when sending a message to the Heltec endpoint device and in standby mode and when receiving a message for the base station. These studies were conducted using various data transfer protocols (LoRa, Wi-Fi and Bluetooth). The paper presents the result of the development of a digital twin of a university building and the development of augmented reality software for receiving data from real-time data collection devices.

scholarly journals Information Security Terminal Architecture of Power Transportation Mobile Internet of Things Based on Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xianzhi Tang ◽  
Chunyan Ding
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Information Security ◽  
Internet Of Things ◽  
Power System ◽  
Big Data Analysis ◽  
The Internet ◽  
Mobile Information ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The progress of the social economy and the rapid development of the power field have created more favorable conditions for the construction of my country’s power grid. In this network age, how to further realize the connection between the power system and the Internet of Things is the key content of many scholars’ research. In the Internet of Things environment, there have been many excellent results in the collection, storage, and management of electric power big data, but the problem of information security has not been completely solved. Based on big data analysis and Internet of Things technology, this paper studies the architecture design of power information security terminals. In view of the diverse types of power grid mobile information and the large amount of data, this paper designs a power transportation mobile information security management system structure, which improves the effective management of power data by the system through big data, smart sensors, and wireless communication technology. According to the experiment, the power information security terminal constructed in this paper can effectively reduce communication resources and save communication costs in the process of aggregating multidimensional data. In the user satisfaction survey, residents’ satisfaction with the convenience and safety of the intelligent power system is also as high as 9.312 and 9.233. On the whole, the application of big data and Internet of Things technology to the construction of power information security terminals can indeed improve the service efficiency of power companies under the premise of ensuring safety and allow users to have a better experience.

Augmented Reality in the Context of Automotive Manufacturing

2020 ◽  
pp. 95-110
Author(s):  
Gisela Pires Garcia
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Large Scale ◽  
Industrial Revolution ◽  
Shop Floor ◽  
New Work ◽  
Automotive Manufacturing ◽  
Digital World

The 4th industrial revolution based on the digitization of industrial processes, on the connection of the equipment between them, and on new interfaces with the humans, will require new work contexts and new organizations (Cyber-Physical System and Internet of Things). Virtual Reality (VR) and Augmented Reality (AR) will contribute in a large scale for the automotive industry transition to the Industry 4.0 paradigm. This chapter provides an overview of these versatile technologies in the context of industrial production, where these technologies will allow the real world of the shop floor to merge with a digital world of simulations, predictions, and automation.

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