Knowledge Management and Industry Revolution 4.0 E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Get up to speed with how the latest knowledge management and industry 4.0 technologyhelp make enterprises secure, controlled, and optimized for a better future.
This book focuses on how the practices of Industrial Revolution 4.0 and knowledge management interact to create value. In recent years, value chain relationships and related activities have utilized new technologies so that existing conceptual frameworks require a roadmap for innovation strategies and effective implementation. The chapters in this book include case studies contributed by researchers and industry practitioners that showcase the impact of practices and challenges presented by technological changes, upgrading of old systems, and internal and external factors.
Knowledge Management and Industrial Revolution 4.0 describes how knowledge management impacts the automation of the industry in secure, controlled, and optimized ways. For instance, the use of the latest technologies and sensors can lead to significant time and cost savings, and operators can utilize their machines and equipment from remote locations. The Industrial Revolution 4.0 incorporates the latest technologies for automation and, in many cases, the result is similar to working from home, even in manufacturing.
The use of deep learning should offer many quality control benefits. Furthermore, blockchain technology can help the industry with automation in secure and transparent ways. Apart from industry automation, other departments like human resources can also use effective knowledge management for better outcomes. The use of HR knowledge management allows employees to find and access the information they require without the assistance of the HR department.
The book focuses on every aspect of the industry to help all the stakeholders of an organization. The benefits include a reduction in time required for accessing information, easier training, decreased operational expenses, improved stakeholders’ satisfaction, faster problem-solving, increased pace of innovation, simpler employee review and progress reports.
Audience
The book will have a wide audience within academia, education, businesses, and industrial organizations, especially those who are undergoing industry 4.0 changes to optimize for a better future.
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Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
Preface
Acknowledgement
1 The 5G Technology IR4 and Knowledge Management
1.1 Introduction
1.2 5G Technology Architecture
1.3 Technology Features of 5G
1.4 Applications of 5G Technology in Industry 4.0 (4IR)
1.5 Knowledge Management in Industry 4.0
1.6 The Role of 5G Technology in Knowledge Management
1.7 Challenges of Implementing 5G Technology for Knowledge Management
1.8 Future Trends and Developments in 5G Technology and Knowledge Management
References
2 Impact of Knowledge Management on Industry 4.0
2.1 Introduction
2.2 State of Art
2.3 Models of Knowledge Management
2.4 Proposed Model for Industry 4.0
2.5 Conclusion
References
3 Synergizing Knowledge Management in the Era of Industry 4.0: A Technological Revolution for Organizational Excellence
3.1 Introduction
3.2 Historical Perspective
3.3 Knowledge Management in the Fourth Industrial Revolution (Industry 4.0)
3.4 The Intersection of Knowledge and Technology
3.5 Knowledge Creation and Capture
3.6 Facilitating Knowledge Sharing and Dissemination
3.7 Knowledge Transfer and Training Initiative
3.8 Strategic Knowledge Management for Fostering Innovation
3.9 Common Challenges in Managing Knowledge During Industrial Revolutions
3.10 Conclusion
References
4 Improving Manufacturing: Organizational Innovation Through Effective Knowledge Management, A McElroy Knowledge Life Cycle Approach
4.1 Introduction
4.2 Unleashing the Innovation Possibilities: The Effectiveness of Knowledge Creation in Manufacturing Organizations
4.3 Leveraging Manufacturing Industries’ Potential Through Efficient Knowledge Capture
4.4 Knowledge Sharing as a Tool for Innovation in Manufacturing Organization
4.5 From Theories to Action: The Impact of Knowledge Application in Manufacturing Industries
4.6 Knowledge Management Practices in Global Manufacturing Organizations: Boosting Innovation and Performance
4.7 Conclusion
References
5 Industry 4.0 Trends and Strategies: A Modern Approach with Focus on Knowledge Management
5.1 Introduction
5.2 Understanding Industry 4.0
5.3 Literature Review
5.4 Emerging Trends in Industry 4.0
5.5 Knowledge Management in Industry 4.0
5.6 Leveraging Knowledge Management for Successful Industry 4.0 Implementation
5.7 Case Studies: Industry 4.0 Implementation with Knowledge Management
5.8 Future Directions and Challenges
5.9 Conclusion
References
6 Artificial Intelligence on Knowledge Management and Industry Revolution 4.0: Impacts and Challenges
6.1 Introduction
6.2 Background of the Study
6.3 Industry 4.0 Revolution
6.4 Technology is Driving Industry 4.0
6.5 Role of AI in KM and IR 4.0
6.6 The Effects of AI on IR 4.0 and KM
6.7 Key Challenges of AI in KM and IR 4.0
6.8 Limitation of the IR 4.0 and KM
6.9 Future Direction
6.10 Research Challenges
6.11 Conclusion
References
7 Blending of Knowledge Management with Industry 4.0: A New Formula for Success!
7.1 Introduction
7.2 History of Industry 4.0
7.3 Objectives of the Chapter
7.4 Conclusion
References
8 Modern Approaches and Implications Toward Industry 4.0
8.1 Introduction
8.2 Literature Review
8.3 Modern Methodologies Supporting Industry 4.0
8.4 Implications of Adopting Industry 4.0 Practices
8.5 Cross-Sector Collaboration
8.6 Strategies for Successful Adoption
8.7 Future Prospects and Research Directions
8.8 Conclusion
References
9 Managing Knowledge in the Era of Industry 4.0: Challenges and Strategies
9.1 Introduction
9.2 Literature Review
9.3 Impacts of Industry 4.0
9.4 Importance of Knowledge Management in the Context of Industry 4.0
9.5 Knowledge Management
9.6 Overview of Industry 4.0 and Technologies
9.7 Implications of Industry 4.0 for Knowledge Management
9.8 Role of Artificial Intelligence, Big Data, and IoT in Knowledge Management
9.9 Challenges of Knowledge Management in Industry 4.0
9.10 Strategies for Effective Knowledge Management
9.11 Best Practices for Knowledge Management in Industry 4.0
9.12 Strategies for Leveraging Technology for Effective Knowledge Management
9.13 Case Studies of Successful Knowledge Management in Industry 4.0
9.14 Result
9.15 Discussion
9.16 Conclusion
9.17 Future Directions
References
10 Enhance Knowledge Management in Industry 4.0
10.1 Introduction
10.2 Background
10.3 Literature Survey
10.4 Previous Study
10.5 Case Study
10.6 Analysis of the Work
10.7 Challenges of Data Analytics
10.8 Future Scope
10.9 Conclusion
References
11 Industrialized Control and Automation System (ICAS): A Software-Defined Analysis Framework for Industry 4.0
11.1 Introduction
11.2 Related Works
11.3 Healthcare Applications in Industries
11.4 Inventory Management and Quality Control
11.5 Analysis of a Machine Learning Algorithm to Predict Wine Quality
11.6 Conclusion and Future Directions
References
12 Structural Understanding of the Relationship Between Various Consciousness of Programming and Creative Attitudes as Part of Knowledge Management Process
12.1 Introduction
12.2 Method
12.3 Analysis Procedure
12.4 Results
12.5 Discussion
12.6 Conclusion
Acknowledgments
Note
References
13 Blended-Mode Instruction for Knowledge Management Toward IR4.0: Exemplars in Lifelong STREAM Education and The Way Forward
13.1 Introduction
13.2 Analysis of Findings and Illustrations of Case Exemplars
13.3 Conclusion
Acknowledgments
References
14 Insight Review on Advanced Digital Manufacturing Technology Solutions for Industry 4.0
14.1 Introduction
14.2 Digitization of Manufacturing Sectors
14.3 Knowledge Management Practices Adopted in Manufacturing
14.4 Challenges in Digitization of Industry 4.0
14.5 Key Factors in Addressing Obstacles and Hindrances
14.6 Conclusion
References
15 Enhancing Students’ Learning Achievement, 21st-Century Skills, and Self-Regulation Skills— Knowledge Management and Education 4.0 Perspective
15.1 Introduction
15.2 Literature Review
15.3 Methodology
15.4 Participants
15.5 Research Instruments
15.6 Data Collection
15.7 Data Analysis
15.8 Results and Discussion
15.9 Conclusion
References
Index
End User License Agreement
List of Tables
Chapter 8
Table 8.1 Evolutionary milestones of Industry 4.0.
Table 8.2 Comparison of studies on modern approaches.
Table 8.3 Research areas in Industry 4.0 that demand attention.
Table 8.4 Applications and benefits of cyber-physical systems in various indus...
Table 8.5 Primary components of industrial Internet of Things and their specif...
Table 8.6 The role of advanced analytics in enhancing Industry 4.0 outcomes.
Table 8.7 Skill transformation in Industry 4.0.
Table 8.8 Comparative cost-benefit analysis of Industry 4.0 transition.
Table 8.9 Case studies on Industry 4.0 adoption.
Chapter 9
Table 9.1 Literature review with research gap.
Table 9.2 Summary of key results.
Chapter 10
Table 10.1 Algorithm to arrange the dataset.
Chapter 11
Table 11.1 Industrial revolutions.
Table 11.2 New topics and findings from related studies in each subset of ICAS...
Chapter 12
Table 12.1 Measurement items of consciousness for programming.
Table 12.2 Validity and reliability of each factor of creative attitude scale....
Table 12.3 Descriptive statistics for creative attitudes and the various consc...
Chapter 15
Table 15.1 ANCOVA results on FRR and HCP posttest scores.
Table 15.2 ANCOVA results on 21st CS and SRS posttest scores.
List of Illustrations
Chapter 1
Figure 1.1 5G architecture.
Chapter 2
Figure 2.1 Von Krogh and Roos model.
Figure 2.2 Nonaka and Takeuchi model.
Figure 2.3 Choo sense-making KM model.
Figure 2.4 WIIGs KM model.
Figure 2.5 Social Learning Cycle (SLC) based on Boisot I-Space.
Figure 2.6 Zack model of knowledge management.
Figure 2.7 Complex adaptive system model.
Figure 2.8 4A—Intelligent complex sdaptive system model (source: authors).
Chapter 3
Figure 3.1 Progress of innovations during the Industrial Revolution.
Figure 3.2 Characteristics of Industry 4.0.
Figure 3.3 Key aspects of Industry 4.0.
Figure 3.4 Technologies in Industry 4.0.
Figure 3.5 Strategies for industrial knowledge management.
Figure 3.6 Role of R&D in knowledge creation.
Chapter 4
Figure 4.1 KM techniques used to capture knowledge. Source — Author’s own comp...
Figure 4.2 Knowledge management practices adopted by global manufacturing orga...
Chapter 5
Figure 5.1 The transformative paradigm of Industry-4.
Figure 5.2 The Industry 4.0 background.
Figure 5.3 Evolution of Industry 4.
Figure 5.4 Fundamental concepts of Industry 4.0.
Figure 5.5 Technologies converge to drive innovation, efficiency, and competit...
Figure 5.6 Cyber-physical systems (CPS) architecture.
Figure 5.7 Strategies to equip employees with the skills needed to thrive in t...
Figure 5.8 Framework of Industry-4.
Figure 5.9 Societal and environmental implications in Industry 4.0.
Chapter 6
Figure 6.1 Industry revolution 4.0.
Figure 6.2 Technologies are driving Industry 4.0.
Chapter 7
Figure 7.1 Industry 4.0 (source: Industry 4.0 (dg1.com)).
Chapter 8
Figure 8.1 Core elements of Industry 4.0.
Figure 8.2 Timeline and progression of the industrial revolutions.
Figure 8.3 Schematic representation of a cyber-physical system integration.
Figure 8.4 Commercial and industrial applications of CPS.
Figure 8.5 IIoT system architecture and components.
Figure 8.6 Strategies and challenges in cybersecurity for Industry 4.0.
Chapter 9
Figure 9.1 Importance of knowledge management in the context of Industry 4.0....
Chapter 10
Figure 10.1 Representation of dataset (an instance).
Figure 10.2 Representation of dataset (an instance).
Figure 10.3 Comparison of association between clusters.
Chapter 11
Figure 11.1 Internet of Things.
Figure 11.2 Technologies that support i4.0.
Figure 11.3 The Internet of Things enables smart circumstances.
Figure 11.4 IoT development key business driver.
Figure 11.5 IoT connecting technologies.
Figure 11.6 Industrial Internet.
Figure 11.7 Data flow diagram for an IIoT-enabled healthcare system.
Figure 11.8 Smart devices for checking the health conditions of patients.
Figure 11.9 Schematic view of inventory management.
Figure 11.10 Benefits of IIoT applications in inventory management.
Figure 11.11 Benefits of IIoT applications in inventory management.
Figure 11.12 System model for WQA.
Chapter 12
Figure 12.1 Results of covariance structural analysis between creative attitud...
Chapter 13
Figure 13.1 Telegram and Google Meet as SNPs for most of the KM process especi...
Figure 13.2 Team web meeting platform during KM process especially for AoK dur...
Figure 13.3 Blended shop with on-site and online created by ethnic girls and w...
Figure 13.4 Training of Trainers’ (ToT) to facilitate Distribution of Knowledg...
Figure 13.5 www.ccdkm.org through BMI to facilitate Use of Knowledge (UoK).
Figure 13.6 E-brochure of one of Thailand’s events to promote literacy through...
Figure 13.7 On-site training workshop at a glance with projector showing imple...
Figure 13.8 On-site training workshop facilitated by the first author.
Figure 13.9 E-brochure of webinar to promote smart silver economy through loca...
Figure 13.10 Workshop participants and one of the targeted outputs to promote ...
Figure 13.11 Workshop participants and some of their outputs to promote silver...
Figure 13.12 Presentation slide extracted from “Local Wisdom Cowongan in Banyu...
Chapter 14
Figure 14.1 Knowledge management practices.
Figure 14.2 Various levels in knowledge management—Data collection to data app...
Chapter 15
Figure 15.1 Creative education.
Figure 15.2 Data–information–knowledge–wisdom hierarchy in terms of knowledge ...
Guide
Cover Page
Table of Contents
Series Page
Title Page
Copyright Page
Preface
Acknowledgement
Begin Reading
Index
WILEY END USER LICENSE AGREEMENT
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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106
Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])
Knowledge Management and Industry Revolution 4.0
Edited by
Rajendra Kumar
Dept. of Computer Science & Engineering, Sharda University, Greater Noida, India
Vishal Jain
Dept. of Computer Science & Engineering, Sharda University, Greater Noida, India
Venus C. Ibarra
San Pablo Colleges, Laguna, Philippines
Corrienna Abdul Talib
Dept. of Educational Science, Mathematics and Creative Multimedia, Universiti Teknologi Malaysia
and
Vinay Kukreja
Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
This edition first published 2024 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2024 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-394-24261-0
Cover image: Pixabay.ComCover design by Russell Richardson
Preface
This book focuses on how the practices of Industrial Revolution 4.0 and knowledge management interact to create value. This volume mainly discusses the impact and challenges of knowledge management in the Fourth Industrial Revolution. In recent years, the value chain relationships and related activities have taken advantage of new technologies, but a new era is beginning and the existing conceptual frameworks require a roadmap for innovation strategies and effective implementation. The material collected herein includes case studies contributed from researchers and industry practitioners that showcase the impact of practices and challenges presented by technological changes, upgradation of old systems, and internal and external factors.
Knowledge Management and Industrial Revolution 4.0: Impacts and Challenges describes how knowledge management impacts the automation of the industry in secure, controlled, and optimized ways. For instance, the use of the latest technologies and sensors can lead to significant time and cost savings, and operators can utilize their machines and equipment from remote locations. The Industrial Revolution 4.0 incorporates the latest technologies for automation and, in many cases, the result is similar to working from home, even in manufacturing.
The use of deep learning should offer many quality control benefits. Furthermore, blockchain technology can help the industry with automation in secure and transparent ways. Apart from industry automation, other departments like human resources can also use effective knowledge management for better outcomes. The use of HR knowledge management allows employees to find and access the information they require without the assistance of the HR department. However, proper management is required to make all information accessible to every employee, otherwise they can become exhausted or access information not fruitful to them.
The book focuses on every aspect of the industry to help all the stakeholders of an organization. The benefits include a reduction in time required for accessing information, easier training, decreased operational expenses, improved stakeholders’ satisfaction, faster problem-solving, increased pace of innovation, simpler employee review and progress reports, etc.
Chapter 1 discusses the integration of IoT (Internet of Things) into manufacturing processes. It also introduces new challenges, including cyber-security vulnerabilities and the necessity for upskilling labor forces.
Chapter 2 proposes an intelligent complex adaptive system named 4A, which insists on Agent, Algorithm, Architecture, and Adaptation. The proposed model aims to offer a more adaptable and flexible approach to KM in the context of I4.0.
Chapter 3 discusses the synergizing of knowledge management in the era of Industry 4.0.
Chapter 4 gives an overview of how knowledge production (knowledge creation, capture, sharing, and application) helps manufacturing organizations acquire new information, discuss best practices, successfully use knowledge, and incorporate new knowledge to promote innovation.
Chapter 5 sheds light on the significance of cyber security measures in safeguarding sensitive data and maintaining the integrity of interconnected systems. This comprehensive review highlights the transformative potential of Industry 4.0 and the pivotal part of knowledge management in its successful implementation.
Chapter 6 discusses the use of artificial intelligence in knowledge management and the Industrial Revolution 4.0.
Chapter 7 presents a transformative opportunity for organizations seeking enhanced efficiency and sustainable growth through the convergence of Industry 4.0 and knowledge management.
Chapter 8 provides various insights on the requirements for advanced development and dynamic change in the industrial sector.
Chapter 9 serves as a comprehensive guide for organizations seeking to harness the potential of Industry 4.0 while adeptly managing their knowledge assets.
Chapter 10 discusses the use of IoT and data analytics to enhance knowledge management in Industry 4.0.
Chapter 11 presents a study of the software-defined analysis framework for Industry 4.0, and specifically for Industrialized Control and Automation Systems (ICAS).
Chapter 12 includes the results of a survey aimed at understanding the structural relationship between interest in programming and creative attitudes among Japanese high school students as part of the knowledge management process in preparation for the Industrial Revolution 4.0.
Chapter 13 examines the concepts and roles of Blended-Mode Instruction (BMI) as an emerging knowledge management platform during the Industrial Revolution 4.0. It aims to promote Science, Technology, Reading, Engineering, Arts, and Mathematics (STREAM) education in three Southeast-Asian countries and China.
Chapter 14 gives an insightful review of advanced digital manufacturing technology solutions for Industry 4.0.
Chapter 15 presents a study for enhancing students’ learning achievement, 21st-century skills, and self-regulation skills with a knowledge management and Industry 4.0 perspective.
Editors
Rajendra Kumar
Vishal Jain
Venus C. Ibarra
Corrienna Abdul Talib
Vinay Kukreja
Acknowledgement
This book is a collective effort not only by the contributors but also the publisher and its staff, reviewers, and critics. The editors are grateful to Mr. Martin Scrivener for accepting the book proposal and publishing the book within the stipulated time. Many thanks to the editorial and production team of Scrivener publishing.
Editors are thankful to the contributors of the book and all the editors who reviewed the contents with full enthusiasm.
Editors are very much thankful to Sharda University (India), San Pablo Colleges (Philippines), Universiti Teknologi Malaysia (Malaysia), and Chikara University (India) for providing necessary support and resources.
Last, but not the least, the editors are thankful to their colleagues and families for their kind cooperation and direct/indirect support.
Editors
Rajendra Kumar
Vishal Jain
Venus C. Ibarra
Corrienna Abdul Talib
Vinay Kukreja
1The 5G Technology IR4 and Knowledge Management
Vyshali Rao K. P.1*, Shanthi M. B.2 and Sudhakar K. N.3
1Department of ISE, CMR Institute of Technology, Bangalore, India
2Department of CSE, CMR Institute of Technology, Bangalore, India
3SoCSE, RV University, Bangalore, India
Abstract
Often termed as Industry IR-4.0, the fourth revolution industry encompasses the merging of high-end technologies, with a distinct emphasis on the Internet of Things (IoT), within the manufacturing domain, leading to the transformation of the industrial landscape into a heightened state of intelligence. The IoT concept encompasses the interlinking of hardware devices, vehicles, and various objects embedded with sensors and connectivity software, facilitating processes like data collection, organization, and exchange. The swift growth of IoT in the present years has led to an upsurge in Internet-connected devices spurring the need for faster and more dependable networks to accommodate this expansion. The emergence of 5G networks offers a potential solution delivering enhanced speeds, reduced delay, and increased capacity compared to previous generations. These 5G networks are well positioned to support a wide variety of IoT devices, including sensors, wearable, smart cities, autonomous vehicles, and industrial factories. Thanks to its increased bandwidth and decreased latency, 5G facilitates real-time communication between devices enabling more efficient data transfers. This capability finds particular relevance in applications, such as industrial automation, where seamless real-time communication between machines enhances production processes. Notably, 5G networks for IoT offer support for extensive machinetype communications (mMTC), and they feature slicing of network, allowing network operators to develop virtual networks optimized for specific industrial IoT applications. However, while the integration of IoT into manufacturing processes brings about advantages, it also introduces new challenges, including cybersecurity vulnerabilities and the necessity for up-skilling labor forces.
Keywords: Radio access networks (RANs), service-aligned architecture (SAA), long term evolution (LTE), industrial revolution (IR)
1.1 Introduction
The Fourth Industrial Revolution (4IR) is the upcoming level in computerizing the mass production industry. It is fueled by ingenious developments like growth of size of data and their connectivity, analytics, machine– human interaction, and elevation in robotics. The industrial revolution 4.0, commonly known as Industry 4.0, is exemplified by the integration of advanced technologies to create smart, connected, and highly automated systems [1]. One of the key enablers of Industry 4.0 is the deployment of 5G technology, which represents the 5G mobile networks. 5G is poised to revolutionize various industries by providing unprecedented levels of speed, reliability, and connectivity. In this introduction, we will explore the necessary aspects of 5G technology and its role in powering Industry 4.0.
The 5G technology is the latest improvisation in cellular communication networks succeeding the previous generation, 4G/LTE [2]. It is designed to deliver significantly faster data speeds, lower delays (the time taken by data to travel among devices), and enhanced network capacity. 5G operates on greater frequency bands and millimeter waves, enabling it to handle more significant data volumes with minimal delays. While 5G holds immense promise for Industry 4.0, its widespread implementation faces some challenges. These include the need for significant infrastructure upgrades, ensuring network security and privacy, and addressing potential grievance regarding health effects of larger frequency radio waves [3]. The 5G technology is a critical enabler of Industry 4.0 revolutionizing various sectors by providing faster and more reliable connectivity. Its implementation has the future to transform industries, boost innovation, and expose new business models that leverage the power of smart, connected systems. As 5G networks continue to expand, we can foresee a proliferation of cutting-edge technologies that will reshape our way of living, work, and having an interaction with digital age.
1.2 5G Technology Architecture
Cellular networking has evolved across successive generations with the imminent fifth generation being the latest advancement. The primary objective of preceding iterations was to provide rapid and dependable mobile services to users. However, 5G significantly broadens this objective introducing an extensive array of wireless services available to users across diverse platforms and multi-layered networks. This new generation, 5G establishes a cohesive, dynamic, and adaptable framework comprised of forward-looking technologies capable of accommodating a wide range of applications. Employing a more advanced architecture, 5G’s Radio Access Networks (RANs) are not objectified by the proximity of base stations or intricate infrastructure. Instead, 5G paves the way for a flexible, disaggregated, and virtual RAN augmented by interfaces that create additional data access points.
The 5G basic network infrastructure is crucial for supporting the increased throughput demand of 5G [4]. It follows a cloud-oriented, service-aligned architecture (SAA) defined by 3GPP. This architecture encompasses various 5G functionalities, including security, authentication, session management, and data traffic accumulation from the user end. The 3rd Generation Partnership Project (3GPP) encompasses telecommunication technologies such as RAN, core transport networks, and service capabilities [5]. It has defined comprehensive system requirements for the 5G network infrastructure, which is characterized as service-oriented compared to previous generations. These services are made available via a familiar framework to networking accessibility that are available for usage. Reusability, modularity, and self-circumscription of these 5G network functionalities are added design considerations for the 5G network infrastructure described by the 3GPP specifications.
The architecture of 5G networks is designed to support faster and more reliable wireless communication. It consists of three major components, the radio access network (RAN), the root network, and user equipment (UE). The RAN includes base stations and antennas that connect devices at the end to a network. The basic network manages the flow of data and provides services like authentication and security. The UE refers to the devices used by users to access the network, such as smartphones or IoT devices [6]. Overall, the architecture of 5G networks aims to provide enhanced connectivity and enables new applications and services. The Figure 1.1 depicts the core architecture of 5G networks per 3GPP specifications.
User equipment (UE), such as smartphones or mobile devices that utilize 5G technology, establishes connections through the 5G New Radio Access Network to the 5G core and subsequently to Data Networks (DN), including the Internet.
Access and Mobility Management Function (AMF)
[7]
: The AMF serves as the indigenous point of entry for UE connections. It performs tasks such as non-access stratum (NAS) signal termination, NAS encoding and protection of integrity, management of registration, connection, mobility, access authorization and authentication, and security factor management. Depending on the requested service by the UE, the AMF selects the relevant Session Management Function (SMF) to oversee the user session. Additionally, the AMF incorporates the Network Slice Selection Function (NSSF) and serves as the termination point for RAN control plane (CP) interfaces (N2).
Figure 1.1 5G architecture.
5G Network Exposure Function (NEF)
[8]
: The NEF ensures secure and robust access to the network services and capabilities exposed by your 5G network. It provides developers and enterprises with the means to create tailored network services on-demand fostering innovation within an extended ecosystem.
Network Repository Function (NRF)
[9]
: As a vital component of the 5G core, the NRF functions as an index that aids other network functions (NFs) in discovering information about other entities within the core, along with necessary service capabilities.
Authentication Server Function (AUSF)
[10]
: The AUSF qualifies the AMF to authorize the UE and allow access to the 5G basic services.
User Plane Function (UPF)
[11]
: The UPF supervises transporting IP datagram traffic (user plane) among the UE and other external networks.
Additional Functions: The Session Management Function (SMF)
[12]
, Policy Control Function (PCF), Application Function (AF), and Unified Data Management (UDM) function constitute a framework for policy control. They implement policy decisions, access subscription information, and regulate network behavior.
1.3 Technology Features of 5G
The 5G technology depicts a significant breakthrough in terms of fastness, capacity, latency, and connectivity in comparison to previous generations (such as 4G or LTE). Here are crucial features [13] and characteristics of 5G technicality.
Increased Speed:
The 5G presents notably elevated data transmission speeds compared to its predecessors boasting peak velocities that can attain up to 10 Gbps. This enhancement facilitates swifter downloads, uninterrupted streaming of high-definition media, and instantaneous interactions characterized by minimal latency.
Low Latency:
The 5G technology reduces network latency to as low as 1 millisecond (ms) providing nearly instantaneous communication between devices and minimizing delays. This is a bottle neck for applications like remote surgery, autonomous vehicles, and virtual gaming.
High Capacity:
5G networks can handle a large number of interconnected devices concurrently. The technology utilizes advanced frequency bands, including higher-frequency millimeter waves, to increase network capacity and accommodate the growing number of Internet of Things (IoT) devices.
Enhanced Coverage:
5G networks employ various technologies, including small cells, massive MIMO (Multiple Input Multiple Output), and beam forming, to improve coverage and signal strength. This enables reliable connectivity even in crowded areas and remote locations.
Network Slicing:
With the advent of 5G comes the innovative notion of network slicing, a concept enabling network operators to craft numerous virtual networks within a solitary physical infrastructure. Each distinct network slice offers tailored communication services to cater to diverse needs encompassing aspects like ultra-low latency and ultrahigh speed.
Enhanced Energy Efficiency:
5G technologies aim to be more energy efficient in comparison to older generations. This is achieved through optimized network architecture, reduced power consumption of network equipment, and intelligent network management.
Empowering Emerging Innovations:
Anticipated to play a pivotal role, 5G is poised to facilitate the growth of nascent technologies like autonomous vehicles, augmented reality (AR), virtual reality (VR), smart cities, industrial automation, and remote telemedicine. The swift speeds, minimal latency, and extensive connectivity provided by 5G networks cater to the intricate requirements of these cutting-edge applications.
Security:
Enhancing the security of mobile devices and IoT systems is a perpetual priority due to the positioning of the latter at the periphery of the corporate network. The advent of 5G has brought forth heightened security measures compared to its predecessor, 4G LTE. These enhanced security measures encompass hardware security modules, proficient key management services, reliable over-the-air transmission, and fortified secure elements, among other advancements. These collective measures collectively bolster the integrity of data transmitted across the 5G network and contribute to the reinforcement of network endpoints.
1.4 Applications of 5G Technology in Industry 4.0 (4IR)
Industry 4.0, often termed as the 4th industrial revolution, envisions the digitization of production, manufacturing, and associated sectors. This epoch signifies a novel stage in the organizational structure, control mechanisms, and value generation processes within the industrial value chain. Presently, we find ourselves within the realm of the Fourth Industrial Revolution, marked by the implementation of cyber physical systems and intelligent machinery. This phase incorporates sophisticated control systems integrated with embedded software as well as elements like the Internet of Things (IoT), cloud computing, and cognitive computing. The potential of 5G technology spans across diverse industries encompassing domains from hawk to education, commute to entertainment, and intelligent homes to healthcare. It has the capacity to elevate the significance of mobile technology beyond its present status [14].
The benefits of the Fourth Industrial Revolution include the potential to enhance the accessibility and transmission of products and services for businesses, consumers, and stakeholders across the entire value chain. Initial data suggests that the effective implementation of the 4IR technology can lead to improved efficiency in supply chains and increased productivity during working hours. It also contributes to reduced factory waste and brings numerous advantages to employees, stakeholders, and consumers. The transition from traditional industrial methods to contemporary practices can be categorized into three distinct adoption pathways [15]:
Swift Integration:
Irrespective of a company’s current technological setup, be it advanced or non-existent, certain cost-effective digital, augmented reality, and automation solutions can be swiftly incorporated without undergoing complex transition challenges.
Gradual Progression:
The pace of technology adoption can be influenced by a company’s pre-existing technological infrastructure. Businesses with limited foundational information technology (IT), operational technology, and data infrastructure will require time to make the transition. On the other hand, technologically advanced companies are better positioned to swiftly implement new solutions.
Reduced or Postponed Adoption:
Even within companies boasting sophisticated technological foundations, the adoption of the latest and most cutting-edge innovations (such as comprehensive end-to-end automation) might occur at a slower pace due to the substantial capital expenditure involved and the uncertain long-term returns on investment.
5G networks have a variety of applications [16] across different industries. Some of the key applications have been discussed in the following section.
Next-Generation Mobile Network:
5G is set to redefine the mobile experience by introducing an advanced wireless network that can achieve remarkable data download speeds ranging from 1 to 2 GBPS. This swiftness is akin to accessing an optic fiber connection wirelessly. Notably, 5G outperforms previous mobile transmission technologies allowing for efficient concurrent transfer of both voice and high-speed data. Particularly significant is the low latency inherent to 5G, a vital trait for applications like autonomous driving and mission-critical operations. The latency capability of 5G networks is notably under a millisecond. Employing novel radio millimeter waves for transmission, 5G utilizes a vastly broader bandwidth in comparison to lower LTE bands resulting in significantly higher data rates.
Entertainment and Multimedia:
Research indicates that in 2015, video downloads accounted for 55% of global mobile Internet traffic. This trend is projected to intensify driving the widespread embrace of high-definition video streaming. The 5G technology promises to introduce a high-definition virtual realm accessible on mobile devices. Rapid 4K video streaming now demands only a matter of seconds, complemented by crystal-clear audio quality. Wireless networks can effortlessly broadcast live events in high definition, while mobile devices grant access to HD TV channels without interruption. The entertainment sector is poised to reap substantial benefits from the deployment of 5G wireless networks. With the capability to offer 12 frames per second, high-resolution content, and elevated dynamic range video streaming devoid of interruptions, 5G revolutionizes the audiovisual experience. The integration of 5G’s advanced technologies paves the way for augmented reality and virtual reality applications demanding HD video with minimal latency. 5G’s robust capabilities aptly power these immersive experiences enhancing virtual interactions. The burgeoning popularity of high-definition virtual reality games, backed by investments from various companies, underscores the potential of 5G networks. The swift speeds of 5G networks further contribute to an enriched gaming experience through high-speed Internet connectivity.
Internet of Things (IoT):
Leveraging a high-powered 5G wireless network, the development potential within the Internet of Things (IoT) is extensive. IoT envisions a comprehensive network interlinking objects, appliances, sensors, devices, and applications to the Internet. The application of IoT involves the aggregation of substantial data volumes from countless devices and sensors. The need for a capable network handling efficient data collection, processing, transmission, control, and real-time analytics is crucial. 5G emerges as a top contender for IoT applications due to its adaptability, availability of untapped spectrum, and cost-effective deployment solutions. The integration of 5G networks can furnish IoT with numerous advantages in various domains:
Smart Home:
The domain of intelligent home appliances and products is rapidly gaining momentum in the present market scenario. The concept of smart homes will utilize 5G networks to establish seamless connectivity among devices and enable real-time application monitoring. Smart appliances will effectively utilize the potential of the 5G wireless network facilitating remote access and configuration. Closed-circuit cameras will contribute by delivering high-quality, real-time video streams for security purposes.
Logistics and Shipping:
The logistics and shipment industry is poised to experience substantial advantages through the integration of intelligent 5G technology. This advancement can be effectively employed for tasks such as goods tracking, optimizing fleet management, centralized administration of databases, staff scheduling, and the real-time monitoring and reporting of deliveries.
Smart Cities:
Applications within smart cities, encompassing tasks like traffic management, immediate weather updates, local area broadcasting, energy management, smart power grids, street lighting control, water resource management, crowd management, and emergency responses, can seamlessly operate through a dependable 5G wireless network.
Industrial IoT:
The further improvisations of industries rely on intelligent wireless communications like 5G and LTE Advanced, for enhancing equipment automation, preventative maintenance, security protocols, process monitoring, intelligent packaging, efficient shipment, logistics, and resource management. The potential of smart sensor functionality is boundless offering answers for industrial IoT, ensuring smarter, safer, cost-conserving, and effectiveresource-utilization industrial operations.
Advanced Agriculture:
In the impending era, the 5G technology is set to play a pivotal role in the agricultural sector, particularly in smart farming. By leveraging intelligent sensors with RFID mounted and GPS technology, farmers can effectively monitor the whereabouts and management of livestock. Smart sensors prove valuable in tasks such as regulating irrigation, managing access, and optimizing energy consumption.
Healthcare and Crucial Applications:
The realm of healthcare stands to be positively impacted by 5G technology serving as a dependable wireless network even across global distances for advanced medical procedures. This technology extends to connected classrooms enabling students to participate in seminars and important lectures. Individuals with chronic health severities will gain from smart equipment and real-time overlooking. Healthcare practitioners can engage with patients anytime, anywhere offering guidance as needed. Additionally, the realm of smart medical devices capable of remote surgeries is actively being explored by scientists. The healthcare industry necessitates the integration of all its operations through a robust network. 5G will empower this sector with smart medical devices, the Internet of Medical Things (IoMT), intelligent analytics, and cutting-edge medical radio-imaging technologies.
Intelligent Medical Equipment:
Including wearable
[17]
, are designed to consistently monitor a patient’s well-being and trigger alerts during uncertainties. Hospitals and medical services will promptly receive alerts in critical scenarios facilitating swift diagnosis and treatment procedures. Individuals with specific requirements could be monitored with the help of specialized stubs and exact location-tracing equipment. Accessible from anywhere, healthcare databases enable data analysis for research and treatment enhancements. Notably, medical professionals will have the capacity to swiftly share sizable files, such as MRI reports, often exceeding 1 GB in capacity, within fractions of a second via a 5G networking.
Autonomous Driving:
The reality of self-driving cars draws closer through the utilization of 5G wireless networks
[18]
. The significance of high-performing wireless connection with minimal delay is paramount for the advancement of autonomous driving. In the forthcoming scenarios, vehicles can seamlessly communicate with intelligent traffic signs, adjacent objects, and fellow vehicles on the road. Given the split-second decisions crucial for self-driving cars to avoid collisions and ensure passenger safety, each millisecond holds great importance.
Drone Operations:
Drones have gained popularity for a multitude of applications spanning recreation video recording, emergency and medical assistance, efficient delivery solutions, security, and surveillance, among others. The 5G network offers robust support, facilitating swift wireless Internet connection for diverse drone operations
[19]
across an extensive range of uses. Especially during emergencies, such as natural disasters, drones can access areas inaccessible to humans, gathering valuable information.
Security and Surveillance:
The 5G wireless technology emerges as an optimal solution for preventive and supervision requirements attributing its vast bandwidth and utilization of illicit spectrum
[20]
.
1.5 Knowledge Management in Industry 4.0
In the context of the Fourth Industrial Revolution (IR4), there are several techniques used in knowledge management [2] to effectively harness and utilize information. Some of these techniques include:
Data Analytics
: IR4 generates vast amounts of data. Data analysis techniques, including machine learning and artificial intelligence, can extract valuable insights from this data. By analyzing patterns and trends, organizations can make informed decisions and improve their knowledge-management processes.
Knowledge-Sharing Platforms:
Collaborative platforms and knowledge-sharing tools enable employees to share their expertise, experiences, and best practices. These platforms can include intranets, wikis, forums, and social networks fostering a culture of knowledge sharing and collaboration within organizations.
Knowledge Mapping:
Knowledge mapping involves visualizing and organizing knowledge assets within an organization. It helps identify experts, knowledge gaps, and areas of expertise. By mapping knowledge, organizations can better understand their knowledge resources and make informed decisions about knowledge acquisition and distribution.
Knowledge Repositories:
Creating centralized repositories for storing and accessing knowledge is crucial in IR4. These repositories can consist of databases, document management systems, and content management systems. They provide a structured and easily accessible knowledge base for employees to retrieve information when needed.
Expert Systems:
Expert systems use artificial intelligence techniques to capture and replicate the knowledge and expertise of human experts. These systems can provide automated responses, recommendations, and solutions based on the captured knowledge. They help organizations leverage expert knowledge even when the experts are not physically available.
Continuous Learning and Training:
IR4. Emphasizes the need for continuous learning and up-skilling. Organizations can implement e-learning platforms, virtual training programs, and micro-learning techniques to ensure employees have access to relevant knowledge and skills to adapt to the rapidly changing technological landscape. These techniques in knowledge management help organizations effectively capture, organize, share, and utilize knowledge in the context of IR4 enabling them to stay competitive and innovative in the digital era.
1.5.1 Architecture of Knowledge Management
The architecture of knowledge management [21] involves the integration of advanced technologies and strategies to effectively capture, store, organize, and utilize knowledge within an organization. While there is no specific image associated with the architecture, here is a general overview of the key components [22]:
Data Sources
: Knowledge management in IR4. Relies on various data sources, consisting of structured and unstructured data from interior and exterior sources such as databases, documents, social media, and IoT devices.
Data Capture and Extraction:
Advanced technologies like artificial intelligence (AI) and machine learning (ML) are used to capture and extract relevant knowledge from the data sources. This involves techniques such as natural language processing (NLP) for text analysis and computer vision for image and video analysis.
Knowledge Storage:
The extracted knowledge is stored in a centralized repository or a distributed database depending on the organization’s requirements. This can include data lakes, data warehouses, or cloud-based storage solutions.
Knowledge Organization and Retrieval:
Knowledge is organized using taxonomies, ontologies, or metadata to enable efficient retrieval. Semantic technologies and search algorithms are employed to categorize and index the knowledge making it easily accessible to users.
Collaboration and Sharing:
IR4 emphasizes collaboration and sharing of knowledge. Collaborative platforms, social networks, and knowledge sharing tools are used to facilitate communication and collaboration among employees, teams, and departments.
Analytics and Insights:
Advanced analytics techniques, such as data mining, predictive analytics, and visualization, are applied to gain insights from the stored knowledge. This aids in identifying patterns, trends, and valuable insights that can inform decision making and foster innovation.
Security and Privacy:
Given the sensitive nature of knowledge, robust security measures are implemented to protect intellectual property and ensure data privacy. This includes access controls, encryption, and compliance with data protection regulations. The architecture of knowledge management in IR4 is dynamic and continuously evolving as new technologies and strategies emerge. It aims to leverage the power of data and advanced technologies to enable organizations to make informed decisions, foster innovation, and gain a competitive edge in the digital era.
1.6 The Role of 5G Technology in Knowledge Management
The 5G technology has greater ability to revolutionize knowledge management by enabling faster and more efficient data transfer. With 5G, organizations can access and share information in real time allowing for quicker decision making and collaboration. Additionally, 5G can support the usage of modern technologies like augmented reality and virtual reality, which can enhance knowledge sharing and training. Overall, the 5G technology has the ability to greatly improve knowledge-management processes and outcomes [23]. In order to optimize knowledge management for 5G, there are a few modifications that can be considered. First, it is significant to make sure that the knowledge-management systems and platforms are compatible with the elated speed and efficiency of 5G networks. This may involve upgrading hardware and software to handle the higher data transfer rates. Additionally, with the advancement of 5G, there will be a significant increase in the volume of data generated, growing exponentially. Therefore, it is crucial to enhance data storage and processing capabilities to effectively manage and analyze this vast amount of information. This could involve implementing advanced data-management techniques such as cloud-based solutions for distributed computing. Furthermore, the 5G technology enables real-time communication and collaboration, which can greatly enhance knowledge sharing and collaboration within organizations. To leverage this capability, it would be beneficial to integrate collaborative tools and platforms into the knowledge-management systems. This could include features like instant messaging, video conferencing, and virtual collaboration spaces. Last, as 5G networks enable connectivity across various devices and locations, it is important to ensure that knowledge-management systems are accessible and user-friendly on different devices such as smartphones, tablets, and laptops. This may involve developing responsive and mobile-friendly interfaces for seamless access to knowledge resources.
Overall, adapting knowledge-management systems to the advancements brought by 5G technology can greatly enhance the efficiency and effectiveness of knowledge sharing [24] and collaboration within organizations.
1.7 Challenges of Implementing 5G Technology for Knowledge Management
While 5G has the strength to greatly enhance knowledge-management tasks, there are several problems or challenges that need to be addressed in order to successfully implement it. Some of these challenges [25] include:
Infrastructure requirements:
5G networks require significant core set up upgrades, including the deploying of new base stations and optical fiber cables. This can be an expensive and time-consuming task especially in regions with restricted existing infrastructure.
Security concerns:
As with any new technology, there are concerns around the security of 5G networks. With more devices connected to the network, there is a greater risk of cyberattacks and data breaches.
Interoperability issues:
There are currently multiple standards for 5G technology, which can create interoperability issues between different networks and devices. This can make it difficult to ensure seamless connectivity and data transfer.
Regulatory challenges:
The rollout of 5G networks is subject to regulatory approval, which can vary by country and region. This can create challenges for organizations operating in multiple jurisdictions.
There can be some other challenges faced when implementing it in industries. One of the main difficulties is the initial cost of upgrading existing infrastructure to support 5G. This includes installing new equipment, upgrading network components, and ensuring compatibility with 5G standards. The financial investment required for this transition can be a significant hurdle for some industries.
Another challenge is the need for extensive coverage and infrastructure deployment. 5G networks rely on a dense network of small cells to provide high-speed connectivity. This means that industries may need to invest in deploying a large number of small cells to ensure reliable coverage throughout their facilities. This can be particularly challenging in remote or rural areas where infrastructure deployment may be more difficult.
Additionally, the increased complexity of 5G networks can pose challenges in terms of network management and security. With more devices connected and higher data-transfer rates, industries need to ensure robust network management systems to handle the increased traffic and maintain network performance. Moreover, the increased connectivity also raises concerns about cybersecurity and data privacy requiring industries to implement stringent security measures to protect sensitive information.
Last, the adoption of 5G technology may require industries to reevaluate their existing processes and workflows to fully leverage its capabilities. This could involve training employees on new technologies, updating protocols, and integrating 5G-enabled devices and applications into existing systems. Adapting to these changes and ensuring a smooth transition can be a time-consuming and complex task.
Despite these challenges, the potential benefits of 5G technology in industries, such as increased efficiency, faster data transfer, and improved connectivity [26], make it worth considering and addressing these difficulties.
1.8 Future Trends and Developments in 5G Technology and Knowledge Management
The future scope of 5G technology in knowledge management is quite promising. With its high-speed connectivity, low latency, and increased capacity, 5G has the potential to revolutionize how knowledge is managed and shared within organizations [27]. One significant aspect is the ability to access and share knowledge in real time. With 5G, employees can collaborate seamlessly regardless of their physical location. This means that knowledge can be shared instantly leading to faster decision making and problem solving. Additionally, 5G enables the use of advanced technologies like augmented reality (AR) and virtual reality (VR) [28], which can enhance knowledge management by providing immersive and interactive experiences for training, simulations, and remote collaboration.
Another area where 5G can have a significant impact is in the Internet of Things (IoT). With 5G’s ability to connect a massive number of devices simultaneously, IoT devices can gather and transmit data in real time enabling organizations to collect valuable insights and knowledge [29]. This can lead to more informed decision making and the ability to proactively address issues. Furthermore, 5G’s increased bandwidth and capacity can support the storage and processing of large amounts of data. This can enable organizations to implement advanced analytics and machine-learning algorithms [30] to extract valuable knowledge and insights from the data. This, in turn, can help in identifying patterns, trends, and correlations that may have been previously overlooked.
Increased adoption of 5G-enabled devices:
As more and more devices become 5G enabled, the potential for knowledge-management applications to leverage the speed and capabilities of 5G networks will increase.
Greater use of augmented reality and virtual reality:
5G networks can support the use of advanced technologies like augmented reality and virtual reality, which can enhance knowledge sharing and training. As these technologies become more widely adopted, we can expect to see more knowledge-management applications leveraging them.
Improved data analytics:
5G networks can enable faster and more efficient data transfer, which can support more advanced data analytics capabilities. This can help organizations to gain deeper insights into their data and make more informed decisions.
Increased use of edge computing:
5G networks can facilitate edge computing, which involves processing data in proximity to its source rather than sending it to a centralized data center. This enables quicker processing and analysis of data, making it especially valuable for knowledge-management applications.
Overall, these trends and developments are likely to lead to more advanced and sophisticated knowledge-management applications that leverage the speed and capabilities of 5G networks. The future scope of 5G technology in knowledge management is vast. It has the potential to transform how knowledge is shared, accessed, and utilized within organizations leading to improved collaboration, faster decision making, and enhanced innovation.
References
1. Majid, M., Habib, S., Javed, A.R., Rizwan, M., Srivastava, G., Gadekallu, T.R., Lin, J.C., Applications of wireless sensor networks and internet of things frameworks in the industry revolution systematic literature review.
Sensors
, 22, 6, 2087, 2022.
2. Khuntia, M., Singh, D., Sahoo, S., Impact of internet of things (IoT) on 5g, in:
Intelligent and Cloud Computing: Proceedings of ICICC 2019
, vol. 2, pp. 125–136, Springer, Singapore, 2021.
3. Pons, M., Valenzuela, E., Rodríguez, B., Nolazco-Flores, J.A., Del-Valle-Soto, C., Utilization of 5g technologies in iot applications: Current limitations by interference and network optimization difficulties - A review.
Sensors
, 23, 8, 3876, 2023.
4. Attarbashi, Z.S., Altaleb, A.E., Mohd Aman, A.H., Hassan Abdalla Hashim, A., Eker, S., A review of 5g technology: Architecture and challenges, in:
2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED)
, pp. 1–4, IEEE, 2022.
5. William, P., Choubey, S., Ramkumar, M., Verma, A., Vengatesan, K., Choubey, A., Implementation of 5G network architecture with interoperability in heterogeneous wireless environment using radio spectrum, in:
2022 International Conference on Electronics and Renewable Systems (ICEARS)
, pp. 786–791, IEEE, 2022.
6. Kazmi, S.H.A., Qamar, F., Hassan, R., Nisar, K., Chowdhry, B.S., Survey on Joint Paradigm of 5G and 1SDN Emerging Mobile Technologies: Architecture, Security, Challenges and Research Directions.
Wirel. Pers. Commun.
, 130, 4, 2753–2800, 2023.
7. Siddiqui, M.U.A., Qamar, F., Tayyab, M., Hindia, M.N., Nguyen, Q.N., Hassan, R., Mobility Management Issues and Solutions in 5G- and Beyond Networks: A Comprehensive Review.
Electronics
, 11, 9, 1366, 2022.
8. Marquez-Barja, J.M., Naudts, D., Maglogiannis, V., Hadiwardoyo, S.A., Moerman, I., Klepper, M., Kakes, G., Lian, X., Vandenberghe, W., Kusumakar, R.
et al.
, Designing a 5G Architecture to Overcome the Challenges of the Teleoperated Transport and Logistics, in:
2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)
, IEEE, pp. 264–267, 2022.
9. Husain, S., Kunz, A., Song, J., 3GPP 5G core network: An Overview and Future Directions.
J. Inf. Commun. Converg. Eng.
, 20, 1, 2022.
10. Chen, Z., Ao, J., Luo, W., Cheng, Z., Liu, Y., Sheng, K., Chen, L., A Dual-Factor Access Authentication Scheme for IoT Terminal in 5G Environments with Network Slice Selection.
J. Inf. Secur. Appl.
, 68, 103247, 2022.
11. Kundel, R., Meuser, T., Koppe, T., Hark, R., Steinmetz, R., User plane hardware acceleration in access networks: Experiences in Offloading Network Functions in Real 5G Deployments, in:
HICSS
, 2022.
12. Park, S., Kwon, S., Park, Y., Kim, D., You, I., Session Management for Security Systems in 5G Standalone Network.
IEEE Access
, 10, 73421–73436, 2022.
13. Attar, H., Issa, H., Ababneh, J., Abbasi, M., Solyman, A.A.A., Khosravi, M., Said Agieb, R.
et al.
, 5G System Overview for Ongoing Smart Applications: Structure, Requirements, and Specifications.
Comput. Intell. Neurosci.
, 2022, 2022.
14. Tsaramirsis, G., Kantaros, A., Al-Darraji, I., Piromalis, D., Apostolopoulos, C., Pavlopoulou, A., Alrammal, M., Ismail, Z., Buhari, S.M., Stojmenovic, M.
et al.
, A Modern Approach Towards an Industry 4.0 model: From Driving Technologies to Management.
J. Sens.
, 1–18, 2022.
15. Javaid, M., Haleem, A., Rab, S., Singh, R.P., Suman, R., Mohan, S., Progressive Schema of 5G for Industry 4.0: Features, Enablers, and Services.
Ind. Robot: Int. J. Robotics Res. Appl.
, 49, 3, 527–543, 2022.
16. Ghoraishi, M., 5G-Clarity Executive Summary, pp. 11–15, 2023.
17. Long, N., Lei, Y., Peng, L., Xu, P., Mao, P., A scoping review on monitoring mental health using smart wearable devices.
Math. Biosci. Eng
, ., 19, 8, 7899–7919, 2022.
18. Parekh, D., Poddar, N., Rajpurkar, A., Chahal, M., Kumar, N., Joshi, G.P., Cho, W., A Review on Autonomous Vehicles: Progress, Methods and Challenges.
Electronics
, 11, 14, 2162, 2022.
19. Balamurugan, N.M., Mohan, S., Adimoolam, M., John, A., Wang, W.
et al.
, DOA Tracking for Seamless Connectivity in Beamformed IoT based Drones.
Comput. Stand. Interfaces
, 79, 103564, 2022.
20. Gangwar, P.K., The Internet of Things Integration in Building Information Management Towards Construction 4.0.
J. Surv. Fish. Sci.
, 10, 2S, 1662–1671, 2023.
21. Logeshwaran, J., Kiruthiga, T., Lloret, J., A Novel Architecture of Intelligent Decision Model for Efficient Resource Allocation in 5G Broadband Communication Networks.
ICTACT J. Soft Comput.
, 13, 3, 2023.
22. Tiwari, S.P., Knowledge Management Strategies and Emerging Technologies - An Overview of the Underpinning -Concepts-Siddhartha Paul Tiwari. Authorea Preprints. 2022 Apr 20.
23. Zhao, J., Influence of Knowledge Sharing on Students’ Learning Ability Under the Background of “5G + AI”.
Int. J. Emerg. Technol. Learn. (iJET)
, 17, 1, 133–145, 2022.
24. Samtani, S., Zhao, Z., Krishnan, R., Secure Knowledge Management and Cybersecurity in the Era of Artificial Intelligence.
Inf. Syst. Front.
, 25, 2, 425– 429, 2023.
25. Dong, X. and Yu, Y., Knowledge Management in the Digital Economy Era: Challenges and Trends, in:
The Routledge Companion to Knowledge Management
, pp. 115–127, 2022.
26. Pradhan, D., Tun, H.M., Dash, A.K., Iot: Security & Challenges of 5G Network in Smart Cities.
Asian J. Converg. Technol.
, 8, 2, 45–5, 2022, ISSN-235-1146.
27. Xu, X. and He, Y., Blockchain Application in Modern Logistics Information Sharing: A Review and Case Study Analysis.
Prod. Plan. Control
, 1–15, 2022.
28. Zhang, Z., Wen, F., Sun, Z., Guo, X., He, T., Lee, C., Artificial Intelligence-Enabled Sensing Technologies in the 5G/Internet of Things Era: from Virtual Reality/Augmented Reality to the Digital Twin.
Adv. Intell. Syst.
, 4, 7, 210028, 2022.
29. Huseien, G.F. and Shah, K.W., A Review on 5G Technology for Smart Energy Management and Smart Buildings in Singapore.
Energy AI
, 7, 100116, 2022.
30. Almutairi, M.S., Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction.
Math. Probl. Eng.
, 1–27, 2022.
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