Autonomous vehicles with augmented reality internet of things and edge intelligence system for industry 5.0 based on 6G

In an era of rapidly evolving technology, traditional cloud computing struggles to meet the demands of resource-intensive smart devices. This necessitates a shift towards Edge Computing (EC), which brings computation and data storage closer to the network's edge, enhancing efficiency and reducing latency. This is particularly crucial for the Internet of Things (IoT), where supporting mobility, location awareness, and real-time processing are paramount. However, the scalability of EC applications is significantly influenced by network parameters and the capabilities of the computing system. This paper proposes a novel system architecture for Industry 5.0 that leverages the synergy between 6G networks, autonomous vehicles, Augmented Reality (AR), IoT, and edge intelligence to revolutionize transportation systems. Our approach integrates AR for enhanced user interfaces, utilizes IoT for data acquisition and control, and employs edge computing for real-time decision-making. Our experimental results demonstrate a strong correlation between processing speed and network bandwidth. While increasing either parameter individually enhances overall system performance. The two-tier architecture, combined with the Entity Objects (EO) model, demonstrates superior scalability compared to traditional approaches. By distributing processing tasks and leveraging the resources of other edge servers, the system can handle increasing numbers of AVs and data loads without compromising performance.

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Publication Details

Journal
PLoS ONE
Published
2025-12-18
DOI
https://doi.org/10.1371/journal.pone.0339022
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Autonomous vehicles with augmented reality internet of things and edge intelligence system for industry 5.0 based on 6G

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PLoS ONE
IoT and Edge/Fog Computing
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Autonomous vehicles with augmented reality internet of things and edge intelligence system for industry 5.0 based on 6G

Amjed Abbas Ahmed, Salah A. Aliesawi, Abir Hussain, Belal Abdullah Hezam Murshed, Sumaia Mohammed Al-Ghuribi, Dhafar Hamed, Luke Topham, Aqeel Kamil Kadhim, Wasiq Khan, Mohammad Kamrul Hasan
article en

Abstract

In an era of rapidly evolving technology, traditional cloud computing struggles to meet the demands of resource-intensive smart devices. This necessitates a shift towards Edge Computing (EC), which brings computation and data storage closer to the network's edge, enhancing efficiency and reducing latency. This is particularly crucial for the Internet of Things (IoT), where supporting mobility, location awareness, and real-time processing are paramount. However, the scalability of EC applications is significantly influenced by network parameters and the capabilities of the computing system. This paper proposes a novel system architecture for Industry 5.0 that leverages the synergy between 6G networks, autonomous vehicles, Augmented Reality (AR), IoT, and edge intelligence to revolutionize transportation systems. Our approach integrates AR for enhanced user interfaces, utilizes IoT for data acquisition and control, and employs edge computing for real-time decision-making. Our experimental results demonstrate a strong correlation between processing speed and network bandwidth. While increasing either parameter individually enhances overall system performance. The two-tier architecture, combined with the Entity Objects (EO) model, demonstrates superior scalability compared to traditional approaches. By distributing processing tasks and leveraging the resources of other edge servers, the system can handle increasing numbers of AVs and data loads without compromising performance.

PLoS ONEVol. 20(12)
University of Baghdad (IQ), Prince Sattam Bin Abdulaziz University (SA), University of Anbar (IQ), University of Sharjah (AE), Alsalam University College (IQ), Imam Sadiq University (IR), Amran University (YE), Liverpool John Moores University (GB), National University of Malaysia (MY)
Openalex Percentile: Top 54%
IoT and Edge/Fog Computing
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