Collective Intelligence Using 5G: Concepts, Applications, and Challenges in Sociotechnical Environments

Narayanan, Arun; Korium, Mohamed Selim; Carrillo, Dick; Hussain, Hafiz Majid; Sena, Arthur Sousa de; Silva, Pedro E. Gória; Gutiérrez-Rojas, Daniel; Ullah, Mehar; Nezhad, Ali Esmaeel; Rasti, Mehdi; Pournaras, Evangelos; Nardelli, Pedro H. J.

doi:10.1109/access.2022.3184035

Cited by 9 publications

(4 citation statements)

References 191 publications

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“…Connector: Cellular networks have a wide and high-speed communication range, which allows a base station to preserve connectivity and continuously serve a mobile agent (e.g., vehicle). The upcoming 5G/6G cellular networks are leading technologies for native mobile edge computing capabilities [28], [29] to support mobility applications such as augmented reality with high network capacity and throughput/bandwidth. In SMOTEC, the connector manages the communication network and is responsible for communication between edge agents and service distributor.…”

Section: Testbed Design Modelmentioning

confidence: 99%

SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation

Nezami,

Pournaras,

Borzouie

et al. 2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

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Smart mobility becomes paramount for meeting net-zero targets. However, autonomous, self-driving and electric vehicles require more than ever before an efficient, resilient and trustworthy computational offloading backbone that expands throughout the edge-to-cloud continuum. Utilizing on-demand heterogeneous computational resources for smart mobility is challenging and often cost-ineffective. This paper introduces SMOTEC, a novel open-source testbed for adaptive smart mobility experimentation with edge computing. SMOTEC provides for the first time a modular end-to-end instrumentation for prototyping and optimizing placement of intelligence services on edge devices such as augmented reality and real-time traffic monitoring. SMOTEC supports a plug-and-play Docker container integration of the SUMO simulator for urban mobility, Raspberry Pi edge devices communicating via ZeroMQ and EPOS for an AI-based decentralized load balancing across edgeto-cloud. All components are orchestrated by the K3s lightweight Kubernetes. A proof-of-concept of self-optimized service placements for traffic monitoring from Munich demonstrates in practice the applicability and cost-effectiveness of SMOTEC.

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Section: Testbed Design Modelmentioning

confidence: 99%

SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation

Nezami,

Pournaras,

Borzouie

et al. 2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

Self Cite

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“…Towards this end, we have adopted Narayanan’s definition of collective intelligence (Narayanan et al, 2022), considering it as a decision-making approach in which intelligent and distributed IoT networks generate insights and feedback from their immediate environment and users. Together, they make collective decisions to perform tasks that lead to a common and desirable outcome.…”

Section: Introductionmentioning

confidence: 99%

Fostering new vertical and horizontal IoT applications with intelligence everywhere

Cao,

Wachowicz,

Richard

et al. 2023

Collective Intelligence

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Intelligence Everywhere is predicated on the seamless integration of INTERNET of Things (IoT) networks transporting a vast amount of data streams through many computing resources across an edge-to-cloud continuum, relying on the orchestration of distributed machine learning models. The result is an interconnected and collective intelligent ecosystem where devices, systems, services, and users work together to support IoT applications. This paper discusses the state-of-the-art research and the principles of the Intelligence Everywhere framework for enhancing IoT applications in vertical sectors such as Digital Health, Infrastructure, and Transportation/Mobility in the context of intelligent society (Society 5.0). It also introduces a novel perspective for the development of horizontal IoT applications, capable of running across various IoT networks while fostering collective intelligence across diverse sectors. Finally, this paper provides comprehensive insights into the challenges and opportunities for harnessing collective knowledge from real-time insights, leading to optimised processes and better overall collaboration across different IoT sectors.

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“…However, this progress is accompanied by a surge in data generated by interconnected devices, necessitating a thorough examination of data privacy and security within the realm of AI-powered industrial systems. Referred to as Industry 4.0, this convergence unfolds as an integrated technology encompassing big data analysis, cloud computing, artificial intelligence, mobile communications, and IoT functionalities [1]. The paper emphasizes the significance of IIoT in digital transformation, optimizing industrial processes, enhancing manufacturing efficiency, and ushering in a new era for traditional industries using the research survey.…”

Section: Introductionmentioning

confidence: 99%

Privacy-Preserving Techniques in Artificial Intelligence Applications for Industrial IOT Driven Digital Transformation

Saurabh Suman Choudhuri

2023

IJRITCC

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The advent of Industry 4.0 has brought about a revolution in the Industrial Internet of Things (IIoT) driving digital transformation, which now includes data analytics, cloud computing, artificial intelligence, and mobile connectivity. This paper delves into the effectiveness of existing privacy protection measures, as well as the challenges and opportunities presented by emerging technologies such as unified encryption and machine learning. Additionally, the paper provides insights into the processes required for industry-specific compliance with relevant laws and regulations. The findings emphasize the crucial role privacy plays in AI applications for IIoT systems and shed light on the strategies, obstacles, and prospects that organizations must navigate in this rapidly evolving landscape.

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Collective Intelligence Using 5G: Concepts, Applications, and Challenges in Sociotechnical Environments

Abstract: This paper is partly supported by Academy of Finland via (a) FIREMAN consortium n.326270 as part of CHIST-ERA grant CHIST-ERA-17-BDSI-003, and (b) EnergyNet Research Fellowship n.321265/n.328869 and (c) n.339541, and by Jane and Aatos Erkko Foundation via STREAM project.

Cited by 9 publications

References 191 publications

SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation

SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation

Fostering new vertical and horizontal IoT applications with intelligence everywhere

Privacy-Preserving Techniques in Artificial Intelligence Applications for Industrial IOT Driven Digital Transformation

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