Environmental Intelligent Perception in the Industrial Internet of Things: A Case Study Analysis of a Multicrane Visual Sorting System

Fu, Meixia; Wang, Zhenqian; Wang, Jianquan; Wang, Qu; Jiansheng, Wu; Sun, Lei; Ma, Zhangchao; Huang, Rong; Li, Xianda; Wang, Danshi; Liang, Qilian

doi:10.1109/jsen.2023.3294962

Cited by 2 publications

(2 citation statements)

References 38 publications

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“…DMC platforms are one of the preferred cloud platforms for geodistributed networks [15], [16], [17], [18], including DSM. The University of Aizu's robot research group is working on the DMC shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

“…With respect to robustness, scalability and interoperability should be preserved without compromising integrity. We can then note that security, privacy, scalability, and interoperability are essential multiobjective QoS requirements for maintaining the integrity and robustness of components and operations [17], [18], [19], [20], [21], [22].…”

Section: Introductionmentioning

confidence: 99%

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QoS-Aware Federated Crosschain-Based Model-Driven Reference Architecture for IIoT Sensor Networks in Distributed Manufacturing

Siriweera,

Naruse

2023

IEEE Sensors J.

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The realm of the Industrial Internet of Things (IIoT) encompasses a broad spectrum of sensors that are integral to distributed smart manufacturing (DSM). The miscellaneous IIoT sensors deployed for DSM are distributed and operate in a hierarchical and federated structure. Nonetheless, fulfilling essential quality of service (QoS) requirements, such as ensuring security and privacy (integrity) while maintaining scalability and interoperability (robustness), poses a profound challenge for the DSM cloud service platform. Although blockchain technologies have been used to safeguard integrity, the first two generations have imposed constraints on robustness. In contrast, the third-generation blockchain, a.k.a. decentralized crosschain ecosystem, complements Web 3.0 and metaverse and can mitigate the constraints of previous generations. Moreover, blockchain-based ad hoc solutions for DSM use cases are abundant; they often suffer from limited adaptability and unique or homogeneous use cases from a software engineering perspective. A holistic architectural modeling process (AMP) leading to a software reference architecture (SRA) is preferred when alleviating ad hoc constraints. Therefore, we proposed an AMP for SRA for crosschain-based DSM that safeguards integrity while preserving robustness. In the work described in this article, we have conducted the following system-modeling process. First, we propose a novel software AMP for DSM. Second, we deduce a modeled SRA based on a crosschain. Third, we infer a modeled system architecture (SA). Empirical experiment results demonstrate that our proposed crosschain-based method outperforms the widely used on-chainbased method while achieving our objectives efficiently.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

QoS-Aware Federated Crosschain-Based Model-Driven Reference Architecture for IIoT Sensor Networks in Distributed Manufacturing

Siriweera,

Naruse

2023

IEEE Sensors J.

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Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse

Kliestik,

Kral,

Bugaj

et al. 2024

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Research background: Multi-modal synthetic data fusion and analysis, simulation and modelling technologies, and virtual environmental and location sensors shape the industrial metaverse. Visual digital twins, smart manufacturing and sensory data mining techniques, 3D digital twin simulation modelling and predictive maintenance tools, big data and mobile location analytics, and cloud-connected and spatial computing devices further immersive virtual spaces, decentralized 3D digital worlds, synthetic reality spaces, and the industrial metaverse. Purpose of the article: We aim to show that big data computing and extended cognitive systems, 3D computer vision-based production and cognitive neuro-engineering technologies, and synthetic data interoperability improve artificial intelligence-based digital twin industrial metaverse and hyper-immersive simulated environments. Geolocation data mining and tracking tools, image processing computational and robot motion algorithms, and digital twin and virtual immersive technologies shape the economic and business management of extended reality environments and the industrial metaverse. Methods: Quality tools: AMSTAR, BIBOT, CASP, Catchii, R package and Shiny app citationchaser, DistillerSR, JBI SUMARI, Litstream, Nested Knowledge, Rayyan, and Systematic Review Accelerator. Search period: April 2024. Search terms: “digital twin industrial metaverse” + “artificial Intelligence of Things systems”, “multisensory immersive extended reality technologies”, and “algorithmic big data simulation and modelling tools”. Selected sources: 114 out of 336. Published research inspected: 2022–2024. PRISMA was the reporting quality assessment tool. Dimensions and VOSviewer were deployed as data visualization tools. Findings & value added: Simulated augmented reality and multi-sensory tracking technologies, explainable artificial intelligence-based decision support and cloud-based robotic cooperation systems, and ambient intelligence and deep learning-based predictive analytics modelling tools are instrumental in augmented reality environments and in the industrial metaverse. The economic and business management of the industrial metaverse necessitates connected enterprise production and big data computing systems, simulation and modelling technologies, and virtual reality-embedded digital twins.

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Environmental Intelligent Perception in the Industrial Internet of Things: A Case Study Analysis of a Multicrane Visual Sorting System

Cited by 2 publications

References 38 publications

QoS-Aware Federated Crosschain-Based Model-Driven Reference Architecture for IIoT Sensor Networks in Distributed Manufacturing

QoS-Aware Federated Crosschain-Based Model-Driven Reference Architecture for IIoT Sensor Networks in Distributed Manufacturing

Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse

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