A Digital Twin Architecture Based on the Industrial Internet of Things Technologies
Abstract
Computation and communication evolved to enable digital representations of physical systems. Decision-making support via data analysis, virtualization of machinery control, information flowing over the Internet are all trending on industrial systems. This allowed emerging one of the main concepts applied in manufacturing processes, the Digital Twins. A digital counterpart of a physical process allows management, remote control and simulations over the process in a safe environment. This work proposes guidelines to design a Digital Twin architecture using Industrial Internet of Things and the integration of current technologies, applying these aspects in an experimental application.
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Digital twins support supply chain management through data monitoring.
“supporting the supply chain management through data monitoring [23,26]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [26]
Seven articles in Table 1 developed ad-hoc systems to build DT.
“In Table 1 seven articles developed ' ad-hoc ' systems to build DT: for the management of a didactic production line [26], to construct a MES in Android systems [43], to build user guides for safety reason [60,62], and to evaluate the performances of a cloud-based DT [74,75];”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [26]
The Industrial Internet of Thing Consortium is addressing the manufacturing community with its architecture and APIs.
“For example, the Industrial Internet of Thing Consortium is addressing the manufacturing community with its architecture and APIs [25][26].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [26]
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“…University of Amazonas, Manaus, Brazil {vss, sidneylins}@icomp.ufam.edu.br; {robsoncruz, wasacioli, vicente}@ufam.edu.br The information gathering from the environment and its context are one of the main features of IoT, consequently IIoT as well, and crucial for the DT aware the PT status [7].”
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- Authors
- Souza, V., Cruz, R., Silva, W., Lins, S., & Lucena, V.
- Affiliations
- Universidade Federal do Amazonas (BR)
- Venue
- 2019 IEEE International Conference on Consumer Electronics (ICCE)
- Publisher
- IEEE
- Published
- 2019-01
- Pages
- 1-2
- OpenAlex
- W2922263402
- Cited by
- 89
- References
- 6
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 14 · 2023: 21 · 2022: 17 · 2021: 20 · 2020: 8 · 2019: 5
- FWCI
- 18.14
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Consumer Electronics (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Physical Sciences › Engineering › Control and Systems Engineering › Industrial Automation and Control Systems
- Keywords
- digital twin, digital twin architecture, Industrial Internet of Things, production process, remote control, process simulation, technology integration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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