Evidence map›Paper›PMID 38257686›Full record

ArticleSensors (Basel, Switzerland)2024

IoT-Based Framework for Digital Twins in the Industry 5.0 Era.

Ahmed Awouda, Emiliano Traini, Giulia Bruno, Paolo Chiabert

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Medical Digital Twin Technology for Interoperability: Challenges and Opportunities.Biomedical engineering and computational biology · 2026
    Review
  3. Review
  4. A Review of Digital Twinning for Rotating Machinery.Sensors (Basel, Switzerland) · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ahmed AwoudaDepartment of Management and Production Engineering, Politecnico di Torino, 10129 Turin, Italy.ORCID 0000-0002-6079-0919
Emiliano TrainiDepartment of Management and Production Engineering, Politecnico di Torino, 10129 Turin, Italy.
Giulia BrunoDepartment of Management and Production Engineering, Politecnico di Torino, 10129 Turin, Italy.ORCID 0000-0001-5585-647X
Paolo ChiabertDepartment of Management and Production Engineering, Politecnico di Torino, 10129 Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital twins are considered the next step in IoT-based cyber-physical systems; they allow for the real-time monitoring of assets, and they provide a comprehensive understanding of a system behavior, allowing for data-driven insights and informed choices. However, no comprehensive framework exists for the development of IoT-based digital twins. Moreover, the existing frameworks do not consider the aspects introduced by the Industry 5.0 paradigm, such as sustainability, human-centricity, and resilience. This paper proposes a framework based on the one defined as the outcome of a project funded by the European Union between 2010 and 2013 called the IoT Architectural Reference Model (IoT-A or IoT-ARM), with the aim of the development and implementation of a standard IoT framework that includes digital twins. This framework establishes and implements a standardized collection of architectural instruments for modeling IoT systems in the 5.0 era, serving as a benchmark for the design and implementation of an IoT architecture focused on digital twins and enabling the sustainability, resilience, and human-centricity of the information system. Furthermore, a proof of concept of a monitoring digital twin for a vertical farming system has been developed to test the validity of the framework, and a discussion of applications in the manufacturing and service sectors is presented.

Indexed as

aeroponicsdigital twinIndustry 5.0Internet of ThingsIoT-ARM

Identifiers

PMID38257686
PMCPMC10819514

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.