Evidence map›Paper›PMID 34502637›Full record

ArticleSensors (Basel, Switzerland)2021

Green IoT and Edge AI as Key Technological Enablers for a Sustainable Digital Transition towards a Smart Circular Economy: An Industry 5.0 Use Case.

Paula Fraga-Lamas, Sérgio Ivan Lopes, Tiago M Fernández-Caramés

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  14. Digital Twins in Industry 5.0.Research (Washington, D.C.) · 2023
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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

3 authors.

Paula Fraga-LamasDepartment of Computer Engineering, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain.ORCID 0000-0002-4991-6808
Sérgio Ivan LopesADiT-Lab, Instituto Politécnico de Viana do Castelo, Rua da Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.ORCID 0000-0001-6944-7757
Tiago M Fernández-CaramésDepartment of Computer Engineering, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain.ORCID 0000-0003-2179-5917

Funding

Agencia Estatal de Investigación of Spain and ERDF funds of the EU (FEDER Galicia 2014-2020 & AEI/FEDER Programs, UE). RED2018-102668-T, PID2019-104958RB-C42CITIC funded by "Consellería de Cultura, Educación e Universidades from Xunta de Galicia", supported in an 80 % through ERDF Funds, ERDF Operational Programme Galicia 2014-2020, 20 % by "Secretaría Xeral de Universidades" ED431G 2019/01Xunta de Galicia ED431C 2020/15
6 · The paper itself

Abstract

Internet of Things (IoT) can help to pave the way to the circular economy and to a more sustainable world by enabling the digitalization of many operations and processes, such as water distribution, preventive maintenance, or smart manufacturing. Paradoxically, IoT technologies and paradigms such as edge computing, although they have a huge potential for the digital transition towards sustainability, they are not yet contributing to the sustainable development of the IoT sector itself. In fact, such a sector has a significant carbon footprint due to the use of scarce raw materials and its energy consumption in manufacturing, operating, and recycling processes. To tackle these issues, the Green IoT (G-IoT) paradigm has emerged as a research area to reduce such carbon footprint; however, its sustainable vision collides directly with the advent of Edge Artificial Intelligence (Edge AI), which imposes the consumption of additional energy. This article deals with this problem by exploring the different aspects that impact the design and development of Edge-AI G-IoT systems. Moreover, it presents a practical Industry 5.0 use case that illustrates the different concepts analyzed throughout the article. Specifically, the proposed scenario consists in an Industry 5.0 smart workshop that looks for improving operator safety and operation tracking. Such an application case makes use of a mist computing architecture composed of AI-enabled IoT nodes. After describing the application case, it is evaluated its energy consumption and it is analyzed the impact on the carbon footprint that it may have on different countries. Overall, this article provides guidelines that will help future developers to face the challenges that will arise when creating the next generation of Edge-AI G-IoT systems.

Indexed as

Internet of ThingsArtificial IntelligenceDiagnostic Tests, RoutineIndustryTechnologyAIdigital circular economydigital transitionedge AIedge computingGreen IoTIIoTIndustry 5.0sustainability

Identifiers

PMID34502637
PMCPMC8434294

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.