Evidence map›Paper›PMID 38794094›Full record

ArticleSensors (Basel, Switzerland)2024

Hydrogen 4.0: A Cyber-Physical System for Renewable Hydrogen Energy Plants.

Ali Yavari, Christopher J Harrison, Saman A Gorji, Mahnaz Shafiei

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Ali YavariSchool of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia.ORCID 0000-0002-0588-5931
Christopher J HarrisonSchool of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia.ORCID 0000-0002-6270-0630
Saman A GorjiHydrogen 4.0 Lab, Swinburne University of Technology, Melbourne, VIC 3122, Australia.ORCID 0000-0002-8712-959X
Mahnaz ShafieiSchool of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC 3122, Australia.ORCID 0000-0002-3520-1553

Funding

Australian Renewable Energy Agency 2018/RND012Future Energy Exports CRC 21.RP2.0062
6 · The paper itself

Abstract

The demand for green hydrogen as an energy carrier is projected to exceed 350 million tons per year by 2050, driven by the need for sustainable distribution and storage of energy generated from sources. Despite its potential, hydrogen production currently faces challenges related to cost efficiency, compliance, monitoring, and safety. This work proposes Hydrogen 4.0, a cyber-physical approach that leverages Industry 4.0 technologies-including smart sensing, analytics, and the Internet of Things (IoT)-to address these issues in hydrogen energy plants. Such an approach has the potential to enhance efficiency, safety, and compliance through real-time data analysis, predictive maintenance, and optimised resource allocation, ultimately facilitating the adoption of renewable green hydrogen. The following sections break down conventional hydrogen plants into functional blocks and discusses how Industry 4.0 technologies can be applied to each segment. The components, benefits, and application scenarios of Hydrogen 4.0 are discussed while how digitalisation technologies can contribute to the successful integration of sustainable energy solutions in the global energy sector is also addressed.

Indexed as

green hydrogenhydrogenHydrogen 4.0Industry 4.0Internet of Thingsrenewable energy

Identifiers

PMID38794094
PMCPMC11125211

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.