The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Industry 4.0 in the port and maritime industry: A literature review
Abstract
Abstract Ports and terminals have evolved and from the 2010s have entered into a fifth stage of evolution characterized by their digital transformation and alignment with Industry 4.0 practices. Co-operation among agents is a key element and integration not only involves Port Authorities, Terminals and Port users and related Port Services Providers but the city, port's hinterland and well beyond the Global Supply Chain. Internet of Things and sensing solutions, cybersecurity, horizontal and vertical system integration, cloud computing, 3D printing and additive manufacturing, big data and business analytics, augmented reality and simulation and modeling are the pillars of Industry 4.0. Some of those are mature enough in the port and maritime industry. However, others remain in their earliest stages in this business and thus, poorly covered by the scientific literature. The article reviews the state of the art on these new emerging technologies, summarizing how ports and terminals are deploying specific projects in the new era of smart ports and Ports 4.0.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172
Internet of things and supply chain management: A literature review
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019) · International Journal of Production Research · doi:10.1080/00207543.2017.1402140 · Cited by 1,501
An ultrasonic sensor for distance measurement in automotive applications
Carullo, A., & Parvis, M. (2001) · IEEE Sensors Journal · doi:10.1109/jsen.2001.936931 · Cited by 382
Ku, A. Y. (2018) · Sustainable Materials and Technologies · doi:10.1016/j.susmat.2017.10.001 · Cited by 28
Cited by
Industry 5.0: A survey on enabling technologies and potential applications
Maddikunta, P. K. R., Pham, Q.-V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2021.100257 · Cited by 1,890
Metadata
- Authors
- de la Peña Zarzuelo, I., Freire Soeane, M. J., & López Bermúdez, B.
- Venue
- Journal of Industrial Information Integration
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 20
- Pages
- 100173
- ISSN
- 2452-414X (ISSN-L)
- OpenAlex
- W3090500826
- Cited by
- 269
- References
- 4
- FWCI
- 18.70
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.