Evidence map›Paper›PMID 40293074›Full record

ArticleSensors (Basel, Switzerland)2025

Hybrid Dual-Link Data Transmission Based on Internet of Vessels.

Fei Li, Ying Guo, Ziqi Wang, Yuhang Chen, Jingyun Gu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Fei LiCollege of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China.ORCID 0009-0008-2966-7964
Ying GuoCollege of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China.ORCID 0000-0002-5327-6292
Ziqi WangCollege of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China.
Yuhang ChenCollege of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China.
Jingyun GuCollege of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transmission of marine data is an urgent global challenge. Due to the particularity of underwater environments, the efficiency and reliability of data transmission in underwater acoustic communication are severely restricted, especially in long-distance and large-scale data transmission situations. This study proposes a dual-link data transmission method based on the Internet of Vessels, utilizing the powerful communication capabilities and flexibility of ships as relay nodes for data transmission. By constructing both above-water and underwater dual-link collaborative transmission, the method effectively improves data transmission rates and stability. Additionally, a spatial crowdsourcing allocation algorithm based on Bayesian reputation selection is designed to assess the capability of ships to complete tasks, and an integrated scoring function is used to select the optimal relay ship, solving the problems of relay ship selection and transmission path selection in the data transmission process. Furthermore, this study introduces an incentive mechanism for data transmission based on the Internet of Vessels, which maximizes the stability of data transmission. Experimental results show that the dual-link data transmission method of the Internet of Vessels significantly improves the reliability and transmission speed of underwater communication, providing a novel and practical solution for long-distance, large-volume data transmission in maritime environments.

Indexed as

dual-link data transmissionInternet of Vesselsmulti-hopspatial crowdsourcing task allocation

Identifiers

PMID40293074
PMCPMC11946692

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.