Evidence map›Paper›PMID 41547884›Full record

ArticleScientific reports2026

Ubiquitous sensing of marine activities via the cooperation of autonomous underwater vehicles.

Jing Yan, Yuehang Jiang, Xinxin Wang, Jianyu Yu, Xian Yang, Cailian Chen, Xinping Guan

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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

7 authors.

Jing Yan *Department of Electrical Engineering, Hebei Key Laboratory of Industrial Computer Control Engineering, Qinhuangdao, 066004, China. jyan@ysu.edu.cn.
Yuehang Jiang *Department of Electrical Engineering, Hebei Key Laboratory of Industrial Computer Control Engineering, Qinhuangdao, 066004, China. yuehangj@stumail.ysu.edu.cn.
Xinxin WangDepartment of Electrical Engineering, Hebei Key Laboratory of Industrial Computer Control Engineering, Qinhuangdao, 066004, China.
Jianyu YuDepartment of Electrical Engineering, Hebei Key Laboratory of Industrial Computer Control Engineering, Qinhuangdao, 066004, China.
Xian YangDepartment of Electrical Engineering, Hebei Key Laboratory of Industrial Computer Control Engineering, Qinhuangdao, 066004, China.
Cailian ChenSchool of Automation and Intelligent Sensing, Shanghai JiaoTong University, Shanghai, 200240, China.
Xinping GuanSchool of Automation and Intelligent Sensing, Shanghai JiaoTong University, Shanghai, 200240, China. xpguan@sjtu.edu.cn.

Funding

National Natural Science Foundation of China 62222314
6 · The paper itself

Abstract

Effective monitoring of marine activities is essential for optimizing the marine operations, ensuring the safety and protecting the marine environment. However, the existing monitoring approaches still have the problems of low intelligence, high cost and poor reliability. This article attempts to employ autonomous underwater vehicles (AUVs) to develop a ubiquitous monitoring system for marine activities. Particularly, it mainly includes AUVs, human operator, onshore cameras, and wireless communication networks. With the wireless communication networks, the human operator in the control center assigns monitoring tasks to AUVs and onshore cameras. After that, the cameras mounted on AUVs and shore collect the images of surface target (e.g., ship or buoy), such that the target attitudes can be estimated by using deep learning technology. For underwater target (e.g., shipwreck or drowning person), sonars are mounted on AUVs to carry out water depth detection. Finally, experimental results are provided to verify the effectiveness of our system. These results provide evidence that the AUV-assisted monitoring system can improve the reliability and reduce the cost over the manual monitoring system.

Identifiers

PMID41547884
PMCPMC12820200

What OpenQuestion holds

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Registered trials

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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.