Ship Wireless Sensor

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 20 December 2024 | Viewed by 839

Special Issue Editors


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Guest Editor
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: ocean wireless sensor networks; maritime wireless communication networks; intelligent perception of the marine environment

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Guest Editor
Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: logistics engineering and management

Special Issue Information

Dear Colleagues,

At present, the development of intelligent ships and unmanned ships has attracted widespread attention in the field of shipping. This will greatly enhance the level of digital and intelligent development of shipping and enable efficient navigation of ships, leading to rapid advancements. Moreover, wireless ship sensors and their information transmission networks are the key technologies among them. The major technical issues related to the intelligent perception of ships’ navigation environments, real-time fusion of information online, self-organizing networks of perception nodes, and efficient routing transmissions are worthy of an in-depth exploration, especially the urgent and significant practical applications of theoretical methods regarding the intelligent navigation of ships.

  • Background:

With the rapid development of intelligent ships and unmanned ships, the research on comprehensive wireless sensing technology for ship navigation has attracted great attention.

  • Aim and scope:

1) Front end of marine wireless sensor systems;

2) Marine wireless sensor systems;

3) Marine wireless sensor networks;

4) Ocean Internet of Things networking;

5) Wireless sensor information fusion for ships.

  • History:

In the past, ship navigation neglected the comprehensive perception of the ship's own state and the surrounding marine environment, making it impossible to achieve highly energy-efficient navigation.

  • Cutting-edge research:

Current state-of-the-art research focuses on ocean multi-source sensor information fusion; ocean collaborative perception; and integrated ocean network synesthesia.

  • The types of topics we are looking for papers to cover:

1) Ocean physical/chemical sensors; marine hydrological monitoring sensors; biosensors.

2) Ship wireless sensor monitoring systems; layout of ship sensor units; design of new wireless sensor modules for ships.

3) Marine wireless sensor network monitoring; deployment of surface/underwater wireless sensor networks; ocean wireless sensor networking; ocean wireless sensor networks routing; ocean sensor network relay; wireless sensor network for ships; topology optimization of ocean wireless sensor networks.

4) Ocean Internet of Things for assisted navigation; efficient information transmission based on ocean Internet of Things.

5) Ocean wireless sensor network information fusion; ocean network edge computing; ocean network cloud edge systems.

Prof. Dr. Ying Zhang
Prof. Dr. Zhihua Hu
Dr. Xinqiang Chen
Guest Editors

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Keywords

  • physical/chemical sensors
  • ocean/ship wireless sensors
  • ocean wireless sensor network
  • ocean internet of things
  • ocean mobile edge computing
  • networking
  • ocean network topology optimization
  • ocean network information security

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Published Papers (1 paper)

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Research

24 pages, 7675 KiB  
Article
Coordinated Ship Welding with Optimal Lazy Robot Ratio and Energy Consumption via Reinforcement Learning
by Rui Yu and Yang-Yang Chen
J. Mar. Sci. Eng. 2024, 12(10), 1765; https://doi.org/10.3390/jmse12101765 - 5 Oct 2024
Viewed by 517
Abstract
Ship welding is a crucial part of ship building, requiring higher levels of robot coordination and working efficiency than ever before. To this end, this paper studies the coordinated ship-welding task, which involves multi-robot welding of multiple weld lines consisting of synchronous ones [...] Read more.
Ship welding is a crucial part of ship building, requiring higher levels of robot coordination and working efficiency than ever before. To this end, this paper studies the coordinated ship-welding task, which involves multi-robot welding of multiple weld lines consisting of synchronous ones to be executed by a pair of robots and normal ones that can be executed by one robot. To evaluate working efficiency, the objectives of optimal lazy robot ratio and energy consumption were considered, which are tackled by the proposed dynamic Kuhn–Munkres-based model-free policy gradient (DKM-MFPG) reinforcement learning algorithm. In DKM-MFPG, a dynamic Kuhn–Munkres (DKM) dispatcher is designed based on weld line and co-welding robot position information obtained by the wireless sensors, such that robots always have dispatched weld lines in real-time and the lazy robot ratio is 0. Simultaneously, a model-free policy gradient (MFPG) based on reinforcement learning is designed to achieve the energy-optimal motion control for all robots. The optimal lazy robot ratio of the DKM dispatcher and the network convergence of MFPG are theoretically analyzed. Furthermore, the performance of DKM-MFPG is simulated with variant settings of welding scenarios and compared with baseline optimization methods. Compared to the four baselines, DKM-MFPG owns a slight performance advantage within 1% on energy consumption and reduces the average lazy robot ratio by 11.30%, 10.99%, 8.27%, and 10.39%. Full article
(This article belongs to the Special Issue Ship Wireless Sensor)
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