Young Researcher Paper Award 2023
🥇Winners

Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語

Template
English

Publisher
 MYU K.K.
 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.


MYU Research

(proofreading and recording)


MYU K.K.
(translation service)


The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 35, Number 9(3) (2023)
Copyright(C) MYU K.K.
pp. 3429-3440
S&M3402 Research Paper of Special Issue
https://doi.org/10.18494/SAM4474
Published: September 29, 2023

Effect of Ship Motion Prediction Model on Navigational Safety [PDF]

Hyun Soo Choi, Jun Hyuk Jang, and Young Hoon Yang

(Received April 27, 2023; Accepted September 15, 2023)

Keywords: motion prediction model, navigational safety, user satisfaction, system usability scale

In this study, the effect of the motion prediction model (MPM), which is a ship behavior prediction model that predicts and provides short-term motion by analyzing ship location information and motion characteristics in real time, on navigational safety was studied. The electronic chart system (ECS) was installed with the MPM on a ship to connect with sensors such as those of the global positioning system (GPS), automatic identification system (AIS) plug, and real-time kinematic (RTK) for logging the real-time location and dynamic information. The MPM predicts the future motion and position of a ship by calculating the logging data, and it was verified that the motion of the ship predicted by the MPM and the actual navigation were very similar. In this study, the nondimensionalized length over all (LOA) was analyzed and found to have an average of 0.0713, confirming that the value predicted by motioning an actual operation was very accurate. In addition, as a result of the user satisfaction survey of the MPM, the adjective rating scale defined by the system usability scale was evaluated to be good, which was verified as convenient to use. In the case of the effectiveness analysis of the MPM by an expert group, it was found that 56.17% of the maritime accident factors alleviated the risk by 80% and that 20.8% of the factors alleviated the risk by 100%. Through this study, it was found that the result of analyzing the movement of individual ships and predicting their motion is an important impact factor for preventing ship collisions. In the future, the MPM is expected to enhance the operational safety of ships operated by self-pilotage, such as cargo ferries and passenger ships, which are less regulated by governments.

Corresponding author: Jun Hyuk Jang


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Hyun Soo Choi, Jun Hyuk Jang, and Young Hoon Yang , Effect of Ship Motion Prediction Model on Navigational Safety, Sens. Mater., Vol. 35, No. 9, 2023, p. 3429-3440.



Forthcoming Regular Issues


Forthcoming Special Issues

Applications of Novel Sensors and Related Technologies for Internet of Things
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)
Call for paper


Special Issue on Advanced Data Sensing and Processing Technologies for Smart Community and Smart Life
Guest editor, Tatsuya Yamazaki (Niigata University)
Call for paper


Special Issue on Advanced Sensing Technologies and Their Applications in Human/Animal Activity Recognition and Behavior Understanding
Guest editor, Kaori Fujinami (Tokyo University of Agriculture and Technology)
Call for paper


Special Issue on International Conference on Biosensors, Bioelectronics, Biomedical Devices, BioMEMS/NEMS and Applications 2023 (Bio4Apps 2023)
Guest editor, Dzung Viet Dao (Griffith University) and Cong Thanh Nguyen (Griffith University)
Conference website
Call for paper


Special Issue on Piezoelectric Thin Films and Piezoelectric MEMS
Guest editor, Isaku Kanno (Kobe University)
Call for paper


Special Issue on Advanced Micro/Nanomaterials for Various Sensor Applications (Selected Papers from ICASI 2023)
Guest editor, Sheng-Joue Young (National United University)
Conference website
Call for paper


Copyright(C) MYU K.K. All Rights Reserved.