Artificial Intelligence Vision-Based Monitoring System for Ship Berthing

Kim, Hanguen; Kim, Dong-Hoon; Park, Byeolteo; Lee, Seung-Mok

doi:10.1109/access.2020.3045487

Cited by 29 publications

(8 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Port Structuresmentioning

confidence: 99%

“…164 The applications of vision-based monitoring in a port facility are not limited to monitoring the condition of port infrastructure but can be extended to monitor the berthing of ships. 165 Furthermore, the condition of concrete, steel, and geotechnical structures in port complexes can be assessed through vibrational parameters. However, one of the major issues in performing vibration-based SHM in general port structures is the change in the natural frequency of the structure with the fluctuation of the water level.…”

Section: General Port Structuresmentioning

confidence: 99%

See 1 more Smart Citation

Structural health monitoring of inland navigation structures and ports: a review on developments and challenges

Negi

Kromanis

Dorée

et al. 2023

Structural Health Monitoring

View full text Add to dashboard Cite

Inland navigation structures (INS) facilitate transportation of goods in rivers and canals. Transportation of goods over waterways is more energy efficient than on roads and railways. INS, similar to other civil structures, are aging and require frequent condition assessment and maintenance. Countries, in which INS are important to their economies, such as the Netherlands and the United States, allocate significant budgets for maintenance and renovation of exiting INS, as well as for building new structures. Timely maintenance and early detection of a change to material or geometric properties (i.e., damage) can be supported with the structural health monitoring (SHM), in which monitored data, such as load, structural response, environmental actions, are analyzed. Huge scientific efforts are realized in bridge SHM, but when it comes to SHM of INS, the efforts are significantly lower. Therefore, the SHM community has opportunities to develop new solutions for SHM of INS and convince asset owners of their benefits. This review article, first, articulates the need to keep INS safe to use and fit for purpose, and the challenges associated with it. Second, it defines and reviews sensors, sensing technologies, and approaches for SHM of INS. Then, INS and their components, including structures in ports, are identified, described, and illustrated, and their monitoring efforts are reviewed. Finally, the review article emphasizes the added value of SHM systems for INS, concludes on the current achievements, and proposes future trajectories for SHM of INS and ports.

show abstract

Section: Port Structuresmentioning

confidence: 99%

Section: General Port Structuresmentioning

confidence: 99%

Structural health monitoring of inland navigation structures and ports: a review on developments and challenges

Negi

Kromanis

Dorée

et al. 2023

Structural Health Monitoring

View full text Add to dashboard Cite

show abstract

“…In [21], a shore-based assistance system based on cameras is proposed that is also capable of detecting partly obscured vessels in multi-ship situations (e.g., tug-supported berthing). Therefore, the distance of objects to the quay wall is determined by an artificial intelligence vision-based monitoring system (AVMS) consisting of a camera, a Differential Global Positioning System (DGPS), and an Inertial Measurement Unit (IMU) sensor.…”

Section: Related Workmentioning

confidence: 99%

Berthing Assistant System Using Reference Points

Mentjes

Wiards

Feuerstack

2022

JMSE

View full text Add to dashboard Cite

With more goods to be transported oversea, traffic and vessels’ dimensions increase while berthing areas merely remain constant and thus challenge ship masters and pilots to maneuver in small basins with dense traffic even in bad weather situations. Too fast approaches or steep angles of attack result in damages to fenders, quay walls, or even impact the hull structure. We propose a shore-based, vessel-independent berthing assistant system to support sailors by Reference Points that are aligned to a quay’s meter markings and identify the precise berthing location by measuring distance and approach speed. For this purpose, we define the concept of a Berthing Support Area (BSA), which specifies an area in which, subject to constraints, safe berthing is provided. Within this area there are Reference Points, perpendicular distance measurements at arbitrary positions, which are implemented with a set of LiDAR sensors that have been integrated into the quay wall. In a test campaign with a vessel equipped with DGPS sensors, we sailed seven different maneuvers and evaluated the precision and the accuracy of the Reference Points for speed and distance measurements.

show abstract

“…Because it has such a large field of view, the AVMS can measure the distance between ship and berth regardless of ship size. It also gives the pilot a real-time picture of the ship approaching the berth, allowing for safe berthing (H. Kim et al, 2020). A ML approach was used in Lee et al's analysis, which resulted in predictions based on berthing velocity data (Li et al, 2019).…”

Section: Other Applicationsmentioning

confidence: 99%

The Impacts of the Applications of Artificial Intelligence in Maritime Logistics

Aylak¹

2022

European Journal of Science and Technology

View full text Add to dashboard Cite

This study aims to identify current approaches in the usage of Artificial Intelligence (AI) methods for solving shipping problems. Recent advances in AI are being examined, and the way it is adapted to maritime logistics is reviewed. In this study, 66 papers dealing with AI in the maritime industry are reviewed bibliometrically. Research data were primarily sourced from databases of IEEE Xplore, Web of Science, ScienceDirect (Elsevier), Sciences Citation Index, Google Scholar, Springer, and journals. Selected papers are categorized and classified, and the outcomes of some noteworthy publications are discussed in detail. A comprehensive assessment is also presented, which highlights research gaps and forecasts future research orientations. Two possible areas in the maritime industry are proposed for further research using AI capabilities. Predictive analysis is the first domain, followed by energy efficiency optimization. In addition, Machine Learning (ML) and Operations Research (OR) have fostered a growing interest in automating the learning of heuristics to solve optimization problems to avoid the need for expensive and inefficient human labour to create highly specialized heuristics. Future research can take advantage of these new ML approaches to address Maritime Logistics problems utilizing the ever-increasing amount of data available. Future research on maritime logistics can also develop learning models based on the identified gaps.

show abstract

Artificial Intelligence Vision-Based Monitoring System for Ship Berthing

Cited by 29 publications

References 14 publications

Structural health monitoring of inland navigation structures and ports: a review on developments and challenges

Structural health monitoring of inland navigation structures and ports: a review on developments and challenges

Berthing Assistant System Using Reference Points

The Impacts of the Applications of Artificial Intelligence in Maritime Logistics

Contact Info

Product

Resources

About