AI-Powered Intelligent Seaport Mobility: Enhancing Container Drayage Efficiency through Computer Vision and Deep Learning

Author:

Lee Hoon1ORCID,Chatterjee Indranath23ORCID,Cho Gyusung4ORCID

Affiliation:

1. Logistics System Institute, Total Soft Bank Ltd., Busan 48002, Republic of Korea

2. Department of Computer Engineering, Tongmyong University, Busan 48520, Republic of Korea

3. School of Technology, Woxsen University, Hyderabad 502345, India

4. Department of Port Logistics System, Tongmyong University, Busan 48520, Republic of Korea

Abstract

The rapid urbanization phenomenon has introduced multifaceted challenges across various domains, including housing, transportation, education, health, and the economy. This necessitates a significant transformation of seaport operations in order to optimize smart mobility and facilitate the evolution of intelligent cities. This conceptual paper presents a novel mathematical framework rooted in deep learning techniques. Our innovative model accurately identifies parking spaces and lanes in seaport environments based on crane positions, utilizing live Closed-Circuit Television (CCTV) camera data for real-time monitoring and efficient parking space allocation. Through a comprehensive literature review, we explore the advantages of merging artificial intelligence (AI) and computer vision (CV) technologies in parking facility management. Our framework focuses on enhancing container drayage efficiency within seaports, emphasizing improved traffic management, optimizing parking space allocation, and streamlining container movement. The insights from our study provide a foundation that could have potential implications for real-world applications. By integrating cutting-edge technologies, our proposed framework not only enhances the efficiency of seaport operations, but also lays the foundation for sustainable and intelligent seaport systems. It signifies a significant leap toward the realization of intelligent seaport operations, contributing profoundly to the advancement of urban logistics and transportation networks. Future research endeavors will concentrate on the practical implementation and validation of this pioneering mathematical framework in real-world seaport environments. Additionally, our work emphasizes the crucial need to explore further applications of AI and CV technologies in seaport logistics, adapting the framework to address the evolving urbanization and transportation challenges. These efforts will foster continuous advancements in the field, shaping the future of intelligent seaport operations.

Funder

Ministry of Oceans and Fisheries

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference61 articles.

1. Bernacki, D., and Lis, C. (2021). Investigating the sustainable impact of seaport infrastructure provision on maritime component of supply chain. Energies, 14.

2. A smart, efficient, and reliable parking surveillance system with edge artificial intelligence on IoT devices;Ke;IEEE Trans. Intell. Transp. Syst.,2020

3. A communications-oriented perspective on traffic management systems for smart cities: Challenges and innovative approaches;Djahel;IEEE Commun. Surv. Tutor.,2014

4. Smart parking guidance, monitoring and reservations: A review;Kotb;IEEE Intell. Transp. Syst. Mag.,2017

5. World Bank (2023, October 06). The Container Port Performance Index 2022: A Comparable Assessment of Performance Based on Vessel Time in Port. Available online: http://hdl.handle.net/10986/39824.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3