Optimizing Seaport Parking with AI and Computer Vision: A Systematic Review

By Dr Silpaja Chandrasekar, PhDReviewed by Susha Cheriyedath, M.Sc.Sep 17 2023

In a paper published in the journal Applied Sciences, researchers explored the application of artificial intelligence (AI) and computer vision (CV) technologies in addressing urban expansion challenges, particularly in optimizing container movement within seaports. A systematic review of existing literature highlighted the significant role of AI and CV in sustainable parking ecosystems. This paper offered valuable insights for enhancing seaport management and smart city development.

Introduction

Urbanization has created challenges and opportunities in various sectors, including housing, transportation, education, health, and the economy. AI and CV technologies have been employed to tackle these issues. The definition of smart cities is crucial in addressing these challenges as it contains elements such as smart mobility. Moreover, seaports encounter congestion and efficiency issues, underscoring the importance of AI and CV for optimizing container transport and parking management. This study explores the potential benefits of AI and CV in seaport parking to improve efficiency and traffic flow by extending the smart city concept to these critical hubs of global trade.

Methodological Approach: Systematic Review Process

The methodology employed for conducting a systematic review is detailed here, which sheds light on its purpose and scope. The systematic review serves as a meticulous and structured examination of existing literature to identify, select, and synthesize relevant research on AI and CV in parking management, ensuring an unbiased and comprehensive summary of available knowledge.

To maintain transparency and rigor, the study adheres rigorously to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. These guidelines guarantee a standardized checklist for transparent reporting of the review process, which encompasses research focus definition, search strategy formulation, study selection, data extraction, and result synthesis. 

The research scope and keywords are defined, with a careful selection of essential terms and phrases, by ensuring the inclusion of pertinent literature. The search and selection process, conducted across multiple platforms, yielded 60 manuscripts related to AI and CV in parking space allocation. These were subjected to rigorous inclusion and exclusion criteria, resulting in the final selection of 50 studies aligned with the research objectives.

The data extraction process was collaborated by addressing the challenges posed by directly related papers, and the process was structured into distinct subtopics for a comprehensive review. This systematic approach achieves the quality, relevance, and timeliness of the studies, ultimately enhancing the robustness of the present research findings.

Utilizing AI and CV for Parking Space Allocation

Numerous studies have explored the integration of AI and CV to enhance parking space management. These technologies collectively contributed to the efficient allocation of parking slots, which include image processing, object detection, machine learning, deep learning algorithms, and real-time monitoring systems. Many examples include the development of smart parking systems by combining image processing and machine learning for seamless entry, exit, and payment processing. Although the application of AI and CV in addressing parking challenges is promising; however, the need for further research and development in areas such as weather conditions and data security in cloud storage is essential for their real-world applications.

Optimizing Parking Space Allocation in Seaports

The adoption of digital technologies to optimize operations is on the rise in seaports that are driven by globalization and smart city concepts. AI and CV help manage truck traffic and container storage efficiently by enhancing overall port productivity and safety. These technologies provide real-time data for traffic management, safety monitoring, and predictive maintenance, ensuring the operation process is efficient and safe.

The careful selection of 50 relevant papers from various academic databases demonstrates the scientific credibility of the present systematic review. The data is a crucial resource by offering valuable insights into parking space distribution algorithms for smart parking systems, which are applicable even in seaports. The research highlights the importance of digitization in global port competitiveness and identifies technologies like AI and CV that can reduce congestion and emissions. It also explores specific AI and CV applications in seaports by providing practical solutions for optimization and sustainability to benefit scholars, policymakers, and port authorities.

Contributions of this paper

The contributions of this paper are as follows:

Identification of Seaport Challenges: This paper highlights the specific challenges faced by seaports by including the narrow lanes between container stacks and heavy-duty truck congestion.

Global Significance of Seaports: It emphasizes the pivotal role of seaports in international trade and their impact on the global economy.

Comprehensive Examination of AI and CV Benefits: It thoroughly analyzes the advantages of AI and CV in creating efficient and sustainable parking systems.

Future Prospects: This paper also highlights potential future research directions and applications for AI and CV in seaport parking management.

Efficiency and Sustainability Potential: The paper argues that AI and CV technologies have the potential to significantly enhance traffic management and space allocation in seaports, leading to efficient and sustainable gains for the global economy.

Conclusion

In summary, this systematic review highlights the pivotal role of AI and CV technologies in addressing seaport management challenges by particularly focusing on transportation and container movement. It emphasizes their potential for efficient and sustainable parking systems, improved traffic management, optimized space allocation, and streamlined container handling. Future research opportunities include real-time AI algorithms, Internet of Things (IoT) sensor integration, and smart port solutions. Overall, this review emphasizes the transformative impact of AI and CV in port management and calls for further innovation in this promising field to enhance seaport operations towards more efficiency, sustainability, and responsiveness to global trade demands.