# A Systematic Review of Computer Vision and AI in Parking Space Allocation in a Seaport
## 1 Introduction  
Urbanization has brought about numerous opportunities and challenges in various sectors, such as housing, transportation, education, health, and the economy, as highlighted by [PERSON] et al. (2020) [1]. These opportunities and challenges have led to rapid changes in human behavior. To address the challenges, artificial intelligence (AI) and computer vision (CV) tools have been implemented in fields such as health, education, housing, and transportation. The Oxford Learner's Dictionary defines AI as \"the study and development of computer systems that can copy intelligent human behavior\" [2]. Hence, the need of the hour is a machine that can replicate human intelligence to solve various problems. A review study on smart cities by [PERSON] (2019) [3] suggests that the term smart city has been described as a digital city, information city, sensing city, and more. According to the review, a smart city comprises six main elements: smart economy, smart mobility, smart environment, smart people, smart living, and smart governance. Among all elements,smart mobility is a crucial component of a smart city. In designing sustainable and effective transportation systems in a smart city, the increasing number of automobiles poses a challenge. Traffic management and parking space allocation become problematic. Hence, smart traffic surveillance and parking space allotment systems have been introduced, as highlighted by [PERSON] et al. (2020) [1]. A survey by [PERSON] et al. (2019) [4] on smart parking indicates that it takes approximately 107 h per year to find a parking spot in New York City. However, with technological advancements, on-road traffic can be managed, and space can be allocated in random parking areas. For a city to be truly'smart', all areas must be well-developed and equipped with technology. Thus, this study focuses on the need for AI and CV in seaports. The transportation of containers between storage spaces and cargo ships is a significant challenge in any seaport. The lanes between the stacks of containers are narrow, and heavy-duty trucks often cause traffic congestion. With globalization and the increasing import and export of goods, seaports have become busier day by day [4; 5]. Therefore, optimizing the space allocation in seaports using AI and CV techniques can improve overall efficiency. Smart cities have arisen as a solution to these difficulties, utilizing technologies such as AI and CV to improve people's quality of life. Despite substantial progress in smart city development, the primary focus has been on upgrading city transportation systems. Smart city technology, on the other hand, must be expanded to encompass seaports, which are key components of the global economy. Seaports play an important role in the transportation of products, and optimizing space allocation within them can have considerable efficiency and sustainability benefits [6]. As a result, the purpose of this research is to investigate the use of AI and CV techniques in seaport parking management and provide a thorough knowledge of their potential benefits. In contrast to the development of smart cities, which often focuses on enhancing transportation systems inside urban regions, this study investigates the potential of AI and CV as tools for optimizing traffic management and space allocation at seaports [7]. This study aims to shed light on the benefits of AI and CV in managing seaport parking to streamline space allocation and traffic flow. Seaports stand as critical nodes in the global economy, facilitating the movement of goods and contributing significantly to international trade [8]. However, the efficient operation of seaports is beset by a unique set of challenges, many of which revolve around parking space allocation and traffic management. In this study, we delve into these seaport-specific challenges, shedding light on their urgency and relevance to our study. 1.