# A Systematic Review of Computer Vision and AI in Parking Space Allocation in a Seaport
## 4 Parking Space Allocation in Sea Ports  
With the rise of globalization and the smart city concept, seaport industries are expanding at an unprecedented rate. To increase efficiency and profitability, seaports are increasingly implementing digital technologies [26]. The application of the \"simple shuttle problem\" has been highlighted for distribution problems in seaports [39]. Seaports are more than just places for cargo import and export, they also involve loading and unloading goods, warehousing, storing, shipment, packing, and delivery. Due to the added value of seaports, any delay in the process could lead to significant losses and time consumption. In a detailed study on how Malaysia's seaports developed and embraced IR 4.0, [PERSON] (2021) [33] highlighted the adaptations made by Hamburg Port authorities to accept IR 4.0. The port authorities have coined the term \"SmartPort\" to refer to their adaptation to IR 4.0. The \"SmartPort Logistics\" feature manages internal truck parking areas in the port, and the \"SmartPort Monitor\" enables easy accessibility to all essential data necessary for port optimization. However, the design of a seaport is very compact in nature, and the internal traffic and parking management of trucks remains a significant challenge. Long queues of trucks in seaports are a common problem [24]. The authors have proposed a lane allocation framework to manage truck allocation and traffic. By implementing a truck appointment system and lane allocation planning, the flow of trucks in the seaport could be optimized. The authors have identified four types of trucks in a seaport: those sending loaded containers, those sending empty containers, those taking loaded containers, and those taking empty containers. They have divided the lanes in the port accordingly. At the gate, there are four lanes, and during a given time duration, one lane opens for one type of truck while the other three lanes are open for the remaining type of truck. Optimizing the truck parking system at a seaport could be improved if the storage of different containers is performed more effectively. Researchers have used various models for efficient container storage in seaports. [PERSON] et al. (2012) [40] highlighted the difficulties faced in a multiproduct manufacturing factory in labeling and storing products. The authors used a mixed-integer linear programming model to optimize tank allocation and storage. Similarly, there are several studies on how to solve the supply vessel scheduling problem, also known as the periodic supply vessel planning problem (PSVPP) [41]. Along with many other authors [42], [PERSON] (2018) [41] proposed the use of heuristic algorithms for optimizing container storage systems. All these studies had one thing in common: constraints. Space allocation of containers was based on size, weight, color, and destination. Positive results were seen in several studies, including a case study of the Port of Montreal in Canada [43]. Their objective was to optimize the container terminal, and they proposed a new layout by adding new pathways and some new handling equipment, such as an electric straddle carrier. [PERSON] et al. (2020) [43] successfully achieved their objective by reducing transportation costs and CO\({}_{2}\) emissions. Container storage optimization is an important component of seaport optimization since it has a substantial influence on a port's efficiency and productivity. Furthermore, the truck parking system at a seaport is a crucial aspect that might generate traffic congestion during peak hours. The Port of Hamburg [26] has utilized digitalization to continuously monitor parking spot availability. While the port now employs radar technology to locate ship parking places, they are also attempting to optimize the intermodal traffic produced by trucks and other vehicles. The port employs a variety of sensors to monitor all of its assets, including cranes, trucks, and carriers, allowing it to apply AI and computer vision technology to enhance port operations and traffic management.