# A Systematic Review of Computer Vision and AI in Parking Space Allocation in a Seaport
## 6 Discussions  
After analyzing the relevant literature, it is clear that various CV and AI applications have successfully been implemented for on-road vehicle parking systems. Sensors play a crucial role in any smart parking system, and therefore, it is recommended to use microelectromechanical sensors due to their low energy consumption, cost-effectiveness, and high performance [45]. Among the different sensors available, ultrasonic and camera sensors are the most commonly used, as they accurately identify parking spaces for vehicles [1; 17; 46]. [PERSON], [PERSON], [PERSON], [PERSON], & [PERSON] (2018) [21] conducted a study where they compared different sensor technologies such as Bluetooth and Wi-Fi with infrared sensors and found that infrared sensors reduce time and CO\({}_{2}\) emissions, making them an efficient choice for smart parking systems. If the sensors effectively collect the required information, it is the software that performs all processing. In various studies, different software solutions such as information management, prediction models, and e-booking models have been discussed for on-road vehicle smart parking systems. [PERSON], [PERSON] et al. (2014) [47] developed a system that used a webpage for booking parking spaces in real-time situations, which was only possible due to effective information management. However, since it uses cloud storage to store data, the risk of cyber-attacks is high. [PERSON], [PERSON], [PERSON] & [PERSON] (2016) [48] proposed an e-booking or reservation model for driverless cars, allowing the driver to reserve a parking space in advance. [PERSON], [PERSON] et al. (2018) [49]developed a smart parking system that can be installed with existing cameras. In their proposed model, data from all cameras are used to compose a final parking matrix, and empty spaces are not colored. Prediction models are another type of software used in smart parking systems. In a survey conducted by [PERSON] & [PERSON]. (2019) [4] on IoT-enabled cities, the importance of embedding sensors in vehicles and the city's infrastructure for smart parking systems was highlighted. The authors analyzed several studies and found that not all smart parking designs are thoughtfully designed; therefore, to achieve more efficiency, smart city planners should opt for conceptual hybrid parking systems. Using the right sensors and software is crucial for the development of an efficient on-road vehicle smart parking system. While various sensors and software solutions have been discussed in the reviewed studies, it is important to choose the most suitable one based on the requirements and limitations of the project. Additionally, smart city planners should consider hybrid parking systems to achieve maximum efficiency. After reviewing the relevant studies on on-road vehicle parking systems, it became imperative to investigate the advancements made in managing seaports. Several papers discussed the digitalization of seaports, including the decision by Malaysia Seaport Development to align with Industrial Revolution 4.0 [33]. The authors examined the advantages and disadvantages of the cyber-physical system named 'SmartPort', which manages container and asset management, among other things. Further research revealed that ports are currently employing AI, ML, and CV to optimize container and crane management and reduce queues at the gate. The Korean Port Logistics Association utilizes a particular model for port service quality. However, to the best of our knowledge, no paper explicitly mentions the use of AI and CV in managing trucks inside the port during container delivery or pickup. Despite several studies on the significance of seaport digitalization, one critical problem remains unaddressed: truck traffic management inside seaports. Studies discussing lane and container allocation fail to consider the port's infrastructure, where narrow lanes near the containers could cause significant delays [50].