Exploring the Role of AI-Based Computer Vision in University Parking Management: A Case Study of University of Maiduguri (Maiduguri LGA, Borno State)
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Background of the Study
Parking management has become an increasingly important issue for universities, especially as campus populations grow and available parking spaces become more limited. Traditional methods of parking management, such as manual monitoring or basic ticketing systems, are often inefficient, prone to errors, and fail to optimize space utilization (Mohammed et al., 2024). AI-based computer vision systems, which use cameras and image recognition technology to monitor parking lots and analyze vehicle occupancy, offer a more automated and intelligent solution to these challenges (Suleiman & Zubair, 2025). These systems can detect available parking spaces, monitor unauthorized parking, and even guide drivers to open spaces in real-time, thereby improving parking efficiency and user experience (Aliyu et al., 2023).
The University of Maiduguri, located in Maiduguri LGA, Borno State, faces significant parking management challenges due to its large student population and limited parking space. By implementing AI-based computer vision technologies, the university could streamline parking operations, optimize space usage, and enhance campus mobility (Garba & Tukur, 2023). This study seeks to investigate the potential of AI-based computer vision in improving parking management at the University of Maiduguri, with a focus on its impact on efficiency, convenience, and resource utilization.
Statement of the Problem
The University of Maiduguri's parking system is currently inefficient, resulting in overcrowding, long search times for parking spaces, and unauthorized parking. Traditional methods of managing parking are time-consuming and do not optimize the use of available space. AI-based computer vision systems present a promising solution, but their effectiveness and feasibility in improving parking management at the university need to be explored further.
Objectives of the Study
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To design and implement an AI-based computer vision system for parking management at the University of Maiduguri.
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To evaluate the impact of the AI-based system on parking efficiency, space utilization, and user satisfaction at the university.
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To assess the feasibility of implementing AI-based parking management systems in Nigerian universities.
Research Questions
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How does the AI-based computer vision system improve parking efficiency and space utilization at the University of Maiduguri?
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What impact does the AI-based system have on user satisfaction and convenience in the parking process?
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How feasible is the implementation of AI-based parking management systems in Nigerian universities?
Significance of the Study
This research will provide valuable insights into the potential of AI-based computer vision in addressing parking challenges at universities. The findings could lead to more efficient and convenient parking solutions, which can be applied to other educational institutions in Nigeria and globally.
Scope and Limitations of the Study
This study will focus on the implementation and evaluation of AI-based computer vision for parking management at the University of Maiduguri, located in Maiduguri LGA, Borno State. The study will be limited to the analysis of parking efficiency and user satisfaction, excluding other aspects of campus management.
Definitions of Terms
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AI-Based Computer Vision: A field of AI that enables computers to interpret and analyze visual information from the world, often used in applications like image recognition and automated monitoring.
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Parking Management: The process of organizing, monitoring, and optimizing the use of parking spaces in a given area.
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Space Utilization: The measure of how effectively parking spaces are used, typically in terms of occupancy rates and efficiency.
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