Optimization of IoT-Based Transport Management Systems for University Shuttle Services: A Case Study in Minna LGA, Niger State
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Background of the Study :
Efficient transportation is a cornerstone of effective campus management, particularly in large universities where shuttle services are critical for student mobility. In Minna LGA, Niger State, university shuttle services often face challenges such as route inefficiencies, delays, and high operational costs due to outdated management systems. The advent of IoT technology offers an opportunity to optimize transport management by providing real-time tracking, route optimization, and predictive maintenance. This study aims to optimize an IoT-based transport management system specifically for university shuttle services. The proposed system will incorporate GPS tracking, vehicle sensors, and communication modules to monitor shuttle location, speed, and passenger load continuously. Data collected will be transmitted to a centralized platform, where advanced algorithms will analyze the information to dynamically adjust routes, optimize schedules, and predict potential maintenance issues before they lead to breakdowns. The system is expected to reduce travel times, lower fuel consumption, and improve overall service reliability. Additionally, a mobile application will be developed to provide students with real-time shuttle status updates, estimated arrival times, and route changes, enhancing commuter experience. Prior research has indicated that IoT-based transport management can significantly improve efficiency and user satisfaction in public transit systems (Ibrahim, 2023). By adapting these technologies to the context of university shuttle services in Minna LGA, this study seeks to provide a scalable and cost-effective solution that addresses the unique challenges faced by educational institutions in resource-limited settings. The integration of real-time analytics and cloud-based data management will further ensure that the system remains responsive to changing traffic patterns and operational demands (Olu, 2024; Adeniran, 2025).
Statement of the Problem :
University shuttle services in Minna LGA currently suffer from inefficiencies such as unoptimized routes, delayed schedules, and poor vehicle maintenance, all of which contribute to increased operational costs and student dissatisfaction. Traditional management methods lack real-time data and dynamic response capabilities, making it difficult to adapt to fluctuating traffic conditions and unexpected breakdowns. The absence of a centralized monitoring system hinders effective communication between drivers, administrators, and students, resulting in frequent delays and route deviations. Additionally, manual scheduling methods are prone to errors and are not scalable as student populations grow. These challenges underscore the need for an IoT-based transport management system that can continuously monitor shuttle operations and provide actionable insights to improve efficiency. The proposed solution aims to leverage real-time tracking and data analytics to optimize routes, adjust schedules dynamically, and predict maintenance needs, thereby reducing downtime and improving service reliability. Addressing these issues is essential for enhancing the overall transportation experience for university students, reducing costs, and ensuring that shuttle services operate smoothly and efficiently. The study will focus on developing a system that integrates seamlessly with existing university infrastructure and is user-friendly for both administrators and students (Ibrahim, 2023; Olu, 2024).
Objectives of the Study:
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To design an IoT-based transport management system for real-time shuttle tracking and route optimization.
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To develop algorithms for dynamic schedule adjustments and predictive maintenance.
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To evaluate the system’s impact on operational efficiency and commuter satisfaction.
Research Questions:
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How can IoT technology optimize university shuttle routes and schedules?
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What predictive maintenance strategies can be implemented to reduce shuttle downtime?
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How does the system improve overall shuttle service reliability and user satisfaction?
Significance of the Study :
This study is significant as it develops an IoT-based transport management system that enhances the efficiency of university shuttle services. By optimizing routes, scheduling, and maintenance, the system will reduce operational costs and improve the commuting experience for students. The model can serve as a blueprint for similar institutions aiming to leverage IoT for better transportation management (Adeniran, 2025).
Scope and Limitations of the Study:
The study is limited to the design, implementation, and evaluation of an IoT-based transport management system for university shuttle services in Minna LGA, Niger State, and does not extend to public transportation systems outside the university context.
Definitions of Terms:
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Transport Management System: A system that optimizes the planning, execution, and monitoring of transportation operations.
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IoT (Internet of Things): A network of interconnected devices that exchange data for improved system performance.
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Predictive Maintenance: The use of data analytics to predict equipment failures before they occur.
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