Evaluation of IoT‐Based Smart Intelligent Bus Scheduling for University Shuttle Services in Maiduguri LGA, Borno State
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- NGN 5000
Background of the study
University shuttle services in Maiduguri LGA are critical for facilitating the daily commute of students and staff. However, traditional bus scheduling systems, which rely on static timetables and manual coordination, often result in inefficiencies such as delays, overcrowding, and suboptimal route utilization. IoT-based smart intelligent bus scheduling systems represent an innovative solution that leverages real-time data, GPS tracking, and predictive analytics to optimize shuttle services. These systems continuously monitor bus locations, passenger loads, and traffic conditions to dynamically adjust schedules and routes (Garba, 2023). The integration of IoT technology in bus scheduling enables university transport managers to improve service reliability and operational efficiency while reducing fuel consumption and environmental impact (Ibrahim, 2024). Moreover, the system’s capacity to analyze historical and real-time data facilitates the identification of peak travel periods and demand patterns, which in turn supports more effective resource allocation. In a rapidly growing academic environment such as Maiduguri LGA, where the demand for shuttle services is high, the implementation of IoT-based scheduling is critical for ensuring timely and efficient transportation. However, challenges related to infrastructure, data integration, and cybersecurity must be addressed to fully realize the benefits of this technology (Garba, 2023). This study aims to evaluate the performance of IoT-based smart intelligent bus scheduling systems in university shuttle services, focusing on their impact on reducing wait times, optimizing routes, and enhancing overall commuter satisfaction.
Statement of the problem
University shuttle services in Maiduguri LGA face chronic inefficiencies due to outdated scheduling systems that do not adapt to real-time traffic and passenger demand fluctuations. Static timetables often lead to long waiting times, overcrowded buses, and underutilized routes, which collectively contribute to commuter dissatisfaction and increased operational costs (Ibrahim, 2024). Despite the potential of IoT-based solutions to transform bus scheduling through real-time monitoring and dynamic route adjustment, their implementation is fraught with challenges. Key issues include insufficient network infrastructure, data interoperability problems among various IoT devices, and vulnerabilities in cybersecurity that may compromise sensitive operational data (Garba, 2023). Moreover, the lack of adequate training for personnel in managing and interpreting real-time data further exacerbates these challenges, undermining the system’s potential effectiveness. The failure to implement an adaptive scheduling system results in inefficient resource allocation and a diminished quality of service for university commuters. This study seeks to identify the operational and technical barriers that hinder the effective deployment of IoT-based bus scheduling systems and to propose strategies to overcome these obstacles. The research will examine how real-time data can be harnessed to optimize shuttle routes and schedules, thereby enhancing service reliability and reducing operational inefficiencies (Ibrahim, 2024).
Objectives of the study
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To assess the effectiveness of IoT-based scheduling in optimizing bus routes and reducing wait times.
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To identify technical and operational challenges in implementing the system.
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To recommend strategies for enhancing system reliability and user satisfaction.
Research questions
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How does real-time data improve bus scheduling efficiency?
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What are the main challenges in deploying IoT-based scheduling systems?
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How can system integration be optimized for better performance?
Significance of the study
This study is significant for advancing the efficiency of university shuttle services by leveraging IoT-based scheduling systems. The findings will provide actionable insights for transport managers and policymakers, enhancing commuter satisfaction and operational efficiency while reducing costs and environmental impact (Garba, 2023; Ibrahim, 2024).
Scope and limitations of the study
The study is limited to IoT-based intelligent bus scheduling for university shuttle services in Maiduguri LGA. Limitations include network infrastructure and data security issues.
Definitions of terms
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IoT (Internet of Things): A network of interconnected devices that share real-time data.
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Bus Scheduling: The process of planning and organizing bus routes and timetables.
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Dynamic Routing: The real-time adjustment of routes based on current conditions.
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