Enhancing IoT‐Based Smart Public Transport Route Optimization in Maiduguri LGA, Borno State
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Background of the study
Public transport in Maiduguri LGA is a critical component of urban mobility, yet it is often beset by inefficiencies and suboptimal route management. The integration of IoT-based smart systems into public transport operations promises to revolutionize route optimization by leveraging real-time data and advanced analytics. These systems employ GPS, sensors, and communication networks to monitor vehicle movements, passenger loads, and traffic conditions, thereby enabling dynamic route adjustments and improved scheduling (Garba, 2023). Recent research has demonstrated that the implementation of IoT technologies in transport systems can lead to reduced waiting times, improved fuel efficiency, and enhanced passenger satisfaction (Ibrahim, 2024). By collecting and analyzing continuous streams of data, these systems facilitate proactive decision-making that can significantly improve route planning and operational efficiency in urban settings.
In Maiduguri LGA, where public transport plays a vital role in daily commuting, the traditional static route planning methods are inadequate in addressing the challenges of fluctuating traffic patterns and demand variability. IoT-based solutions offer a more adaptive and responsive framework that can optimize routes in real time, ensuring that transport services meet the dynamic needs of the population (Garba, 2023). Moreover, the integration of smart route optimization systems aligns with broader governmental initiatives to modernize urban transportation and enhance service delivery. However, challenges such as data accuracy, network reliability, and the integration of heterogeneous data sources must be addressed to fully realize the potential of these systems (Ibrahim, 2024). This study seeks to explore the application of IoT-based technologies for public transport route optimization in Maiduguri LGA, with a focus on identifying critical success factors, assessing system performance, and proposing strategies to overcome existing challenges. The findings are expected to provide valuable insights that can inform policy decisions and operational practices in urban transport management (Garba, 2023).
Statement of the problem
The public transport system in Maiduguri LGA is frequently hindered by inefficient route planning and unpredictable traffic conditions, leading to extended travel times, increased fuel consumption, and commuter dissatisfaction. Traditional route planning methods, which rely on fixed timetables and pre-determined routes, fail to adapt to real-time changes in traffic patterns and passenger demand. Consequently, public transport operators experience challenges in managing congestion, maintaining schedule reliability, and optimizing resource allocation (Ibrahim, 2024). Although IoT-based route optimization systems have shown potential in other metropolitan areas, their implementation in Maiduguri is limited by technical challenges such as data integration, sensor accuracy, and network instability. In addition, the lack of interoperability among different data sources and the absence of a centralized control mechanism further complicate the issue. The resultant inefficiencies not only compromise the operational performance of public transport but also affect the economic well-being of commuters who rely on these services for daily travel (Garba, 2023). This study intends to investigate the root causes of these inefficiencies and evaluate the potential of IoT-based solutions to dynamically optimize transport routes. By examining the interplay between real-time data, traffic conditions, and route planning algorithms, the research aims to propose a comprehensive framework for enhancing public transport efficiency in Maiduguri LGA. The anticipated outcome is a set of actionable recommendations that address both technological and operational challenges, thereby improving overall service delivery and commuter satisfaction (Ibrahim, 2024).
Objectives of the study
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To analyze the current public transport routing challenges in Maiduguri LGA.
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To assess the effectiveness of IoT-based systems in dynamic route optimization.
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To develop strategic recommendations for improving public transport efficiency.
Research questions
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How can real-time data improve public transport route planning?
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What are the key technological challenges in implementing IoT-based optimization?
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What strategies can enhance the efficiency of public transport operations?
Significance of the study
This study offers critical insights into the deployment of IoT technologies for enhancing public transport route optimization. Its findings will assist transport operators and policymakers in developing adaptive routing strategies that reduce delays and improve commuter satisfaction. The research supports the modernization of urban mobility systems, ultimately contributing to economic efficiency and sustainable transport development (Garba, 2023; Ibrahim, 2024).
Scope and limitations of the study
The study is confined to IoT-based smart public transport route optimization in Maiduguri LGA. Limitations include data integration challenges and variability in sensor performance.
Definitions of terms
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IoT (Internet of Things): A network that connects devices to exchange data in real time.
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Route Optimization: The process of improving travel paths for efficiency and cost-effectiveness.
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Public Transport: Systems and services provided for shared passenger mobility.
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