Evaluation of IoT-Based Smart Public Transport Management in Sokoto South LGA, Sokoto State
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Background of the Study :
Efficient public transport is vital for urban mobility, and in Sokoto South LGA, Sokoto State, university campuses and urban centers face challenges with congestion, delayed services, and inefficient route management. IoT-based smart public transport management systems have the potential to revolutionize how transport services are monitored and managed by integrating real-time data from vehicles, passenger flow sensors, and traffic monitors. This study aims to evaluate the effectiveness of an IoT-based smart public transport management system in improving service delivery and reducing congestion in Sokoto South LGA (Ibrahim, 2023). The system will utilize GPS tracking and sensor networks installed in buses and on roadways to collect real-time data on vehicle locations, passenger counts, and traffic conditions. This information will be transmitted to a centralized platform that employs advanced analytics and machine learning algorithms to optimize routes, adjust schedules dynamically, and predict maintenance needs. Prior research indicates that smart transport systems can reduce waiting times, enhance reliability, and improve the overall user experience (Olu, 2024). This study will involve field deployment, data collection, and performance evaluation to assess improvements in operational efficiency and commuter satisfaction. The integration of a mobile application will provide real-time updates to passengers, further enhancing the system’s utility. By addressing the challenges of route optimization and real-time monitoring, the proposed system seeks to reduce congestion, lower fuel consumption, and contribute to a more sustainable urban transport environment. The outcomes of this research are expected to inform policymakers and transport authorities about the benefits of IoT-based solutions in public transport management, offering a scalable model for other urban areas facing similar challenges (Adeniyi, 2025).
Statement of the Problem :
Public transport in Sokoto South LGA suffers from chronic inefficiencies, including poorly managed routes, irregular schedules, and delayed services, which contribute to increased congestion and commuter dissatisfaction. Traditional transport management methods rely on manual monitoring and outdated scheduling techniques that fail to adapt to real-time traffic conditions. The absence of an integrated, automated system prevents the timely collection and analysis of data necessary for effective route optimization and service planning. This lack of real-time information leads to suboptimal resource allocation and prolonged wait times, ultimately reducing the efficiency of public transport services. Additionally, the current systems do not provide passengers with real-time updates, further exacerbating commuter frustration. There is a critical need for an IoT-based smart public transport management system that can automate data collection, analyze real-time information, and adjust routes and schedules dynamically. By addressing these challenges, the system can improve service reliability, reduce congestion, and enhance the overall commuter experience. This study seeks to evaluate the performance of such a system in Sokoto South LGA, focusing on improvements in operational efficiency and user satisfaction. Addressing these issues is essential for transforming urban public transport into a more responsive, efficient, and sustainable service, ultimately benefiting both commuters and transport operators (Ibrahim, 2023; Olu, 2024).
Objectives of the Study:
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To implement an IoT-based system for real-time public transport monitoring.
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To optimize transport routes and schedules using data analytics.
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To assess the system’s impact on service efficiency and passenger satisfaction.
Research Questions:
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How effective is the IoT system in improving route management and schedule adherence?
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What are the impacts on commuter wait times and overall satisfaction?
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How can the system be scaled to manage larger urban transport networks?
Significance of the Study :
This study is significant as it evaluates an IoT-based smart public transport management system aimed at reducing congestion and enhancing service efficiency in urban areas. The system’s real-time monitoring and dynamic scheduling capabilities are expected to improve public transport reliability, reduce operational costs, and provide a replicable model for sustainable urban mobility (Adeniyi, 2025).
Scope and Limitations of the Study:
The study is limited to the evaluation of the smart public transport system in Sokoto South LGA, Sokoto State, and does not extend to private or intercity transport services.
Definitions of Terms:
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Smart Public Transport Management: The use of IoT technologies to monitor and optimize public transportation operations.
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Real-Time Monitoring: Continuous data collection and analysis as events occur.
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Predictive Analytics: The use of data, statistical algorithms, and machine learning techniques to forecast future events.
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