Enhancing IoT-Based Smart Public Transport Scheduling in Lokoja LGA, Kogi State
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- NGN 5000
Background of the study:
Urban mobility is a critical component of sustainable city development, yet many cities struggle with inefficient public transport scheduling. In Lokoja LGA, Kogi State, traditional scheduling methods often lead to delayed departures, uneven vehicle distribution, and congestion during peak hours. The integration of Internet of Things (IoT) technology into public transport scheduling systems offers a promising solution by enabling real-time data collection, dynamic route optimization, and adaptive scheduling based on current passenger demand and traffic conditions (Ibrahim, 2023). Smart sensors, GPS tracking, and cloud-based analytics can provide up-to-date information about vehicle location and road conditions. This real-time data can be used to adjust bus schedules dynamically, ensuring that resources are allocated efficiently and that delays are minimized. Furthermore, IoT-based systems facilitate the integration of multiple data streams from traffic cameras, weather sensors, and commuter mobile applications, which collectively enhance the accuracy of predictive analytics. By forecasting demand and traffic flow, the system can preemptively adjust schedules to avoid bottlenecks and ensure smoother operations (Adeniyi, 2024). The implementation of such a system not only improves service reliability but also reduces fuel consumption and operational costs by optimizing vehicle routes. Moreover, increased transparency and timely information can enhance commuter satisfaction and trust in public transport services. The data-driven approach supports long-term strategic planning and urban development, paving the way for smart city initiatives. As Lokoja continues to expand, adopting an IoT-based public transport scheduling system is essential to meet the growing mobility needs and reduce urban congestion. Continuous monitoring and adaptive control provide the foundation for a more resilient and responsive transportation network that is both economically and environmentally sustainable (Udo, 2025). This research, therefore, seeks to explore the design, implementation, and optimization of IoT-based scheduling systems tailored to the unique challenges of Lokoja LGA, with the aim of enhancing public transport efficiency and overall commuter experience.
Statement of the problem:
In Lokoja LGA, public transport scheduling faces significant challenges due to outdated manual systems that are unable to respond promptly to dynamic traffic conditions and fluctuating passenger demands. The current system lacks real-time monitoring capabilities, which often results in buses being dispatched along fixed routes and schedules, irrespective of current road conditions and passenger loads. Consequently, this leads to inefficient vehicle utilization, increased waiting times, and overall commuter dissatisfaction (Ibrahim, 2023). Moreover, the absence of automated data integration means that traffic congestion and unforeseen delays are not accounted for, further exacerbating scheduling inefficiencies. These shortcomings not only elevate operational costs—through wasted fuel and increased labor—but also contribute to environmental pollution. The reactive nature of the existing scheduling framework prevents proactive planning, leaving the transport system ill-prepared to handle peak demand periods or unexpected incidents. Additionally, a lack of communication between the transport management center and commuters leads to uncertainty and frustration among users. Financial limitations and insufficient technical infrastructure compound these challenges, making it difficult to implement effective improvements. Without a robust, IoT-based scheduling system, public transport in Lokoja LGA will continue to struggle with inefficiencies, thereby impeding urban mobility and economic growth (Adeniyi, 2024; Udo, 2025).
Objectives of the study:
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To design an IoT-based system for real-time tracking and adaptive scheduling of public transport vehicles.
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To assess the system’s impact on reducing waiting times and improving route efficiency.
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To recommend strategies for integrating real-time data analytics into existing transport management frameworks.
Research questions:
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How effective is the IoT-based system in providing real-time data for public transport scheduling?
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What improvements in commuter waiting times and route optimization can be observed after implementation?
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How can real-time data integration enhance the overall efficiency of public transport management in Lokoja LGA?
Significance of the study:
This study is significant because it offers a transformative approach to urban mobility by integrating IoT technology into public transport scheduling. The findings will help policymakers and transport authorities reduce congestion, cut operational costs, and improve service reliability. Enhanced scheduling efficiency directly translates to better commuter satisfaction and supports the broader goal of developing smart, sustainable cities.
Scope and limitations of the study:
This study is limited to the design, implementation, and evaluation of an IoT-based public transport scheduling system in Lokoja LGA, Kogi State. It does not extend to other urban transportation solutions or geographic regions.
Definitions of terms:
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IoT (Internet of Things): A network of interconnected devices that collect and exchange real-time data.
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Adaptive Scheduling: Dynamic adjustment of transport schedules based on real-time data.
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Real-Time Data Analytics: The immediate processing and analysis of data as it is collected.
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