Background of the study:
Efficient transportation scheduling is essential for ensuring smooth mobility and reducing congestion in urban areas. In Sokoto North LGA, transportation systems are often plagued by inefficiencies due to manual scheduling and outdated planning methods. IoT-based smart transportation scheduling systems offer a modern solution by integrating real-time data collection, vehicle tracking, and predictive analytics to optimize route planning and scheduling (Emeka, 2023). These systems continuously gather data from GPS-enabled devices and traffic sensors, enabling authorities to adjust schedules based on current traffic conditions and passenger demand (Ibrahim, 2024). By dynamically adjusting bus or shuttle schedules, the system can minimize waiting times, reduce fuel consumption, and improve overall service reliability. Furthermore, the integration of mobile applications allows commuters to receive real-time updates on vehicle arrival times, enhancing user satisfaction and reducing uncertainty (Aminu, 2025). The automated scheduling system also supports proactive maintenance by identifying patterns in vehicle performance and usage. This smart approach not only streamlines transportation operations but also contributes to environmental sustainability by reducing emissions through optimized route planning. As urban mobility challenges intensify, the deployment of IoT-based scheduling systems is critical for transforming transportation services and promoting efficient resource use. This study focuses on optimizing transportation scheduling in Sokoto North LGA, aiming to enhance service quality and operational efficiency.
Statement of the problem:
Transportation systems in Sokoto North LGA suffer from inefficient scheduling practices that lead to irregular service, long waiting times, and increased fuel consumption (Emeka, 2023). Traditional manual scheduling methods fail to adapt to real-time changes in traffic and passenger demand, resulting in congestion and delays that negatively impact commuters and increase operational costs. The lack of a dynamic, data-driven approach means that vehicles are often underutilized during off-peak periods and overwhelmed during rush hours, exacerbating urban mobility challenges. Furthermore, the absence of integrated communication between transportation providers and commuters limits the ability to make informed decisions. Financial constraints and limited technological integration hinder the modernization of the scheduling system, leaving the transportation network fragmented and inefficient (Ibrahim, 2024). Without an automated, real-time scheduling system, the region continues to experience inefficiencies that reduce service quality and contribute to environmental degradation. Implementing an IoT-based solution is imperative to streamline scheduling, optimize resource utilization, and enhance commuter experience (Aminu, 2025).
Objectives of the study:
To design an IoT-based transportation scheduling system that adjusts routes and timings in real time.
To evaluate the system’s impact on reducing waiting times and improving vehicle utilization.
To propose integration strategies with existing urban transport management frameworks.
Research questions:
How effective is the IoT-based scheduling system in optimizing vehicle routes and timings?
What improvements in service reliability and fuel efficiency can be observed after system implementation?
How can the system be integrated with current transportation management practices to enhance urban mobility?
Significance of the study:
This study is significant as it provides a modern, data-driven solution to address transportation inefficiencies in Sokoto North LGA. By optimizing scheduling and route planning, the IoT-based system can reduce congestion, enhance commuter satisfaction, and contribute to environmental sustainability through reduced emissions. The research offers valuable insights for urban planners and transport authorities.
Scope and limitations of the study:
This study is limited to the design, implementation, and evaluation of an IoT-based smart transportation scheduling system in Sokoto North LGA, Sokoto State. It does not extend to other urban mobility systems or regions.
Definitions of terms:
IoT (Internet of Things): A network of interconnected devices that exchange real-time data.
Transportation Scheduling System: A system that organizes and optimizes transit routes and timings.
Smart System: A technology-enhanced system that automates decision-making based on real-time analytics.
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