Design and Implementation of an IoT-Based Smart Traffic Monitoring System for Major Roads in Maiduguri LGA, Borno State
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Background of the study:
Urban traffic congestion is a growing challenge in Maiduguri LGA, significantly affecting commuter safety, travel time, and environmental quality. Traditional traffic monitoring systems, which often rely on manual observation and static cameras, fail to capture real-time data and provide timely alerts about road conditions. An IoT-based smart traffic monitoring system utilizes interconnected sensors, cameras, and data analytics to continuously monitor vehicle flow, congestion levels, and incident occurrences on major roads. This system processes real-time data to provide dynamic insights into traffic patterns, enabling authorities to manage congestion more effectively (Ibrahim, 2023). With the integration of machine learning algorithms, the system can predict congestion trends and alert drivers about potential delays or accidents, thereby enhancing road safety and reducing travel times (Udo, 2024). Moreover, the system can facilitate adaptive traffic signal control, ensuring that intersections operate efficiently during peak hours. The use of IoT technology in traffic management supports proactive decision-making and urban planning by providing a comprehensive overview of traffic conditions. Such an approach not only improves commuter experiences but also contributes to reducing vehicular emissions and energy consumption (Emeka, 2025). The smart traffic monitoring system represents a significant step towards creating a more responsive, data-driven urban transportation network that addresses the evolving needs of Maiduguri’s rapidly growing population.
Statement of the problem:
Major roads in Maiduguri LGA suffer from severe traffic congestion and inefficient management due to outdated monitoring technologies that do not offer real-time data. Traditional traffic monitoring systems, which depend on periodic manual data collection and static cameras, are unable to capture the dynamic nature of urban traffic, leading to delayed responses and inadequate congestion management (Ibrahim, 2023). This results in prolonged travel times, increased fuel consumption, and elevated levels of air pollution. The lack of integrated, automated monitoring tools further impedes the ability of traffic authorities to implement effective traffic control measures. In addition, the absence of real-time alerts for incidents such as accidents or road blockages compromises road safety and hinders prompt emergency responses. Financial and technical constraints have prevented the adoption of modern, IoT-based solutions, leaving the traffic management system fragmented and inefficient (Udo, 2024). Without a comprehensive, data-driven monitoring system, the urban transport network remains vulnerable to unpredictable traffic fluctuations, adversely affecting economic activities and the quality of life for residents (Emeka, 2025). There is an urgent need to develop an IoT-based smart traffic monitoring system that provides continuous, real-time insights and supports proactive management of urban traffic conditions.
Objectives of the study:
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To design an IoT-based system for real-time monitoring of traffic conditions on major roads.
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To evaluate the system’s impact on reducing congestion and improving incident response times.
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To propose recommendations for integrating the system with existing urban traffic management frameworks.
Research questions:
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How effective is the IoT-based traffic monitoring system in capturing real-time traffic data?
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What impact does the system have on reducing congestion and improving commuter safety?
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How can the system be integrated with current traffic management practices to enhance overall urban mobility?
Significance of the study:
This study is significant as it provides a modern, data-driven approach to managing urban traffic congestion. By leveraging IoT technology, the smart traffic monitoring system offers real-time insights and predictive analytics, which can significantly improve road safety, reduce travel times, and optimize traffic flow. The findings will assist policymakers and traffic authorities in developing more effective urban transport strategies and enhancing commuter experiences.
Scope and limitations of the study:
This study is limited to the design, implementation, and evaluation of an IoT-based smart traffic monitoring system on major roads in Maiduguri LGA, Borno State. It does not extend to other transportation systems or regions.
Definitions of terms:
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IoT (Internet of Things): A network of interconnected devices that transmit real-time data.
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Traffic Monitoring System: A system that tracks and analyzes vehicular flow and congestion in real time.
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Adaptive Traffic Control: Technology that adjusts traffic signals based on real-time traffic conditions.
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