In an era where urban mobility is increasingly challenged by rising car usage and population density, a recent study led by Ayodeji Okubanjo from Olabisi Onabanjo University has proposed an innovative solution to alleviate traffic congestion in Nigeria. The research, published in the journal “ITEGAM-JETIA” (International Journal of Emerging Technologies in Engineering and Management), focuses on leveraging emerging technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) to enhance traffic management at critical road intersections.
The study identifies a pressing issue in many emerging nations, particularly in Nigeria, where traditional traffic control measures such as traffic lights and wardens often fall short. Okubanjo highlights the challenges faced by these systems: “Stress, public anger, and rash traffic signal judgments restrict the effectiveness of these tactics, resulting in delayed mobility and decreased transit times.” This inefficiency not only frustrates commuters but also contributes to broader climate challenges, underscoring the necessity for a more adaptive approach to urban traffic management.
The proposed model introduces a low-cost IoT traffic surveillance system designed specifically for a closed campus in Nigeria. By providing real-time traffic updates, this system aims to significantly improve vehicle mobility during peak hours, addressing the needs of the academic community and potentially extending its benefits to other urban areas. The integration of AI and neural networks into this system could also facilitate smarter decision-making processes, allowing for dynamic traffic management that adapts to current conditions.
The implications of this research extend beyond just traffic flow improvements. For technology companies, especially those in the IoT and AI sectors, this presents a commercial opportunity to develop and deploy solutions tailored to urban mobility challenges. Furthermore, local governments and municipalities could benefit from investing in such technologies, potentially leading to reduced congestion, lower emissions, and enhanced public satisfaction.
As urban populations continue to grow, the need for innovative traffic management solutions becomes increasingly critical. Okubanjo’s work highlights a path forward, suggesting that with the right technological investments, cities in Sub-Saharan Africa can create a more sustainable and efficient future for urban mobility. The integration of IoT and AI into traffic systems not only addresses immediate congestion issues but also sets the stage for smarter, greener cities.
