Smart Traffic Management System.
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| Title: | Smart Traffic Management System. |
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| Authors: | PRIYA, V. SHANMUGA, P., MADHANKUMAR |
| Source: | International Scientific Journal of Engineering & Management; Oct2025, Vol. 4 Issue 10, p1-10, 10p |
| Subject Terms: | ARTIFICIAL intelligence, INTERNET of things, TRAFFIC engineering, TRAFFIC flow, SUSTAINABILITY, CITY traffic, REAL-time computing, MACHINE learning |
| Abstract: | The increasing urban population and rapid growth in the number of vehicles have created significant challenges in managing urban traffic efficiently. Traditional traffic management systems, based on pre-timed signals and static infrastructure, often fail to adapt to real-time traffic fluctuations, leading to frequent congestion, delays, road accidents, and increased air pollution. In response to these challenges, the Smart Traffic Management System (STMS) presents a modern, technology-driven solution aimed at improving the efficiency, safety, and sustainability of urban transportation networks. The proposed STMS integrates advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and cloud computing to monitor, analyze, and control traffic flow in real-time. IoT-enabled sensors, cameras, and GPS devices installed at key traffic intersections and on vehicles gather real-time data on traffic density, vehicle speed, road conditions, and environmental factors. This data is transmitted to a centralized processing unit, where intelligent algorithms analyze traffic patterns and make dynamic adjustments to traffic signal timings based on current demand. Furthermore, the system incorporates predictive analytics to anticipate congestion and suggest alternate routes to drivers via mobile applications or smart navigation systems. Emergency vehicle prioritization, pedestrian safety monitoring, and integration with public transportation systems are also key features of the system, contributing to a more inclusive and responsive traffic ecosystem. The implementation of a Smart Traffic Management System has the potential to significantly reduce travel time, fuel consumption, and greenhouse gas emissions, while also improving road safety and commuter experience. Additionally, the system's scalability and adaptability make it suitable for deployment in cities of varying sizes and complexities. This paper explores the architecture, functionalities, implementation strategies, and benefits of STMS, while also addressing the potential challenges such as data privacy, infrastructure costs, and the need for policy support. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
Nájsť tento článok vo Web of Science | Abstract: | The increasing urban population and rapid growth in the number of vehicles have created significant challenges in managing urban traffic efficiently. Traditional traffic management systems, based on pre-timed signals and static infrastructure, often fail to adapt to real-time traffic fluctuations, leading to frequent congestion, delays, road accidents, and increased air pollution. In response to these challenges, the Smart Traffic Management System (STMS) presents a modern, technology-driven solution aimed at improving the efficiency, safety, and sustainability of urban transportation networks. The proposed STMS integrates advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and cloud computing to monitor, analyze, and control traffic flow in real-time. IoT-enabled sensors, cameras, and GPS devices installed at key traffic intersections and on vehicles gather real-time data on traffic density, vehicle speed, road conditions, and environmental factors. This data is transmitted to a centralized processing unit, where intelligent algorithms analyze traffic patterns and make dynamic adjustments to traffic signal timings based on current demand. Furthermore, the system incorporates predictive analytics to anticipate congestion and suggest alternate routes to drivers via mobile applications or smart navigation systems. Emergency vehicle prioritization, pedestrian safety monitoring, and integration with public transportation systems are also key features of the system, contributing to a more inclusive and responsive traffic ecosystem. The implementation of a Smart Traffic Management System has the potential to significantly reduce travel time, fuel consumption, and greenhouse gas emissions, while also improving road safety and commuter experience. Additionally, the system's scalability and adaptability make it suitable for deployment in cities of varying sizes and complexities. This paper explores the architecture, functionalities, implementation strategies, and benefits of STMS, while also addressing the potential challenges such as data privacy, infrastructure costs, and the need for policy support. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 25836129 |
| DOI: | 10.55041/ISJEM05091 |