OPTIMIZING URBAN TRAFFIC FLOW WITH IOT-BASED TRAFFIC MANAGEMENT SYSTEMS
Komal Khadotra, Sandeep Raj
(2023) Vol. 01, No. 01, pp. 128-134
ABSTRACT
Urban areas face persistent challenges from traffic congestion and road safety issues, impacting economic efficiency and public welfare. Addressing these concerns requires innovative approaches, and this paper explores the transformative potential of Internet of Things (IoT) technology in revolutionizing urban traffic management. By leveraging IoT- enabled solutions such as smart traffic lights and variable message signs, the paper investigates how real-time data collection and advanced analytics can optimize traffic flow and enhance road safety. Drawing from a comprehensive review of existing literature, the study proposes a detailed conceptual framework for the implementation of IoT-based traffic management systems. Key components of this framework include the deployment of IoT
sensors for data collection, integration of communication technologies for real-time data transmission, and implementation of data analytics for informed decision-making. Furthermore, the paper discusses potential socio-economic benefits, such as reduced travel times, fuel consumption, and emissions, along with improved road safety and overall urban liability. The findings underscore the importance of IoT-driven innovations in reshaping urban mobility and highlight avenues for future research and development in this rapidly evolving field.
Keywords: IoT, Traffic Management, Smart Traffic Lights, Urban Traffic Flow, Traffic Congestion, Traffic Accidents