IoT Devices and Sensors Are Used to Optimize Traffic Flow, Reduce Congestion, And Enhance Road Safety

Abstract

Wireless sensor networks (WSN) use wireless ad-hoc technology to connect self-powered sensing devices. In addition to summarizing the potential advantages of Intelligent Transport Systems (ITS) applications for enhancing mobility quality and safety, this paper introduces the fundamentals of WSN-based traffic monitoring. This method increases the geographical precision of traffic parameter sampling by enabling a denser placement of sensors along the route than traditional infrastructure-based monitoring systems. This work's analysis of experimental data demonstrates how high geographical resolution can improve both the accuracy of short-term traffic status prediction and the dependability of traffic modeling. The analysis makes use of data released by the state's Ministry of Transportation and the University of California, Berkeley's motorway performance measuring system. On an asphalt segment where a pertinent traffic-flow abnormality is identified, traffic flow and occupancy are estimated continuously using a microscopic cellular automata model. As is possible in the case of WSN-based monitoring systems, the research demonstrates that the estimate accuracy increases with a greater amount of operating sensors. In order to reduce metropolitan congestion, smart public transportation systems, or STS, are essential. This study looks at how jam administrators could increase the flexibility and productivity of transportation by utilizing IoT-related remote monitoring systems. Synergies with IoT-connected wireless sensor networks, smart traffic signal systems, and driverless cars are also discussed in the piece of writing. These collaborations improve the viability of gridlock executives and the future of STS. In the investigation piece, an IoT-related remote sensor network was deployed to a metropolitan region to assess the proposed concept. The statistics, traffic management techniques, and improvements in journey duration, traffic flow, and environmental sustainability are all examined in the study. This study suggests that IoT-connected wireless sensor networks could transform traffic congestion management in smart transportation systems. With the use of real-time data and sophisticated analytics, cities may be able to increase mobility, reduce traffic, and build sustainable cities.