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Enhanced Traffic Management for Emergency Vehicle Information Transmission using Wireless Sensor Networks.

Authors :
Kumar, P Phani
Simon, Judy
Devi, K Durga
Elaveini, M Aarthi
Kapileswar, N
Source :
Procedia Computer Science; 2023, Vol. 230, p798-807, 10p
Publication Year :
2023

Abstract

Considerable research has been conducted in over a decade on traffic management systems that utilize Wireless Sensor Networks (WSNs) to mitigate congestion and prioritize emergency vehicles. The traffic management is becoming a wide interesting area for both academic and industrial researchers. The real-time traffic management is a dynamic scheme and is very challenging to provide an accurate signalling time and priority for a specific vehicle. This paper introduces a novel emergency vehicle information passing system that utilizes Radio Frequency (RF) sensors. This research study presents an innovative system for transmitting emergency vehicle information, which makes use of Radio Frequency (RF) sensors. The system effectively transmits crucial data, such as vehicle ID, approaching direction, mileage driven, and destination time. By doing so, it enables other vehicles to allocate appropriate space and facilitate smoother passage for emergency vehicles. The main intention of this approach is to improve the communication speed among the nodes and to reduce the response time. The communication among the nodes is done with different frequencies to enhance the method's effectiveness. We also propose a priority-based MAC (PMAC), which guarantees a slot allocation for emergency message transmission in the network. The effectiveness of the proposed approach is assessed through simulation using NS-2. The findings emphasize the effectiveness of the RF sensor when it comes to its ability to respond quickly and showcasing the PMAC's capability to reduce end-to-end delay. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
230
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
174641281
Full Text :
https://doi.org/10.1016/j.procs.2023.12.053