Intelligent Traffic Signal Prioritization for Emergency Vehicle Diversion in Urban Environments using Multi-modal Deep Learning

Author(s)	Santosh D. Pandure, Pravin L. Yannawar
Country	India
Abstract	This research work introduces an innovative approach for diverting traffic in urban areas by prioritizing traffic signals for emergency vehicles. The proposed method leverages deep learning techniques to identify and prioritize emergency vehicles, thereby enabling the manipulation of signal sequences at local traffic intersections along their path. The identification of emergency vehicles is achieved through the integration of multiple artificial intelligence(AI)-based algorithms, combining audio and video data analysis to enhance accuracy and reliability in urban settings. This research contributes to the enhancement of urban traffic management, reducing response times for emergency services, and improving overall road safety.
Keywords	Emergency Vehicle(EV), artificial intelligence(AI), Emergency services, Urban.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 4, July-August 2024
Published On	2024-07-03
Cite This	Intelligent Traffic Signal Prioritization for Emergency Vehicle Diversion in Urban Environments using Multi-modal Deep Learning - Santosh D. Pandure, Pravin L. Yannawar - IJFMR Volume 6, Issue 4, July-August 2024. DOI 10.36948/ijfmr.2024.v06i04.23981
DOI	https://doi.org/10.36948/ijfmr.2024.v06i04.23981
Short DOI	https://doi.org/gt3ngd

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research