|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | AI Based Emergency Vehicles Detecting and Traffic Controlling System |
| Authors Name: | Aditya Pawar , Yogesh Sutar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_215635
|
| Published Paper Id: | IJNRD2403303 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | Intersection congestion presents a formidable obstacle to the efficient movement of emergency vehicles, such as ambulances and fire trucks, jeopardizing prompt responses to life-threatening situations. Despite ongoing efforts, existing solutions have struggled to adequately address this pressing issue. However, our innovative artificial intelligence (AI)-based system offers a superior alternative. Leveraging advanced AI algorithms, our technology intelligently detects and prioritizes approaching emergency vehicles, enabling dynamic adjustments to traffic signal timings at intersections. This strategic allocation of green signal intervals minimizes transit delays, resulting in significantly reduced response times for emergency vehicles. Notably, our system seamlessly integrates with pre-existing infrastructure, requiring minimal additional hardware or upgrades. Furthermore, its adaptability to various intersection layouts and traffic conditions ensures versatile applicability. Through collaborative partnerships with municipalities and transportation authorities, our solution aims to achieve widespread implementation, thereby enhancing emergency response capabilities and safeguarding the safety and well-being of individuals within our communities. |
| Keywords: | Emergency Vehicles, Artificial Intelligence, Video Processing, Traffic Signals, Traffic Congestion, Intelligent Traffic Management System, Scheduling Algorithm, Integrated Circuit |
| Cite Article: | "AI Based Emergency Vehicles Detecting and Traffic Controlling System", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.d10-d17, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403303.pdf |
| Downloads: | 000116 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2403303 Registration ID: 215635 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: d10-d17 Country: Solapur, Maharashtra, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403303 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403303 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn