 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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: June 2026
Volume 11 | Issue 6
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 : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 121
Article Submitted : 24737
Article Published : 9361
Total Authors : 24875
Total Reviewer : 861
Total Countries : 169
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | AI-Based Smart Traffic Monitoring and Signal Management System |
| Authors Name: | Tejaswini K , Aravinda T V , Krishnareddy K R , Ramesh B E |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_213006
|
| Published Paper Id: | IJRTI2605177 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | The IoT-Based Smart Traffic Management System is an advanced intelligent transportation solution developed to reduce traffic congestion, improve road safety, and optimize vehicle movement using Internet of Things (IoT), Artificial Intelligence (AI), and Deep Learning technologies. The system integrates IoT hardware components such as IR sensors, ultrasonic sensors, RFID modules, NodeMCU/ESP8266 microcontrollers, cameras, and wireless communication modules to collect real-time traffic data from road intersections and traffic signals. The captured data is transmitted to the central monitoring system through IoT communication protocols for real-time analysis and decision-making. The proposed system uses the YOLOv8 deep learning model for vehicle detection and counting from live camera feeds. Based on the detected traffic density, a Deep Q-Network (DQN) reinforcement learning algorithm dynamically adjusts traffic signal timings to reduce waiting time and improve traffic flow efficiency. The IoT sensors continuously monitor vehicle movement and congestion levels, while RFID technology can provide priority access for emergency vehicles such as ambulances and fire trucks. A professional dashboard developed using Python Tkinter and Matplotlib displays live traffic video, traffic density, congestion level, signal status, and graphical traffic trends in real time. The intelligent system automatically predicts congestion conditions and optimizes signal control without manual intervention. By combining IoT hardware, AI-based traffic analysis, and smart signal automation, the system helps reduce fuel consumption, travel delay, and air pollution while improving transportation efficiency and urban mobility. The proposed Smart Traffic Management System offers a scalable, cost-effective, and reliable solution for smart city infrastructure and future intelligent transportation systems... |
| Keywords: | Internet of Things (IoT), Artificial Intelligence (AI), and Deep Learning, IR sensors, ultrasonic sensors, RFID modules, NodeMCU/ESP8266 microcontrollers, cameras, wireless communication |
| Cite Article: | "AI-Based Smart Traffic Monitoring and Signal Management System ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.b672-b675, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605177.pdf |
| Downloads: | 00074 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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: IJRTI2605177
Registration ID:213006
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: b672-b675 Country: chitradurga, karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605177 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605177 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||