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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) |
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Issue: May 2024
Volume 9 | Issue 5
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| Paper Title: | Intelligent Traffic Signal Management using Raspberry Pi and OpenCV |
| Authors Name: | J. Divya Madhuri , Dr. Ch. Rambabu , M. Vamsi , D. Tharun Nayak , L. Pavan Prasad |
| Download E-Certificate: | Download |
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IJNRD_216926
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| Published Paper Id: | IJNRD2404301 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Traffic congestion is a prevalent problem in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. The Smart Traffic Management System project aims to address these big challenges by leveraging advanced technologies such as computer vision, Internet of Things (IoT), and machine learning to optimize traffic flow, enhance road safety, and improve overall transportation efficiency. The project focuses on real-time vehicle detection, traffic analysis, and intelligent traffic signal control to dynamically adapt to changing traffic conditions and alleviate congestion at some key intersections. By integrating data from traffic sensors, cameras, and IoT devices into a centralized management platform, the system provides actionable insights for some traffic management authorities to make data-driven decisions and implement proactive measures for congestion mitigation. Through the deployment of smart traffic solutions and the utilization of some data analytics techniques, the Traffic Management System project seeks to somewhat transform urban mobility, reduce travel times, and enhance the quality of life for residents in metropolitan areas. |
| Keywords: | Raspberry Pi, OpenCV, Traffic Control, Realtime monitoring, LED lights, Traffic Density, Vehicle Detection, and Traffic Signals. |
| Cite Article: | "Intelligent Traffic Signal Management using Raspberry Pi and OpenCV", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.d1-d8, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404301.pdf |
| Downloads: | 00034 |
| 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 |
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Published Paper ID:IJNRD2404301 Registration ID: 216926 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: d1-d8 Country: Machilipatnam, Andhra Pradesh, India Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404301 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404301 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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