AI-Based Analysis of Road Congestion Causes Using Real-Time Traffic Camera Data
Abstract
This study uses real-time data from traffic cameras and artificial intelligence (AI) algorithms to analyse the reasons for traffic congestion in a novel way. By recognising particular sources of congestion, such as accidents, processions, road construction, or general traffic accumulation, the proposed system seeks to supplement current navigation tools. The system makes very accurate predictions about the reasons for congestion by utilising a convolutional neural network (CNN) model that has been trained on a variety of datasets. The methodology, dataset preparation, model architecture, and interaction with a map-based user interface are all covered in detail in this work. The system's ability to give drivers and city planners useful insights is demonstrated by the results.
Keywords:
Traffic congestion, artificial intelligence, real-time traffic analysis, convolutional neural network (CNN), deep learning, traffic camera data, road construction, accident detection, processions, traffic management, navigation systems, urban planning, machine learning, data augmentation, web-based platform, intelligent transportation systems.Published
Issue
Section
License
Copyright (c) 2025 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Nikita Niteen , Simy Mary Kurian, Exploring Explainable AI, Security and Beyond : A Comprehensive Review , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- Athulya Anilkumar, Abhinav V V, Aneeta Shajan, Anjana S Nair, Bini M Issac, R Neenu, Image Descriptor For Visually Impaired , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Liyan Grace Shaji, Ayana Soman, Diya V Varghese, Elizabeth Anna Liju, Ethel Jimmy, A Comprehensive Survey on Automated Radiology Report Generation: Methods, Explainability, Multimodal Alignment, and Clinical Integration , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Angelina Kanjooparambil Joseph, Angel Rose Sanoj, Bewin P. G., Fabeela Ali Rawther, A Review on Prompt Engineering in Agriculture , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Linsa Mathew, Brain Tumor Detection , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Anu Rose Joy, An overview of Fake News DetectionusingBidirectional Long Short-TermMemory(BiLSTM)Models , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Shahina K.K, Abia Paul , Adole Saju, Hemil Antony, Sherin Paulose, Literature Survey On Windows Incident Response Tool , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Sreyas George, Gregan George, Ruth Tennyson, Rishil Shajan, Dr. Juby Mathew, MindPulse: Employee Mental Health Detection and Attrition Prediction App , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Amina Manaf , Ance Maria Joseph , Angel Joy , Anjaly Anilkumar , K S Rekha, Driver Drowsiness Detection Using Python , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Lakshmi Nandana, Mariyam Emamudeen, Nikitha Mary Varghese, Susan Andrews, Manoj T Joy, FaceVue: A Review For Dynamic Advertising And Cost Management System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
You may also start an advanced similarity search for this article.
