Traffic Congestion Prediction Dataset

Published: 18 February 2026| Version 1 | DOI: 10.17632/3dng3j76y9.1
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Description

The dataset is designed for the study and development of machine learning and intelligent traffic prediction models for congestion classification. This dataset contains structured traffic observations collected using a virtual IoT-based traffic monitoring approach from selected road segments in the Vijay Nagar area, Indore. The dataset is organized into four congestion classes based on traffic delay values: (1) FREE: Low or no traffic delay (2) LIGHT: Minor traffic delay (3) MODERATE: Noticeable traffic delay (4) HEAVY: Significant traffic congestion --------------------------------------------- Format: CSV (Comma Separated Values) Type: Spatio-temporal traffic dataset Features: Road ID, Hour, Day, Delay, Congestion Status: Primary dataset (collected and structured for machine learning) Applications: * Multi-class classification of traffic congestion levels * Training machine learning models for intelligent traffic prediction * Development of IoT-based smart traffic monitoring systems * Traffic pattern analysis and congestion forecasting * Smart city and intelligent transportation research

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Internet of Things, Field Traffic, Deep Learning

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