Traffic Congestion Prediction Dataset

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
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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