Driver Drowsiness and Attention Detection Dataset

A multi-class dataset for driver monitoring, focusing on drowsiness and attention detection. The dataset was sourced from Kaggle, but the author, organization, and specific collection details are not provided. The last update date and dataset size are unknown.

Use Cases

• Train a multi-class classifier for driver state recognition based on described monitoring features.
• Develop real-time alert systems for driver drowsiness based on behavioral indicators.
• Benchmark attention detection algorithms using labeled driver monitoring data.
• Study the correlation between visual/physiological cues and driver alertness levels.

Strengths

• The dataset is explicitly designed for multi-class classification, a specific machine learning task.
• It focuses on two distinct but related states: drowsiness and attention, which are core to driver safety applications.

Limitations

• Row count, file formats, and column-level documentation are absent, limiting suitability assessment.
• Description metadata is limited; actual data quality and feature semantics require manual inspection after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle