Smart Examination Malpractice Detection Dataset

A multi-sensor dataset designed for intelligent examination surveillance. The dataset was sourced from Kaggle, but the author, organization, and last update date are unknown. Its specific size, row count, file formats, and license information are also not provided.

Use Cases

• Train anomaly detection models based on multi-sensor surveillance data.
• Develop automated proctoring systems based on sensor fusion concepts.
• Research behavioral patterns during examinations based on surveillance data.

Strengths

• The description explicitly mentions it is a multi-sensor dataset, suggesting multiple data modalities.
• The dataset is designed for a specific, applied problem: examination malpractice detection.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Kaggle