Conveyor Belt Operation Anomaly Event Detection Dataset

In the industrial sector, conveyor belts, as important material transport tools, face frequent fault issues such as material blockage, slippage, derailment, and item drop. These faults not only affect production efficiency but can also pose safety risks. Existing monitoring systems mostly rely on manual monitoring, which is inefficient and prone to missed detections. To enhance the level of industrial automation, this dataset aims to help develop more accurate event detection models by providing high-quality video data. Data collection uses high-resolution camera equipment to record the operation state of the conveyor belt under different operating environments. To ensure data quality, we implemented multiple rounds of annotation and consistency checks to ensure annotation accuracy and completeness. Data storage uses the MP4 format, organized in chronological order for easy analysis.