Real-Time Emergency Equipment Monitoring Dataset

The current medical industry faces numerous challenges in the monitoring and management of emergency equipment. Insufficient real-time monitoring of emergency equipment leads to an inability to promptly detect equipment failures, affecting treatment outcomes. Existing solutions primarily rely on manual monitoring, which is inefficient and error-prone. This dataset aims to provide high-quality equipment monitoring image data to assist researchers and developers in training machine learning models, improving the accuracy and timeliness of equipment failure detection. The dataset contains images from various emergency scenarios, captured using high-resolution camera equipment to ensure the quality of each image. The data has undergone multiple rounds of annotation and expert review to ensure consistency and accuracy in labeling. Data is stored in JPEG format, organized by category and time, facilitating subsequent retrieval and use.