Real-Time Emergency Equipment Monitoring Dataset
#object detection #image segmentation #anomaly detection #emergency equipment monitoring #medical imaging analysis #real-time monitoring
- 15000 records
- 3.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
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.
Dataset Insights
Sample Examples
d9eeac7f**.jpg|1280*1706|323.47 KB
480c639d**.jpg|1280*1644|277.49 KB
8a7f703f**.jpg|1280*958|219.28 KB
79757bc6**.jpg|1316*720|90.84 KB
ec3919b9**.jpg|1280*960|208.05 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| device_type | string | The category of emergency device, such as pacemaker, ventilator, etc. |
| device_condition | string | The current operating condition of the device, such as normal, malfunctioning, under maintenance, etc. |
| device_model | string | The specific model information of the emergency device. |
| alert_status | string | Whether the device is in an alert state, such as alert active, no alert. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What types of devices are included in this real-time emergency equipment monitoring dataset?
- The dataset includes images of various emergency equipment such as ECG monitors, ventilators, and defibrillators.
- Which medical equipment management efficiency can this dataset help improve?
- Using object detection technology, this dataset can help improve the management efficiency of devices like ECG monitors, ventilators, and defibrillators.
- How can this object detection dataset be applied in the healthcare industry?
- Healthcare institutions can use this dataset to develop real-time monitoring systems to improve equipment management and fault detection.
- How does object detection technology work in the real-time emergency equipment monitoring dataset?
- Object detection technology operates by identifying and labeling specific objects in device images to monitor equipment status in real-time.
- What are the main advantages of using this dataset?
- The main advantages of this dataset include increased automation in medical equipment management, reduced need for manual monitoring, and improved response speed.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Real-Time Emergency Equipment Monitoring Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/0e92c55d80f91812a88739e919d9bf59?dataset_scene_id=4},
urldate={2025-10-22},
keywords={emergency equipment, real-time monitoring, object detection dataset, medical imaging, machine learning},
version={1.0}
}Using this in research? Please cite us.
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