Remote data monitoring file
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接：
https://zenodo.org/record/14500256
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资源简介：
Description of the Dataset:
Title: Sensor Data for Critical Health Monitoring in IoMT Ecosystems
Description:This dataset contains 1000 sensor readings generated to simulate a remote patient monitoring framework as described in the research paper titled "A Hierarchical Dew-Roof-Fog-Cloud Remote Patient Monitoring Framework for IoMT Ecosystems." The dataset includes key health indicators monitored in Internet of Medical Things (IoMT) setups, focusing on heart rate, body temperature, and blood pressure (systolic and diastolic). These indicators are critical for early detection of abnormal health conditions and emergency response in a hierarchical computing architecture involving dew, roof, fog, and cloud layers.
Data Variables:
Heart Rate (bpm): The number of heartbeats per minute, ranging from normal to critical levels.
Normal range: 60-100 bpm
Critical range: <60 bpm or >120 bpm
Body Temperature (°F): Body temperature recorded in Fahrenheit, simulating normal and febrile conditions.
Normal range: 97°F-99°F
Critical range: <96°F or >101°F
Systolic BP (mmHg): The systolic component of blood pressure, indicating cardiovascular health.
Normal range: 120-140 mmHg
Critical range: <100 mmHg or >140 mmHg
Diastolic BP (mmHg): The diastolic component of blood pressure.
Normal range: 80-90 mmHg
Critical range: <60 mmHg or >90 mmHg
Purpose:The dataset was designed to evaluate the performance of the proposed DeW-IoMT framework for real-time patient monitoring. It helps validate the system's ability to detect and alert abnormal health conditions efficiently within a hierarchical architecture.
Key Features:
Includes both normal and critical readings to simulate realistic healthcare scenarios.
Designed to support response time analysis, energy dissipation evaluation, and anomaly detection in IoMT ecosystems.
Facilitates research on remote patient monitoring, edge computing, and decentralized healthcare systems.
Use Cases:
Validation of IoMT monitoring frameworks.
Testing response mechanisms in hierarchical computing setups.
Developing predictive models for anomaly detection in health monitoring.
Format: CSV file with the following columns:
Heart Rate (bpm)
Body Temperature (°F)
Systolic BP (mmHg)
Diastolic BP (mmHg)
创建时间：
2024-12-16
