Key result
Fog computing architecture enables wearable ECG monitoring at the system edge.
Why the study?
All data generated by measuring biosignals cannot be transferred to cloud servers for processing and storage, requiring edge processing to reduce data.
The paper proposes a fog computing architecture to handle the massive data generated by wearable biosignal (ECG) monitoring devices at the system edge.
Answers are grounded in this paper and cite their sources.
Feasibility shown for edge ECG monitoring; leaves open clinical validation before practice change.
The number of embedded devices connected to the Internet in 2023 has grown upto 15 billion devices. Already in 2020, the global amount of data generated daily was roughly 2.5 Exabytes and a large portion of this is from IoT devices. A significant amount of the data is generated by measuring biosignals, from which all this data cannot be transferred to cloud servers for processing and storage. Some processing to reduce data must be done already at the system edge. This paper proposes an architecture for a fog computing platform suitable for wearable biosignal monitoring. We also demonstrate one implementation for ECG monitoring.
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Waseem et al. (2024) studied Wearable biosignal monitoring. Fog computing platform architecture was evaluated. A fog computing platform architecture suitable for wearable biosignal monitoring was proposed and demonstrated for ECG monitoring at the system edge.
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