[Workshop] Stream Processing Made Easy With Flink | Register Now
The messages in this use case consist of raw ECG measurements, which are streamed to topics in Confluent Cloud and will help with the analysis of heart rates, by using Confluent's Flink service. This demonstrates how we can help health providers and researchers to have real-time data about patients, or even detect malfunction in medical equipment.
Leveraging the power of Apache Flink on Confluent Cloud enables real-time insights from ECG measurements, significantly enhancing cardiovascular healthcare and monitoring. The combination of these technologies ensures scalable and efficient data processing, facilitating continuous monitoring and immediate response capabilities essential for life-saving medical applications.
Gather health data from devices across a single site, or across the country and create a hub for all your needs.
Be able to know in real time which devices are gathering data or need servicing.
Empower healthcare providers to detect anomalies, trends, and critical health events as they happen, providing timely interventions.
This use case leverages the following building blocks in Confluent Cloud:
Continuously deliver messages about heart rate measurements or ECG.
EKS cluster receives the events from the health devices (or this layer could be replaced by an IoT gateway/connector), transforms/serializes as necessary and send it thru the Kafka Cluster for analysis via Flink.
Confluent Cloud hosts the Kafka Cluster and Flink Compute pools used to analyze the data and will tell us which anomalies we should pay attention to.
Contact Ness to learn more about this use case and get started.