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RKP (Real-Time Kinetic Processing)

Transforming Ventilator Data Management: Achieving Real-Time Streaming and Analysis for Enhanced Patient Care.

CLIENT NAME: [CONFIDENTIAL]

About Project

The RKP project for Vyaire Healthcare entailed a comprehensive redesign of the architecture used for ventilator reporting. This initiative aimed to significantly improve the efficiency of real-time data streaming from hospital ventilators. The project involved the development of a specialized data ingestion application and the utilization of advanced cloud technologies to ensure rapid and reliable data transfer and analysis, facilitating timely medical decisions.

Problem Statement

Vyaire Healthcare faced a critical challenge with their existing ventilator reporting system. The system experienced considerable latency, with data streaming efficiency clocking in at a sluggish 15 minutes. This delay in data transmission from hospital ventilators to the data analysis platforms hindered timely decision-making in patient care, posing a risk to patient health and limiting the effectiveness of medical interventions.

Solution Provided

  1. Architecture Redesign: The project team overhauled the entire architecture for ventilator reporting, enhancing the real-time streaming efficiency dramatically from 15 minutes to an impressive 2 seconds.
  2. Data Ingestion Application: A Windows application was developed using the .Net Framework. This application was tailored to capture streaming payloads from hospital ventilators and efficiently transfer them to a data lake on AWS. The use of IoT Core and Kinesis in this process led to a 90 percent reduction in latency.
  3. Real-Time Data Streaming and Analysis: The architecture was modeled to facilitate the streaming of real-time data from ventilators directly to AWS QuickSight reports. This was achieved through the integration of Kinesis Streams, Lambda functions, and Aurora databases. This solution enabled medical staff to access vital data swiftly and make quick, informed decisions for patients in critical conditions.

This comprehensive approach not only resolved the latency issues but also set a new standard in real-time data handling and analysis in healthcare, enhancing patient care and medical response efficiency.

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