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<p>The paper proposes a scalable and secure Remote Patient Monitoring (RPM) architecture with an event-driven model to optimize the ingestion of data and blockchain processing. The framework will combine Apache Kafka to process real-time data with ease, allow the efficient detection of events based on the threshold, and have a customized blockchain that provides an immutable storage of essential patient records. In order to provide better security at very light computational costs, the Elliptic Curve Cryptography (ECC) is used to encrypt at light weights. Moreover, a hybrid on-chain and off-chain storage is embraced in order to strike the balance between resource efficiency and security. Experimental findings show that the system has a maximum throughput of 1000 transactions per second (TPS) and 1 KB packets with a mean latency of 150 ms. The trade-off between data size and processing speed can be observed when the packets are larger (10 MB) where the throughput decreases to 50 TPS. The architecture is 75 percent efficient when it has 1000 IoMT devices, which is indicative of its strength in large scale applications. Comparative analysis shows that the system is superior in scalability, security, and real-time efficiency and can be used as a reliable option in managing healthcare data on blockchains.</p>

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Decoupling data ingestion and blockchain processing: a high-performance event-driven Kafka architecture for remote patient monitoring

  • 期刊论文

  • 发表日期：

    2026年7月14日

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  • Nikita Tiwari,
  • Pradeep Kumar Biswal,
  • Prakash Ranjan

摘要

The paper proposes a scalable and secure Remote Patient Monitoring (RPM) architecture with an event-driven model to optimize the ingestion of data and blockchain processing. The framework will combine Apache Kafka to process real-time data with ease, allow the efficient detection of events based on the threshold, and have a customized blockchain that provides an immutable storage of essential patient records. In order to provide better security at very light computational costs, the Elliptic Curve Cryptography (ECC) is used to encrypt at light weights. Moreover, a hybrid on-chain and off-chain storage is embraced in order to strike the balance between resource efficiency and security. Experimental findings show that the system has a maximum throughput of 1000 transactions per second (TPS) and 1 KB packets with a mean latency of 150 ms. The trade-off between data size and processing speed can be observed when the packets are larger (10 MB) where the throughput decreases to 50 TPS. The architecture is 75 percent efficient when it has 1000 IoMT devices, which is indicative of its strength in large scale applications. Comparative analysis shows that the system is superior in scalability, security, and real-time efficiency and can be used as a reliable option in managing healthcare data on blockchains.