Blockchain-enabled intelligent model for energy-constrained IoMT networks with privacy-preserving

The Internet of Medical Things (IoMT) has expanded to enhance healthcare by integrating physical devices, facilitating real-time monitoring and diagnosis of patient conditions via biosensors. These systems work in tandem with medical experts to track patient records and optimize system efficiency. However, challenges persist in addressing energy management, timely decision-making, and data handling in resource-constrained healthcare applications. Ensuring privacy within wireless networks is another critical concern.

In response, a distributed intelligence-based collaborative framework has been proposed for healthcare systems, utilizing an agent-driven approach. This framework aims to enhance network energy efficiency, enabling swift responses in critical situations. Trust is established through third-party interactions in a decentralized network, maintaining device reputation. The framework also introduces blockchain-based security to preserve data privacy, ensure immutability of data transmission, and maintain data integrity.

The proposed model was evaluated using the NS-3 simulator, showcasing significant improvements over existing schemes such as PKI-EERP, ASCP-IoMT, and GWO-MARP. The enhancements achieved include a 52% reduction in packet drop ratio, 45% increase in throughput, 34% decrease in delay, 42% extension in network lifetime, 39% lower energy consumption, and 30% reduced blockchain overhead across diverse health sensor scenarios and time-variant conditions.

This research was supported by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No. (DGSSR-2025-02-01408).