Healthcare monitoring system with blockchain technology encompassing energy harvesting and delays in a Wideband Network

Abstract

The study of WBANs enables people to be monitored for their healthcare. WBAN connects to the Internet of Things to create a logistic, remote healthcare monitoring system that allows for the diagnosis of a variety of medical conditions. The three main problems in the WBAN IoT environment are the attributes of service, privacy, and efficient energy. Existing solutions for these three problems fall short because nodes are resource-constrained, which causes latency and reduces energy use. This study introduces the B-DEAH system in the WBAN-IoT setting. Dual sinks are used with body and environment sensors for periodic and emergency packet transfer. This study involves several procedures, and each process is detailed as follows: It is suggested to register keys for patients using an expanded form of the PRESENT method. Using the spotted hyena optimizer, cluster nucleation, and central node selection are carried out. The MOORA algorithm is then used to build cluster-based routing. The elliptic curve cryptography used as an algorithm is used to deploy and authenticate the patient block agent (PBA) for data transmission. Classifier, queue manager, channel selector, and security manager are the three entities employed in PBA. A unique function controls each entity, and packets are divided into three categories via two ways deep reinforcement learning (TS-DRL): emergency, non-emergency, and incorrect data. Each packet is placed in a different queue, known as the emergency, periodic, and faulty queue. Reyni entropy is employed to manage each queue. Utilize a vector optimization-based channel selection technique, periodic fragments are delivered by a different channel without any interference.

URN:NBN:sciencein.jist.2024.v12.794