Automated Machine Learning Model in Secure Data Transmission in Sustainable Healthcare Sensor Network Using Quantum Blockchain Architecture
Kaavya Kanagaraj, A. Sheryl Oliver, V.P. Kavitha, S. Magesh, R. Manikandan · 2025
Body sensor network (BSN), a monitoring system utilized in a healthcare setting based on Internet of Things (IoT) technology, consists of wearable or implanted devices. Due to the limited battery capacity and energy supply for sensors in BSN, extending the service cycle of the network is a significant challenge. Increasing energy efficiency and energy collection is essential for the network to remain sustainable. Operators are looking to automate network diagnosis and management using machine learning (ML) to operate complex optical communication networks cost effectively. This research proposes a novel, sustainable, network-secure data transmission technique based on automated machine learning (AutoML). Here, the healthcare network monitoring uses a Reinforcement Bayesian Regressive Vector Machine. The secure data transmission uses quantum blockchain automated transfer machine graph learning. The experimental analysis of throughput, scalability, packet delivery ratio, and data integrity is carried out. New functionalities are needed to enable cognitive, autonomous management of optical network security to achieve these goals.