Sustainable Healthcare 5.0: Integration of IoT and Blockchain Technology with Federated Learning Model for Securing Healthcare Data

Healthcare is one of the goals of Sustainable Development Goals (SDGs) 2030. Technological advancements have been considered an out-fold structure to fulfill the requirements of SDGs requirements. Especially providing a suitable and accessible healthcare environment may create an impact on human sustaining. However, providing a suitable healthcare environment for achieving the SDGs is hampered due to non-structural technological advancements. Integrating federated learning with Internet of Things (IoT) and blockchain technology can provide a significant platform for developing Healthcare 5.0. Federated learning (FL) is a collaborative machine learning paradigm that enables multiple nodes (worker nodes) to train models across multiple devices cooperatively without exchanging the original data. It is promisingly a new methodology that helps to build privacy-preserving systems and secure distributed learning models. Distributed architecture has inherent problems such as communication cost, scaling up the system (vertical scaling), scaling out the system (horizontal scaling), and dealing with the heterogeneity of the nodes in the model, and many more. Specifically, integrating federated learning with blockchain improves federated learning security and performance and increases the scope of application. This integration can be called Blockchain federated learning (BFL). This paper presents a federated learning process by integrating IoT and blockchain through the proposed architecture. The simulations conducted on the model reveal its solidity in modernizing Machine Learning for suitable applications.