A Home Health Monitoring System Based on Federated Learning and Blockchain Technology

As society advances, healthcare has become essential for everyone. New technology is needed to improve healthcare and keep up with changing medical needs. This paper proposes a new home health monitoring system that uses a special blockchain system with a learning technique called Federated Learning. This means people can be monitored at home instead of going to hospitals. The system uses special computer programs (Deep Learning Neural Network and Convolutional Neural Network) to analyze health data and predict diseases like diabetes and pneumonia with an accuracy of approximately $\mathbf{9 0 \%}$. Federated Learning keeps user data secure by sharing only a small part of the data with other hospitals. The system also uses blockchain technology, like a secure lockbox, to further protect data and prevent theft during communication between hospitals. Accurate disease prediction offers significant benefits, including early detection, timely intervention, and better management of chronic conditions, ultimately improving patient outcomes and reducing the burden on healthcare facilities. This new system not only enhances access to healthcare at home but also keeps data safe and private.