Personal Healthcare Data Records Analysis and Monitoring using The Internet of Things and Cloud Computing

Abstract

This paper presents a proposed system for cloud-based and Internet o Things (IoT)-based electronic health records (EHRs) that utilize wearable body biosensors to collect biometric data in real time and analyze it to provide personalized therapy recommendations. The study aims to ensure the confidentiality and integrity of patient data through security authorizations, device authentication, and encrypted communication channels. The research method involves describing the proposed system’s communication environment and trust boundary and illustrating the communication mechanisms, including the “starting” and “authentication” procedures. The proposed communication protocols are also explained in detail, and a complete illustration of the symbols and abbreviations used throughout the work is provided. The initialization process involves contacting a body sensor network (BSN) server to register, generating a secret key, and assigning a track sequence number. The proposed systematic verification involves a dependable authentication solution to maintain secure communication between the biosensors, local processing unit (LPU), and BSN server. The verification process involves figuring out the values and generating a random integer, establishing communication with the receiver, and validating the data by searching for a corresponding tuple in the required database. The study emphasizes the importance of a robust IoT communication architecture to ensure secure data transfer between devices, networks, and individuals.