Volume 7 , Issue 1 , PP: 28-39, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Vikas panthi 1 , Amit Kumar Mishra 2
Doi: https://doi.org/10.54216/IJWAC.070103
The technology that was developed during the fourth industrial revolution has contributed to the recent surge of interest that has been seen in the field of medicine. In particular, the importance of personal medical information obtained via knowledgeable self-diagnosis is becoming more apparent. However, the disclosure of such private medical information raises several concerns regarding trustworthiness and security. Accidents involving personally identifiable medical information could happen on the computer, but more frequently than not, they take place during the process of information exchange and data transfer. So, the goal of this research is to improve the trustworthiness of managing such sensitive data by making blockchain technology better. The objective of the project was to create smart healthcare systems by utilising blockchain technology and the Internet of Things (IoT). Moreover, they utilised various measuring instruments to collect data and carry out an individual electrocardiogram assessment. Through an examination of the fused threshold, the observed biosignals were analysed to provide a tailored diagnostic. In this article, we describe the implementation of a monitoring system that analyses individual biometric information by making use of measuring devices. Machine learning has been included in the deployed system, which has resulted in better dependability and security of the system's information.
Internet of Things , Healthcare , Machine Learning , Software-Defined Networking , Bio- Signals , Data Analysis
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