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Optimized Dictionary-based Sparse Regression Learning for Health Care Monitoring in IoT-based Context-Aware Architecture

S. Kamalesh,A. Muthukrishnan

Published 2023 in Journal of the Institution of Electronics and Telecommunication Engineers

ABSTRACT

Several context-aware systems have been recently developed to provide physiological data about the health and well-being of each individual. But, there is a delay in sending data to the cloud when monitoring the patient's health. So, to overcome such types of delays, in this manuscript, a Dictionary-based Sparse Regression Learning with Golden Jackal Optimization is proposed to monitor the healthcare data in IoT-based context-aware architecture (DSRL-GJO-HD-CAA-IOT). Initially, the input data are gathered from real-time datasets. Afterward, data are fed to pre-processing. Pre-processing data include the collection, data storage, and data redundancy phase. For the redundancy phase, structural interval gradient filtering (SIGF) is used to delete the repeated data. Then, the pre-processing output is fed to feature extraction. The feature is extracted using structured optimal graph-based sparse feature extraction. After that, the extracted features are given to Dictionary-based Sparse Regression Learning (DBSRL) optimized with the Golden Jackal Optimization algorithm for effectively classifying regular, irregular, and critical conditions of patients. The proposed DSRL-GJO-HD-CAA-IOT approach is implemented in OMNeT++. The performance of the proposed DSRL-GJO-HD-CAA-IOT approach attains 3.10%, 7.12%, 7.73%, and 6.7% high accuracy, 24.13%, 13.04%, 29.51%, and 17.81% higher scalability, and 2.29%, 5.36%, 1.55%, and 3.91% higher response time than the existing methods.

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