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Efficient data transmission on wireless communication through a privacy-enhanced blockchain process

In the medical era, wearables often manage and find the specific data points to check important data like resting heart rate, ECG voltage, SPO2, sleep patterns like length, interruptions, and intensity, and physical activity like kind, duration, and levels. These digital biomarkers are created mainl...

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Autores principales: Aluvalu, Rajanikanth, Kumaran V. N., Senthil, Thirumalaisamy, Manikandan, Basheer, Shajahan, Ali aldhahri, Eman, Selvarajan, Shitharth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280508/
https://www.ncbi.nlm.nih.gov/pubmed/37346706
http://dx.doi.org/10.7717/peerj-cs.1308
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author Aluvalu, Rajanikanth
Kumaran V. N., Senthil
Thirumalaisamy, Manikandan
Basheer, Shajahan
Ali aldhahri, Eman
Selvarajan, Shitharth
author_facet Aluvalu, Rajanikanth
Kumaran V. N., Senthil
Thirumalaisamy, Manikandan
Basheer, Shajahan
Ali aldhahri, Eman
Selvarajan, Shitharth
author_sort Aluvalu, Rajanikanth
collection PubMed
description In the medical era, wearables often manage and find the specific data points to check important data like resting heart rate, ECG voltage, SPO2, sleep patterns like length, interruptions, and intensity, and physical activity like kind, duration, and levels. These digital biomarkers are created mainly through passive data collection from various sensors. The critical issues with this method are time and sensitivity. We reviewed the newest wireless communication trends employed in hospitals using wearable technology and privacy and Block chain to solve this problem. Based on sensors, this wireless technology controls the data gathered from numerous locations. In this study, the wearable sensor contains data from the various departments of the system. The gradient boosting method and the hybrid microwave transmission method have been proposed to find the location and convince people. The patient health decision has been submitted to hybrid microwave transmission using gradient boosting. This will help to trace the mobile phones using the calls from the threatening person, and the data is gathered from the database while tracing. From this concern, the data analysis process is based on decision-making. They adapted the data encountered by the detailed data in the statistical modeling of the system to produce exploratory data analysis for satisfying the data from the database. Complete data is classified with a 97% outcome by removing unwanted data and making it a 98% successful data classification.
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spelling pubmed-102805082023-06-21 Efficient data transmission on wireless communication through a privacy-enhanced blockchain process Aluvalu, Rajanikanth Kumaran V. N., Senthil Thirumalaisamy, Manikandan Basheer, Shajahan Ali aldhahri, Eman Selvarajan, Shitharth PeerJ Comput Sci Computer Networks and Communications In the medical era, wearables often manage and find the specific data points to check important data like resting heart rate, ECG voltage, SPO2, sleep patterns like length, interruptions, and intensity, and physical activity like kind, duration, and levels. These digital biomarkers are created mainly through passive data collection from various sensors. The critical issues with this method are time and sensitivity. We reviewed the newest wireless communication trends employed in hospitals using wearable technology and privacy and Block chain to solve this problem. Based on sensors, this wireless technology controls the data gathered from numerous locations. In this study, the wearable sensor contains data from the various departments of the system. The gradient boosting method and the hybrid microwave transmission method have been proposed to find the location and convince people. The patient health decision has been submitted to hybrid microwave transmission using gradient boosting. This will help to trace the mobile phones using the calls from the threatening person, and the data is gathered from the database while tracing. From this concern, the data analysis process is based on decision-making. They adapted the data encountered by the detailed data in the statistical modeling of the system to produce exploratory data analysis for satisfying the data from the database. Complete data is classified with a 97% outcome by removing unwanted data and making it a 98% successful data classification. PeerJ Inc. 2023-04-21 /pmc/articles/PMC10280508/ /pubmed/37346706 http://dx.doi.org/10.7717/peerj-cs.1308 Text en © 2023 Aluvalu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Computer Networks and Communications
Aluvalu, Rajanikanth
Kumaran V. N., Senthil
Thirumalaisamy, Manikandan
Basheer, Shajahan
Ali aldhahri, Eman
Selvarajan, Shitharth
Efficient data transmission on wireless communication through a privacy-enhanced blockchain process
title Efficient data transmission on wireless communication through a privacy-enhanced blockchain process
title_full Efficient data transmission on wireless communication through a privacy-enhanced blockchain process
title_fullStr Efficient data transmission on wireless communication through a privacy-enhanced blockchain process
title_full_unstemmed Efficient data transmission on wireless communication through a privacy-enhanced blockchain process
title_short Efficient data transmission on wireless communication through a privacy-enhanced blockchain process
title_sort efficient data transmission on wireless communication through a privacy-enhanced blockchain process
topic Computer Networks and Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280508/
https://www.ncbi.nlm.nih.gov/pubmed/37346706
http://dx.doi.org/10.7717/peerj-cs.1308
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