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An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems
In today's environment, electronics technology is growing rapidly because of the availability of the numerous and latest devices which can be deployed for monitoring and controlling the various healthcare systems. Due to the limitations of such devices, there is a dire need to optimize the util...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970907/ https://www.ncbi.nlm.nih.gov/pubmed/35371215 http://dx.doi.org/10.1155/2022/2206573 |
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author | Khan, Shadab Singh, Yash Veer Singh, Pushpendra Singh, Ram Sewak |
author_facet | Khan, Shadab Singh, Yash Veer Singh, Pushpendra Singh, Ram Sewak |
author_sort | Khan, Shadab |
collection | PubMed |
description | In today's environment, electronics technology is growing rapidly because of the availability of the numerous and latest devices which can be deployed for monitoring and controlling the various healthcare systems. Due to the limitations of such devices, there is a dire need to optimize the utilization of the devices. In healthcare systems, Internet of things (IoT) based biosensors networking has minimal energy during transmission and collecting data. This paper proposes an optimized artificial intelligence system using IoT biosensors networking for healthcare problems for efficient data collection from the deployed sensor nodes. Here, an optimized tunicate swarm algorithm is used for optimizing the route for data collection and transmission among the patient and doctor. The fitness function of the optimized tunicate swarm algorithm used the distance, proximity, residual, and average energy of nodes parameters. The proposed method is attributed to the optimal CH chosen under TSA operation having a lower energy consumption. The performance of the proposed method is compared to the existing methods in terms of various metrics like stability period, lifetime, throughput, and clusters per round. |
format | Online Article Text |
id | pubmed-8970907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-89709072022-04-01 An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems Khan, Shadab Singh, Yash Veer Singh, Pushpendra Singh, Ram Sewak Comput Intell Neurosci Research Article In today's environment, electronics technology is growing rapidly because of the availability of the numerous and latest devices which can be deployed for monitoring and controlling the various healthcare systems. Due to the limitations of such devices, there is a dire need to optimize the utilization of the devices. In healthcare systems, Internet of things (IoT) based biosensors networking has minimal energy during transmission and collecting data. This paper proposes an optimized artificial intelligence system using IoT biosensors networking for healthcare problems for efficient data collection from the deployed sensor nodes. Here, an optimized tunicate swarm algorithm is used for optimizing the route for data collection and transmission among the patient and doctor. The fitness function of the optimized tunicate swarm algorithm used the distance, proximity, residual, and average energy of nodes parameters. The proposed method is attributed to the optimal CH chosen under TSA operation having a lower energy consumption. The performance of the proposed method is compared to the existing methods in terms of various metrics like stability period, lifetime, throughput, and clusters per round. Hindawi 2022-03-24 /pmc/articles/PMC8970907/ /pubmed/35371215 http://dx.doi.org/10.1155/2022/2206573 Text en Copyright © 2022 Shadab Khan et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Khan, Shadab Singh, Yash Veer Singh, Pushpendra Singh, Ram Sewak An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems |
title | An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems |
title_full | An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems |
title_fullStr | An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems |
title_full_unstemmed | An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems |
title_short | An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems |
title_sort | optimized artificial intelligence system using iot biosensors networking for healthcare problems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8970907/ https://www.ncbi.nlm.nih.gov/pubmed/35371215 http://dx.doi.org/10.1155/2022/2206573 |
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