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| Main Authors: | , , , , |
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| Formato: | Recurso digital |
| Idioma: | |
| Publicado: |
Zenodo
2023
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| Subjects: | |
| Acceso en liña: | https://doi.org/10.5281/zenodo.18345388 |
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Table of Contents:
- Ambient Assistive Living has been a focus for both studies and business due to a fast-growing elderly population and the issues in health and social care that come with it. Government agendas place a high priority on the need to control, if not lower, healthcare costs while enhancing service quality. Although technology has a significant impact on attaining these goals, any solution must be conceived, put into practice, and verified using the right domain expertise. To get around these difficulties, remote real-time monitoring of a person's health can be utilised to spot relapses in illnesses and allow for early intervention. Thus, the study discussed in this paper focuses on creating a smart healthcare monitoring system that can monitor elderly individuals remotely. The technology discussed in this article focuses on the capability to monitor a person's physiological data in order to identify illnesses that can help with early intervention practises. This is accomplished by properly processing and interpreting the sensory data that has been obtained while communicating the discovery of a condition to the proper professional. The conclusion shows that the suggested approach can enhance clinical decision assistance while promoting Early Intervention Practices. Our thorough simulation findings show that the suggested system performs better than expected, with minimal packet loss (2.2% of all packets are discarded) and low latency (96% of packets are received in less than 1 millisecond). As a result, the system operates well and is inexpensive to use for gathering and modifying data.