### Contribution  
The primary objectives of this research are to implement and evaluate the effectiveness of low-cost wireless sensor networks in monitoring the sleep quality and vital signs of elderly individuals within their home environments. By utilizing a WSN, the study aims to enable the continuous, non-invasive monitoring of key physiological parameters, such as heart rate, respiratory rate, and sleep stages, along with environmental factors like temperature and noise levels. Additionally, the research seeks to integrate these networks with artificial intelligence algorithms to generate personalized health recommendations aimed at improving sleep quality and overall well-being. Furthermore, the study endeavors to assess the broader impact of WSN technology on reducing the burden of caregiving for families, thereby enhancing the quality of care for elderly individuals. Through these objectives, this research contributes to the development of scalable, cost-effective solutions that address the unique health challenges faced by aging populations, paving the way for more comprehensive and integrated care strategies in geriatric health monitoring. Our research makes a novel contribution to the field of geriatric health care through the following:  
* Innovative Use of Technology: The deployment of WSNs provides a modern, advanced method for the continuous and non-intrusive monitoring of sleep and vital signs in elderly individuals. * Personalized Health Interventions: By integrating AI with WSN data, this study offers tailored recommendations to improve sleep quality, addressing the specific needs of each individual. * Enhanced Caregiving Support: The system reduces the burden on family caregivers by providing reliable, real-time health monitoring, thereby improving the overall caregiving environment. * Cost-Effective Solution: Utilizing low-cost sensors ensures that the solution is accessible and scalable, making it feasible for widespread adoption in various socioeconomic contexts. * Comprehensive Health Monitoring: This research not only focuses on sleep but also monitors other vital signs, providing a holistic view of the elderly individual's health status. There is a relationship between people's habits and improvements in their rest, which is reflected in the behavior of their vital signs on a daily basis. This work demonstrates the relationships (some strong and others weaker) between the recommendations obtainedfrom a simple sensor network installed at home. These recommendations are based on a threshold analysis algorithm applied by the sensors to assess possible behaviors or improve certain ones for optimal rest. The sensors provide three groups of recommendations that, day by day, show that they can have an impact on the rest and vital signs of an elderly adult. The technical contribution of this document is based on the implementation of a non-invasive sensor network in the home to measure simple parameters such as noise, air quality, movements, and the use of different areas of the house. With these parameters and based on an algorithm, the sensors can provide a series of recommendations that may influence the person's habits and potentially improve their quality of life. Figure 1 provides a comprehensive summary of the research on WSNs for monitoring sleep quality and vital signs in the elderly. The mindmap diagram outlines the background of the study, emphasizing the challenges faced by the aging population regarding health and sleep quality. It details the problem definition, highlighting the health and safety concerns for the elderly at home and the need to identify variables affecting sleep. The justification section underscores the importance of addressing elderly health needs through non-invasive monitoring technologies to improve their quality of life. Objectives include the implementation and data analysis of WSNs to monitor sleep and provide personalized recommendations.