Statistical Study of User Perception of Smart Homes during Vital Signal Monitoring with an Energy-Saving Algorithm  
[PERSON]  
1 Facultad de Ingenieria, Universidad Panamericana, [PERSON] 49, Zapopan 45010, Mexico  
2 School of Engineering and Science, Tecnologico de Monterrey, Monterrey 64849, Mexico  
3 Facultad de Ingenieria, Universidad Panamericana, [PERSON] 101, Aguascalientes 20290, Mexico  
4 Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy  
4 Correspondence: [EMAIL_ADDRESS]  
[PERSON]  
2 School of Engineering and Science, Tecnologico de Monterrey, Monterrey 64849, Mexico
Older people acquire certain routines in their daily lives, which allows a sensor network to \"learn\" some activities depending on the specific day or time. In this way, the network is capable of managing the behavioral patterns observed in the user, optimizing their correct interpretation through the information obtained by the sensors installed at home [5]. Undoubtedly, sensors play a major role in the prompt detection of behaviors related to motor or cognitive problems. Internet access has become a primary need for human development because multiple activities currently require a connection to the web. Education and work are the essential activities that use this service, and they constitute fundamental pillars in the economic development of our society. Highly performant solutions have been generated using WiFi standards and mesh communication technologies [6]. The current global crisis caused by the COVID-19 pandemic has imminently hastened the virtualization of activities and, therefore, the use of Internet services [7]. Older adults are currently at greater risk of blackouts or accidents at home [8]. The World Health Organization (WHO) reports that falls are the second leading cause of death from accidental or unintentional injuries. Those over 65 exhibit the highest prevalence of fatal falls [9]. The technology necessary to remotely detect behavioral changes in real-time is based on recognizing activities from the information gathered from sensors. Public health services are facing shrinking budgets and an increasing pressure to cut costs. Considering the scarcity of specialized healthcare places for the elderly, the solution is to keep them at their own home [10]. For the elderly, representing a significant part of social expenses, it means the obligation to live alone and independently at their homes, with all the risks that this entails. To respond to these new needs, research has been paramount for the meaningful development of telemedicine systems over the last 20 years. These systems are designed to offer greater security to people that live alone at home, including those in specialized centers, and represent a valuable tool for caregivers [11]. Information and Communication Technologies (ICT) have become essential for promoting independent living and improving the quality of life of the elderly. These people experience a progressive loss of functions due to their age or chronic diseases, which makes it difficult for them to carry out daily tasks, forcing them to depend on third parties or, at least, periodically inform someone else about their health status. Digital home is a new technological domain deployed in places of residence to increase security and improve comfort and the ease of communications. All this is achieved with the use of telecommunications networks, the integration of services, and the interconnection of equipment and facilities [12]. Our work is framed in this context. In this study, we analyze the impacts of a sensor network on the life of an older adult at home [13], optimizing its performance in favor of energy savings. The originality of our study lies in a proposed algorithm for a simple sensor network for home care. This algorithm is characterized by its low energy performance for this type of application. It bases its low consumption on the hierarchy and clustering of the sensors according to a person's habits.