Abstract
An accelerated growth in the life expectancy of the elderly is being caused by medical
advancements in recent decades and the decline in birth rates. Therefore, comprehensive care of
the elderly represents a major issue. In addition, loneliness and depression have become major
emotional disorders of high incidence in this sector of the population, causing difficulty in
maintaining an independent life. Thus, this area of attention deserves great attention and
intervention. Hence, it is very important the creation of technological tools that provide solutions
to the aforementioned problem. This study proposes an IoT system using a serverless architecture,
suitable to provide a remote service at home. The system gathers data about the home
environment and the residents. The pilot system presents the monitoring stage, which is able to
collect data from 6 sensors: presence, temperature, humidity, accelerometer, air quality, and the
Fitbit Charge 5. The data is communicated and stored in AWS microservices. In the short term, the
objective is to collect data, monitor, and predict patterns using artificial intelligence of variables
captured by the system from real users. Additionally, the system will be able to generate alarms
when the person is at risk of loneliness or depression to contribute to a rapid intervention. This
system intends to provide a personalized solution, with easy implementation and usability, in
order to reduce the rates of depression and loneliness in elderly people.