Abstract
World population is ageing due to longer life expectancy worldwide. There is a trend in elderly people to live alone in their habitual residences in spite of health and safety risks. Smart Homes, intelligent environment systems deployed at elderly homes can act as early warning systems trying to forecast the worsening or exacerbation of the resident chronic conditions. Access to sensor datasets is essential for the development of an efficient real smart home. Procurement of such datasets is subject to several restrictions and difficulties. This paper describes the generation of synthetic datasets by means of a simulation model as a suitable alternative previous to the deployment of a real monitoring system. The collection of synthetic datasets will be used during the next project step to train and evaluate activity recognition methods and algorithms.
Highlights
The progressive increase of the older adults proportion over the total population is a phenomenon observed in many countries
The objective of the current research consists of describing an environmental intelligence system simulation model that generates synthetic data sets of sensors
The resident profile of the simulated habitat corresponds to an older adult who lives only in his or her habitual residence, somebody who has some type of chronic illness, but is not limited in his or her movements inside or outside the property
Summary
The progressive increase of the older adults proportion over the total population is a phenomenon observed in many countries. The population of Argentine Republic will experience significant changes between the years 1990 and 2025 It will increase from 33 million to 47 million, and the mortality rate will decrease in a context of constant improvement of health levels, which will be reflected in an increase of 72 to 78 years in the average life expectancy (Torrado, 2004). These changes, joined to a birth rate reduction, can produce a progressive increase of the older people percentage in the total population.
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