MATEC Web Conf.
Volume 125, 201721st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)
|Number of page(s)||5|
|Published online||04 October 2017|
An IoT−based system that aids learning from human behavior: A potential application for the care of the elderly
1 TECNALIA Research & Innovation, Sustainable Construction Division, Area Anardi 5, 20730 Azpeitia, Gipuzkoa, Spain
2 Universidad Politécnica de Madrid, ETSII, PMQ Research Group, José Gutierrez Abascal 2, 28006 Madrid, Spain
* Corresponding author: firstname.lastname@example.org
The goal of this paper is to describe the way of taking advantage of the non-intrusive indoor air quality monitoring system by using data oriented modeling technologies to determine specific human behaviors. The specific goal is to determine when a human presence occurs in a specific room, while the objective is to extend the use of the existing indoor air quality monitoring system to provide a higher level aspect of the house usage. Different models have been trained by means of machine learning algorithms using the available temperature, relative humidity and CO2 levels to determine binary occupation. The paper will discuss the overall acceptable quality provided by those classifiers when operating over new data not previously seen. Therefore, a recommendation on how to proceed is provided, as well as the confidence level regarding the new created knowledge. Such knowledge could bring additional opportunities in the care of the elderly for specific diseases that are usually accompanied by changes in patterns of behavior.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.