Issue |
MATEC Web Conf.
Volume 125, 2017
21st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)
|
|
---|---|---|
Article Number | 04020 | |
Number of page(s) | 8 | |
Section | Computers | |
DOI | https://doi.org/10.1051/matecconf/201712504020 | |
Published online | 04 October 2017 |
Fuzzification of facial movements to generate human-machine interfaces in order to control robots by XMPP internet protocol
1 UNAM Facultad de Estudios Superiores Cuautitlán, ITSE. San, Sebastián Xhala, Cuautitlán Izcalli Edo. De Mex. México
2 UNAM Facultad de Estudios Superiores Cuautitlán, Departamento de Ingeniería. San Sebastián Xhala, Cuautitlán Izclli.
* gsusitto@gmail.com
** itse.enrique@gmail.com
*** dativa19@hotmail.com
The classic human-machine interfaces require mechanical or electronic elements which can be cumbersome or complex in their uses and implementations. As a result, interfaces of such kind can present a rigid communication with devices which we want to control, additionally they may not be a usable tool by people who have lost a body limb and who present different types of corporal disabilities.
In this work is showed the development of a human-machine interface which can control a remote device by the characterization of natural human facial movements employing artificial vision and fuzzy logic.
Due to the characteristics of the proposed interface, it permits that disabled, untrained, and even illiterate persons can use it easily.
This implementation is able to establish a remote communication with any electronic device through the internet by the XMPP protocol, which gives it a dynamism of control over practically any geographical position in the world where internet connection exist, in this way, it is possible to integrate it into the internet of things.
Key words: Human-machine interfaces / Fuzzy control systems / Artificial vision / Internet of things
© 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.