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Issue title: Recent Advances in Language & Knowledge Engineering
Guest editors: David Pinto, Beatriz Beltrán and Vivek Singh
Article type: Research Article
Authors: Utsuki-Alexander, Takua | Rios-Martinez, Jorgea; * | Madera, Francisco A.a | Pérez-Espinosa, Humbertob
Affiliations: [a] Facultad de Matemáticas, Universidad Autónoma de Yucatán, México | [b] CICESE-UT3, Nayarit, México
Correspondence: [*] Corresponding author. Jorge Rios-Martinez, Fac. de Matemáticas, UADY, Anillo Periférico Norte, Tablaje Cat. 13615, Colonia Chuburná Hidalgo Inn, Mérida Yucatán. E-mail: [email protected].
Abstract: This work has been focused on the part of the population with hearing impairment who owns a dog and that worries about not listening the dog barks, specially when a risky situation is taking place at home. A survey was carried out on people with deafness problems to find out hazard situations which they are exposed at home. A system prototype was developed to be integrated as a component of ambient intelligence (AmI) for ambient assisted living (AAL) that serves to Hearing Impaired People (HIP). The prototype detects dog barks and notifies users through both a smart mobile app and a visual feedback. It consists of a connection between a Raspberry Pi 3 card and a ReSpeaker Mic Array v2.0 microphone array; a communication module with a smartphone was implemented, which displays written messages or vibrations when receiving notifications. The cylinder-shaped device was designed by the authors and sent it to 3D print with a resin material. The prototype recognized the barking efficiently by using a machine learning model based on Support Vector Machine technique. The prototype was tested with deaf people which were satisfied with precision, signal intensity, and activation of lights.
Keywords: Ambient intelligence, ambient assisted living, dog bark recognition, smart assistant device
DOI: 10.3233/JIFS-219222
Journal: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 5, pp. 4315-4326, 2022
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