Use este identificador para citar ou linkar para este item: http://repositorio.ufes.br/handle/10/10942
Título: A Human-Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things
Autor(es): Bissoli, Alexandre Luís Cardoso
Orientador: Bastos Filho, Teodiano Freire
Coorientador: Encarnação, Lucas Frizera
Data do documento: 20-Fev-2019
Editor: Universidade Federal do Espírito Santo
Resumo: People with severe disabilities may have difficulties when interacting with their home devices, due to the limitations inherent to their disability. Simple home activities may be even impossible for this group of people. Although many works have been devoted to proposing new assistive technologies to improve the lives of people with disabilities, some studies have found that the abandonment of such technologies is quite high. In this sense, this work presents a new and useful assistive system based on eye tracking for controlling and monitoring a smart home based on internet of things, which was developed following concepts of user-centered design and usability. With this system, a person with severe disabilities was able to control everyday equipment of her residence, such as lamps, television, fan and radio. In addition, her caregiver was able to monitor remotely, by internet, her use of the system in real time. Additionally, the user interface developed here has some functionalities that allowed improving the usability of the system as a whole. The experiments were divided into two steps. In the first step, the assistive system was assembled in an actual home, where tests were conducted with 29 participants without disabilities (group of able-bodied participants). In the second step, the system was tested with online monitoring, for seven days, by a person with severe disability (end-user), in her own home, not only to increase convenience and comfort, but also so that the system could be tested where it would in fact be used. At the end of both steps, all the participants answered the SUS questionnaire, which showed that both the group of able-bodied participants and the person with severe disabilities evaluated the assistive system with a mean of 89.9 and 92.5, respectively.Keywords:Human-Machine Interface (HMI); Human-Computer Interaction (HCI); Smart Home; Eye Tracking; Assistive Technology; Usability Evaluation; User-Centered Design (UCD); Home Automation; Internet of Things (IoT).
URI: http://repositorio.ufes.br/handle/10/10942
Aparece nas coleções:PPGEE - Teses de doutorado

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
tese_10849_PhD Thesis - Alexandre Bissoli - Versão Final Revisada - Assinada.pdf3.44 MBAdobe PDFVisualizar/Abrir


Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.