Desenvolvimento e avaliação de um aplicativo de realidade aumentada e colaboração: um estudo de caso para análise nutricional

• Ano de defesa: 2022
• Autor(a) principal: Campos, João Pedro Assunção
• Orientador(a): Rieder, Rafael
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade de Passo Fundo
• Programa de Pós-Graduação: Programa de Pós-Graduação em Computação Aplicada
• Departamento: Instituto de Ciências Exatas e Geociências – ICEG
• País: Brasil
• Palavras-chave em Português: Aplicativos móveis; Realidade aumentada; Nutrição - Avaliação
• Área do conhecimento CNPq: CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO
• Link de acesso: http://tede.upf.br:8080/jspui/handle/tede/2321

Different areas have used Augmented Reality resources to integrate virtual elements into our vision of reality, such as data visualization, telecollaboration, and architecture. Collaborative virtual environments allow interaction between two or more participants, regardless of their geographic position, allowing them to share information and manipulate artifacts in real-time. Augmented Reality and Collaboration solutions have explored Computer Vision and Artificial Intelligence as decision support tools. This work presents the development and evaluation of an Augmented Reality application for remote collaborative interaction on mobile devices. As a case study, it is considered a solution aimed at the nutritional analysis of a food diary, capable of helping people construct food choices under professional guidance. The application also executes data requests through the camera and routines for processing images in the cloud. The evaluation considers a pilot study with nine nutritionist-patient pairs to validate the acceptance and usefulness of the technology. The results show a lower level of acceptance by nutritionists, and a satisfactory level by the group of patients, showing better suitability of this group for the application. We identified the lack of well-consolidated Computer Vision and Artificial Intelligence routines that bring satisfactory results to recognizing food images. The Augmented Reality resource proved to be relevant and differential to the study population, showing a potential trend of greater use from the insertion of new content.