Sapientia: a smart campus model that promotes flexibility

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Brand, Bianca dos Santos
Orientador(a): Rigo, Sandro José
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade do Vale do Rio dos Sinos
Programa de Pós-Graduação: Programa de Pós-Graduação em Computação Aplicada
Departamento: Escola Politécnica
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://www.repositorio.jesuita.org.br/handle/UNISINOS/9213
Resumo: Nowadays, the expansion of IoT and ICT technologies is observed, together with the growing interest in the solutions offered by the Intelligent Concepts applied to the context of cities and other spaces. However, it was identified in the literature the lack of flexible models that also included accessibility aspects, besides being able to incorporate existing hardware and software solutions, which motivates this research to address such issues and challenges. Thus we propose the Sapientia Smart Campus model, which promotes flexibility, also including accessibility aspects as well, with the independence of contexts and being able to incorporate existing solutions. Such features are possible due to the architecture of the model, composed of layers that facilitate the management and update of the technologies used, besides facilitating the insertion of accessibility aspects and the integration of new and existing applications. The model implementation evidences this, involving hardware and software infrastructure, by allowing the same technology to have different applications and new technologies to be easily incorporated. Experiments were carried out with a mobile application that incorporated accessibility aspects of the model and the collection of user behavior information on campus. Also, a data analysis unit was developed, containing Artificial Intelligence resources that perform clustering and time series analysis in the collected data. In addition, it was incorporated existing applications to the developed infrastructure, thus demonstrating the flexibility of the model.