Uma arquitetura baseada em IoT para sistemas de posicionamento interno como suporte a aplicações de ambiente de vida assistida

• Ano de defesa: 2023
• Autor(a) principal: Mendes, Lucas Ferreira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Arquitetura de software; Fog computing; Internet das coisas; Sistemas de posicionamento interno; Vida assistida pelo ambiente; Software architecture; Internet of things; Internal positioning systems; Ambient assisted living; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://repositorio.ufc.br/handle/riufc/74576

Context-aware Internet of Things (IoT) applications provide a ubiquitous and intelligent environment with services to assist people in their daily life activities. Thus, Internal Positioning Systems (IPS) play an important role in providing indoor location information, which is essential for such applications. This information allows applications to provide personalized data and services according to users’ needs. Thus, there are several application areas for IPS systems in an IoT infrastructure, such as supporting elderly or disabled people in their homes or healthcare environments. This is a research topic that has been gaining a lot of relevance, called Ambient Assisted Living (AAL). However, there is a lack of a well-defined architectural pattern or style, as well as a clear understanding of which non-functional requirements (NFR) are most relevant to applications in this domain. This work proposes a software architecture for IoT-based IPS applications to support AAL systems. A systematic literature review (SLR) was carried out to identify solutions and NFRs to be incorporated into the architecture of such applications. Based on the SLR results, a software architecture was designed and modeled for IoT-based IPS applications using Fog Computing elements to support AAL systems. The proposal was evaluated using the iFogSim simulation environment with regard to latency, network usage, energy consumption, computing costs, and operational costs in the cloud. The proposed approach was compared to a cloud-only deployment. The experimental results show that the proposed architecture significantly reduces latency, energy consumption and operational and computational costs in the cloud and is suitable for real-time response scenarios.