Software Architecture for IoT-based Indoor Positioning Systems for Ambient Assisted Living

Indoor positioning is an important element in context-aware applications, especially based on the internet of things (IoT). Elderly people or people with specific needs can benefit from such applications by providing them with an ambient assisted living (AAL). Indoor positioning system (IPS) applications can be deployed under an IoT infrastructure to provide location awareness to other applications, such as AAL solutions. However, software patterns and architectures in the context of IoT applications are still open research topics. This paper proposes a software architecture for IoT-based IPS applications to support AAL systems. We performed a systematic literature review (SLR) to identify solutions and non-functional requirements (NERs) to incorporate into the architecture of these applications. From the SLR results, we developed an architecture for IoT-based IPS applications, using Fog Computing elements, to support AAL systems. We evaluate the architecture using the iFogSim simulation environment regarding latency, network usage, and energy consumption. The proposed approach was compared to a cloud-based deployment. Experimental results show that the proposed fog-based architecture significantly reduces latency, network usage, and operational costs and is suitable for real-time response scenarios. In addition, the energy consumption of cloud data centers is reduced by employing fog computing.