Towards a Context Awareness System Using IoT, AI, and Big Data Technologies

Abstract

The intensive use of connected objects in smart homes has led to a growing demand for intelligent systems for the automatic and simplified control of daily life. These systems seek to simplify the control of functions such as lighting, heating, security, and appliance operation, all of which contribute to household comfort and energy efficiency. In this view, context, which encompasses information about the physical environment, user preferences, ongoing activities, and other relevant variables, can greatly enhance the ability of smart home systems to anticipate and respond to the needs of occupants. However, integrating context in smart home systems presents significant technical and conceptual challenges. One key challenge is the development of accurate and dynamic context models that can consider diverse and changing variables. Additionally, the need to process large volumes of data from multiple IoT devices in real-time requires robust and scalable architectures. This study focuses on creating a context-aware system that leverages AI, IoT, and big data technologies to simplify home function control, anticipate user needs, and address the challenges of context modeling and real-time data processing, ultimately contributing to smarter, more responsive interactions between users and their home environment. We start our study by exploring the domain of context-awareness and architectures related to IoT, Big Data, and AI. We then propose a design of an innovative architecture for a context-aware application for smart homes. We finally test the feasibility and performance of the proposed architecture in a real environment.