Ambient Intelligence for the Internet of Things through Context-Awareness

With the advent of the Internet of Things, new devices feature advanced capabilities that are used in homes, rooms, and offices for better comfort and to save user's time and energy. A complete smart space control system should automatically adjust settings to the user preferences based on data previously collected from such smart things. This paper describes a system that uses environmental data collected from sensors in smart devices to define contexts and user preferences to accomplish this requirement. Contextual data is fed to a context-aware decision engine, composed by a combination of machine learning and data mining techniques. The context-aware decision engine is capable of identifying important data relationships. This allows the use the environment's contextual information to make intelligent control decisions and adjust the environment's settings to user's preferences and reduce the overall power consumption, yielding better services to the user and improving human-technology interaction. We implemented and evaluated the system through a real case study. Results confirm the system's ability to automatically control a smart room with little overhead and latency, while promoting user comfort and energy savings.