Ambient Intelligence for Smart Home using The Internet of Things

This article presents an ambience intelligence application for smart home systems for efficient use of electricity, enhance comfort zone, independence of living and security. The system integrates smart home occupant's identification, sensors-actuators deployment, a gateway Hub, machine learning, and cloud computing components to realize the objectives of smart living. A Mobile phone MAC-address based occupant identification and machine learning algorithms are proposed to address the multiple smart home occupant problems and an instant user control versus rule-based control conflicts. Results show that machine learning algorithm could learn the ambience preferences of multiple occupants when trained on a large enough dataset. The proposed system can implement ambient intelligence applications in smart home.