Implementation of Distributed Smart House Using Multi-Layer AI

Abstract

In recent years, research and development on smart houses that intelligently control various indoor devices (lighting, air-conditioning, etc.) have been active due to advances in communication and machine learning technology. In this paper, we propose and implement a system to realize novel smart house. The proposed system has two major features. One is various devices required for the system (sensing, processing, and actuation). It is an architecture called “distributed smart house” that disperses and arranges the distributed inference devices. In the other, the reasoners necessary for intelligent control are distributed within the device, local network, and cloud network. It is a “multilayer AI” that is implemented by dividing it into multiple layers. Due to these features, it is possible to construct a smart home system flexibly and efficiently. As for the system to be implemented, we used voice recognition using Google Cloud Speech and human posture recognition using Jetson TX2 placed in the local network. In addition, we used ROS as the software platform. This makes it possible to easily expand future functions and improve performance.