Smart Home System Based on Deep Learning Algorithm

Abstract

This paper presents a smart home control system on the strength of human body point cloud data attitude recognition technology. Wherein, the human body point cloud image is obtained by Kinect, and the point cloud image is extracted, and the human body attitude is recognized by Convolutional neural network (CNN) algorithm. The Arduino microprocessor will process the received data to realize the intelligent control of residential electrical appliances in the process. The experimental results show that the system algorithm is able to achieve effective recognition of human attitude and effective control of household appliances and other functions through the analysis and processing of human point cloud images, which features a certain degree of innovation, reliability and practicality.