A smart home system based on deep learning

Abstract

The invention discloses a smart home system based on deep learning. Including video recording subsystem, information processing subsystem, intelligent control subsystem, behavioral data analysis subsystem, early warning subsystem. The video recording subsystem uses high-definition cameras and machine learning to realize 24-hour uninterrupted recording of the real-time situation in the user's house; the information processing subsystem performs image data processing and feature value extraction on the recorded video data to facilitate further detection of abnormal behavior data; The convolutional neural network (CNN) algorithm detects abnormal behavior data, divides abnormal behaviors into abnormal levels, and adopts different early warning measures according to the preset abnormal threshold and abnormal level, which greatly guarantees the safety of users; the system also has behavior data The analysis function uses big data analysis technology, artificial intelligence, machine learning and other technologies to analyze the user's daily behavior data, so that the system can serve different users more humanely.

Description

technical field [0001] The invention belongs to the technical field of deep learning, and particularly relates to a smart home system based on deep learning. Background technique [0002] The development of modern science and technology has driven the development of the intelligent equipment industry, and the intelligentization of residential homes will be an important development trend. At present, our society is undergoing rapid changes, and people's lifestyle has gradually moved from focusing on basic living needs such as clothing, food, housing, and transportation to a spiritual level, that is, to pay more attention to the quality of life. In recent years, the emerging smart home market has been in full swing. Combining emerging technologies, it has created functions such as smart lighting control, smart electrical control, and security monitoring systems, providing people with a safe and comfortable living environment. However, many smart homes currently do not have To...

AI Technical Summary

Problems solved by technology

[0003] (1) my country's smart home industry started relatively late, so the current related technologies are still not developed. Now the stability of smart home control system products is not strong, and there are situations such as incompatibility with mobile phone systems. The actual effect and the expected The effect is quite different

[0004] (2) Different companies have different product docking agreements, so there is a phenomenon that smart homes of different brands are not compatible, which greatly restricts consumers' use of smart homes

[0005] (3) Traditional smart home as a monitoring system cannot achieve 24-hour uninterrupted monitoring, and most of them require human intervention and identification of behavior data, which not only slows the identification speed, but also has a high error rate

[0006] In view of this, traditional smart homes with single functions, complex operations, and poor compatibility obviously cannot meet people's needs for smart homes today.

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