Deep Learning-based Automatic Optimization of Design Smart Home

In this article, the DL (Deep Learning) algorithm, CAD (Computer Aided Design) technology, and other technologies and methods in different fields are comprehensively applied to solve some key problems in the field of smart home design. Specifically, this article constructs an automatic optimization model, which can automatically adjust the control strategy of equipment according to the individual needs and habits of users and realize the automatic control and optimization of equipment. When constructing the automatic optimization model, this article fully considers the issues of security and privacy protection and adopts encryption, access control and other technologies to ensure the security of the system while following the relevant privacy protection laws and standards. The results show that the identification accuracy of this model for user behaviour patterns and habits reaches 95%, which is significantly higher than the traditional behaviour identification methods. Moreover, the design time using this model is shortened by about 40% on average; The design quality score is improved by about 20% on average. In addition, most users give high marks to the smart home design model based on the DL algorithm, with an average score of more than 8.5. This cross-domain comprehensive application mode has great innovation and practical value and can provide a reference for technological innovation and application in other fields. © 2024 U-turn Press LLC, http://www.cad-journal.net.