 Optimization of Network Home Management System Based on Big DataWei Shan and Zaoli Yang Mathematical Problems in Engineering, 2022, vol. 2022, 1-8 Abstract: Network home has become a research hotspot in today’s society, and it can improve the comfort, safety, and convenience of people’s lives. The traditional network home model only makes certain actions to the home system according to people’s instructions, and it is difficult to realize the intelligence of network home. This also limits the security and convenience of an online home. This study makes full use of the advantages of big data technology in processing nonlinear data, and applies the convolutional neural network (CNN) method and long and short-term memory (LSTM) neural network method to the network home system. CNN can be used to extract people’s behavior information, and LSTM can be used to extract people’s speech features. CNN method can establish the relationship between people’s behavior information, speech information, and network home management system. At the same time, this research mainly analyzes the lighting system, home appliance system, security system, and floor heating system in the network home system. The results show that the CNN-LSTM method has high accuracy in predicting the four systems of network home. The largest prediction error is only 2.78%, and this part of the error comes from the prediction of the home appliance system. The smallest prediction error is only 0.98%. Date: 2022 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:5795021 DOI: 10.1155/2022/5795021 Access Statistics for this article More articles in Mathematical Problems in Engineering from Hindawi |
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