Research on smart home environment system with multisensor and three level data fusion DOI

Shaopeng Yu,

Chenyu Liu, Li Liu

et al.

Published: April 9, 2025

Abstract A three level data fusion architecture is proposed to facilitate the real-time detection and intelligent adjustment of living environment, which based on fuzzy theory, back propagation (BP) neural network, Dempster-Shafer (D-S) evidence weight optimization method. The machine learning algorithm used judge environment with historical data, so that current can make users feel comfortable, obtain preferred environmental parameter values residents. According habits residents, transformation parameters from static dynamic be achieved efficiently, feedback realized. test results show system has a accuracy 99.96% fast response speed good reliability performance, as well adaptive capabilities. Therefore, not only provides convenience for users, but also reduces safety hazards in home environment.

Language: Английский

Research on smart home environment system with multisensor and three level data fusion DOI

Shaopeng Yu,

Chenyu Liu, Li Liu

et al.

Published: April 9, 2025

Abstract A three level data fusion architecture is proposed to facilitate the real-time detection and intelligent adjustment of living environment, which based on fuzzy theory, back propagation (BP) neural network, Dempster-Shafer (D-S) evidence weight optimization method. The machine learning algorithm used judge environment with historical data, so that current can make users feel comfortable, obtain preferred environmental parameter values residents. According habits residents, transformation parameters from static dynamic be achieved efficiently, feedback realized. test results show system has a accuracy 99.96% fast response speed good reliability performance, as well adaptive capabilities. Therefore, not only provides convenience for users, but also reduces safety hazards in home environment.

Language: Английский

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