Open AccessIntelligent Building Data Fusion Algorithm by Using the Internet of Things Technology
Author(s) -
Duo Peng,
Jing Zhao,
Tongtong Xu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2143/1/012030
Subject(s) - sensor fusion , covariance intersection , kalman filter , computer science , algorithm , redundancy (engineering) , data mining , fusion , covariance matrix , fuzzy logic , covariance , artificial intelligence , mathematics , estimation of covariance matrices , statistics , linguistics , philosophy , operating system
Analyzed in this paper based on the Internet of things technology for intelligent building data, redundancy of data fusion are pointed out, based on the dynamic Kalman filter algorithm of multi-sensor fusion, first using the theory of fuzzy and covariance matching technique to adjust the noise covariance of traditional algorithm, combined with weighted minimum variance matrix under the optimal information fusion algorithm of data fusion, Finally, the simulation results show that this algorithm can effectively reduce the redundancy of intelligent data and make the estimated value of data fusion more close to the actual value.