Design of Indoor Aging Environment Monitoring System Based on Multi-sensor Data Fusion
The poor performance of current multi-sensor data fusion algorithms may lead to poor monitoring of indoor aging en-vironments,therefore,an improved multi-sensor data fusion algorithm is proposed.A variable length data fusion algorithm(VLDFA)is proposed to eliminate redundant data.Strategies are proposed to improve the dragonfly algorithm(DA),and the improved DA is combined to improve the BP neural network(BPNN).A multi-sensor data fusion model is constructed.The results show that the accuracy of the model exceeds 98％.In the comparison of temperature error and humidity error monito-ring,the average temperature error of the proposed model is 0.34 ℃,which is superior to the other two models.This indicates that the multi-sensor data fusion effect of the model is relatively good,and it can effectively adjust the living environment of the elderly.
data fusionsensorenvironmental monitoringinterior designBP neural network
万方数据
维普
