Research of Prediction of Intelligent Lighting System Maintainability Based on GMM
With the continuous development of intelligent construction in China,most front-end hardware devices can now achieve intelligent control through various communication technologies,including smart lighting equipment.The application of smart lighting equipment is characterized by a large number and wide distribution.During long-term operation,these devices are prone to sudden accidents and aging.Existing technologies cannot determine equipment abnormalities in real time,leading to the need for regular inspections and maintenance.Therefore,a GMM-based maintenance prediction model for smart lighting systems is proposed,using the ReliefF algorithm for feature selection.This model effectively reduces the maintenance frequency of smart lighting equipment,ensuring the stability and safety of its normal operation.Comparative experiments have shown better results,proving the effectiveness and feasibility of the method.It reduces labor costs to some extent and provides an experimental foundation and theoretical basis for further guidance in intelligent construction.
NETL
NSTL
万方数据
