Building Space Sensing Algorithm Based on AHP-DS Heterogeneous Data Fusion
The intelligent control system of smart buildings aims to optimize the comfort and energy distribution of building space,and has received widespread attention in recent years.Building space occupancy information plays an important role in the decision-making of smart building management systems.The existing methods for perceiving building space occupancy have not yet proposed effective solutions to the problem of integrating multi-source data with uncertainty and conflict.Based on this,this paper introduces D-S evidence theory into building space occupancy prediction and constructs a mass function based on building space occupancy detection to ensure the performance of D-S evidence theory in this application.In addition,this article introduces the Analytic Hierarchy Process(AHP)to solve the problem of mismeasurement of building space occupancy caused by conflicts between multiple heterogeneous data sources,in order to improve perception accuracy and system performance.
smart buildingsoccupancy detectionD-S evidence theorymulti-source heterogeneous data fusion
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