Decision Support Tool for Optimizing the Energy Efficient of Buildings

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The construction industry in Canada has been developing automated technologies for smart buildings.At the**individual building level, Building Automation Systems (BAS) is a key technology for smart buildings. These**systems monitor and control building systems, generating a huge amount of data. Whilst this data embeds**imported and critical information about the building dynamics, little has been analyzed to obtain thorough**understanding on the building systems.Current decision support systems are mostly based on prior-knowledge,**which is normally represented by a huge set of equations and empirical relationships, without sufficient**knowledge about the actual systems that can be obtained online through analyzing the operational data and a**self-learning process. This proposed research is aimed to investigate how to best understand the information**embedded in BAS operational data and how to use this understanding to optimize the operation of the building.**In the project, we will integrate a model that can thoroughly analyze BAS operational data from data capturing**systems to provide building managers with a tool for optimizing building operations. Our work will have the**following novel contributions: (1) the decision support system will be capable of correlating the different**dynamic and static variables to provide suggestion for optimization.(2) the decision support system, also will**be able to quantify the lagged or delayed cause-effect relationships among the building parameters. (3) allows**for building manager to simulate predicted performance measures as the result of interventions.In a nut**shell,This research project can increase the competitive edge of the collaborating company in the construction**industry thereby contributing to Canada's economy while protecting environment.In addition, this project will**also be a very useful platform to provide students(HQP) with hands on marketable career oriented experience.