<![CDATA[In todayâs technology, when costs of time, energy and human resources are considered, efficient use of resources provides significant advantages over many aspects. In light of this, role of building automation systems, which are a part of smart cities, become even more important. At the very core of building automation systems there lies the efficient use of resources and systems for providing comfortable living situations. With the advancement in network technology, systems can be programmed smartly and any malfunctions on the systems can be detected and fixed remotely. In addition to that, all data gathered during this process can be analyzed to create machine learning solutions for a system to control and program itself. In this work, we pulled the sensor data and developed an interface to do analysis. Our aim is to understand how the system behaves. This interface will be the basis of our work on developing machine learning algorithms to predict system behaviour for programming the system for energy.]]>
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