Intelligent Querying for Implementing Building Aggregation Pipelines

Sensors, smart meters and IoT devices are key parts of the Building Information Systems. The amount of data generated from these sources is vast and the need for storage, fusion with secondary datasets (such as weather data) and aggregations has arisen in order to enhance building automation control activities. These data are stored on various data-sources, relational and non-relational, using different data formats. The combination of data coming from multiple data-sources constitutes a hard task, since each database uses different query language and structure. However, by combining all the available data-sources, it would be beneficial to reduce the volume of data during the training process. This paper presents an architecture that combines data from multiple data-sources (Databases, Object Storages, Building Information Systems) and create pipelines for aggregating the overall data.