Evaluation of Open Data Models for the Exchange of Sensor Data in Cognitive Building

Buildings become constantly smarter during the last decades. Using sensors, varying information of the building environment, e.g. temperature, energy consumption or building utilization, can be measured and used to improve the user experience. The Internet of Thing (IoT) paradigm increases the number of sources of information from which collect data. However, to store data coming from different sensor systems is still a challenging task. The paper presents an approach for the linkage of sensor data with a Building Information Modeling (BIM)-based building model using the open data format Industry Foundation Classes (IFC). First, based on a research about sensor data and Open Data Models (ODM), the state of the art of possibilities storing sensor data with ODM is described, current advantages and disadvantages are outlined. As an example of the current use of sensor data, the eLUX Lab at the University of Brescia is described. The eLUX lab offers an approach for the connection of sensor data with BIM models. Its usability was proved in case studies and shows, that it is a solid working concept of a static connection. Nevertheless, it can be improved in some aspects. Apart from these optimization opportunities, the concept seems to be well thought out. Thus, it will serve as a basis for the following composed dynamic approach. Especially, the sensor objects of the building information model are well suited for the continued use. With focus on the usage of open data formats, a new dynamic method of linkage using a server platform is developed. Therefore, requirements for the programming of an agent accessing the server and saving the latest sensor data into the IFC file are set. Finally, the general suitability of IFC for the storage and usage of sensor data is described and prospects for the further developments of this approach are given.