A solution for annotating sensor data streams-An industrial use case in building management system

Smart buildings equipped with various building management systems and digital control systems produce enormous amounts of sensor data that can be used to investigate and diagnose operational issues such as unsatisfactory thermal comfort outcomes, excessive energy consumption and/or predicting failures before they occur. However, current building management systems often face the issues with incomplete or unstructured metadata associated with sensor data which prevent such pro-Active, predictive and prescriptive analysis. Currently, building service engineers manually map the sensor data streams to aid their diagnostic process. This process is expensive, ineffective and is also prone to human errors. This paper proposes a novel semi-Automated approach that annotates incoming sensor data streams. We also propose extensions to Project Haystack, a well-known ontology used for naming conventions and taxonomies for building equipment and operational data. We have developed a tool that is currently used by our industry partner and incorporates the proposed automatic annotation approach and maps the data streams to our Haystack-extended ontology. The tool includes an easy to use interface for engineers to easily diagnose issues in mechanical building services. The proposed approach has been validated via both usability and technical evaluation.