A Building Automation System is a system that provides automatic control of many of the tasks required for running a building’s heating, ventilation, air conditioning, electrical, lighting, security, and other interrelated systems. It aims to improve the efficiency of all these systems, keep occupants comfortable, reduce energy consumption, lower operating and management costs, etc.
Ontotext’s GraphDB RDF database for knowledge graphs enabled two leading multinational BAS manufacturers to leverage the Brick metadata schema for buildings. This allowed them to improve the tooling they provided for the modeling and management of their BAS.
A couple of leading multinational Building Automation Systems (BAS) manufacturers wanted to improve the tooling they offered for the modeling and management of their systems. They needed a solution that would make it easy for BAS integrators to create a virtual model that provided a global view over the diverse information managed in these systems.
Building automation systems have become increasingly complex, integrating more and more systems such as HVAC, lighting, fire safety, security, and others. Often using Internet of Things (IoT) devices, every system has proprietary input and output devices connected to a controller and a UI, and these components work together to gather, process, and update real-time information. Each layer of BAS has a role and builds upon the previous layer to provide more functionality and automation.
The problem is that the individual systems are often modeled differently and remain isolated from each other. So, every time something needs to be changed in one system, for example, expanding a building, the change has to be reflected in several different systems. As a result, BAS manufacturers find it difficult to gain a global view over all these segmented models.
The BAS manufacturers chose to use the Brick schema to represent all BAS components and their complex interactions. Brick is an open-source schema, using RDF (Resource Description Framework) to describe assets, with standardized semantic descriptions of physical and virtual assets in buildings and the relationships between them. It was designed by leaders in the field, including Johnson Controls and Schneider Electric, and its modeling support covers HVAC, lighting, electrical, sensors, spatial, and other systems.
To maximize collaboration and data visualization, these BAS manufacturers required an RDF database to house the semantic model and the data. Our clients selected Ontotext GraphDB (RDF database engine for knowledge graph management) as the best choice to take advantage of the Brick schema. Resembling real-world building automation systems and relationships very closely, the RDF graph model provided the best framework for data integration, linking, reuse, and analysis.
Thanks to its robustness, standard compliance, and excellent query performance, GraphDB brings the required business critical stability. It makes it easy for BAS integrators to set up, load data, monitor differences in the systems, compare different versions of the model, and more.
Using standardized Brick descriptions of all assets provides a global view of the building automation systems manufactured by the companies. This contextual awareness makes it easy for BAS integrators to model these systems and make changes from a central place. With GraphDB as their preferred RDF database for the Brick schema, the BAS manufacturers now have efficient, flexible, and reliable tooling as part of their offering.
Ontotext adapted the packaging of GraphDB to comply with the specific technological, deployment, and business models as well as the specific licensing plans of the BAS manufacturers. GraphDB provided powerful tooling for leveraging the functionalities of the Brick schema and the benefits of the graph model. Its predictable performance across a wide range of workloads ensured great efficiency and stability. This facilitated the work of BAS integrators when modeling and managing BAS manufactured by the two customers.
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