An End-to-End Implementation of a Service-Oriented Architecture for Data-Driven Smart Buildings

Abstract

Buildings connect with multiple information systems like Building Management Systems (BMS), Energy Management Systems (EMS), IoT devices, Building Information Models (BIM), the electricity grid, weather services, etc. Data-driven smart building software demands seamless integration of the above systems and their data. The lack of a system architecture with well-defined Application Programming Interfaces (APIs) poses a significant challenge for developing reusable, modular and scalable applications. This article presents a service-oriented system architecture designed with data-driven smart buildings in mind. The architecture relies on the Zachman framework and consists of seven service categories: 1) existing business applications, 2) new microservice-based applications, 3) databases, 4) integration software, 5) infrastructure services, 6) shared services, and 7) user interfaces. It closely resembles the MACH architectural principles: Microservices, API-first, Cloud-based components, and Headless principles. This architecture is implemented as a proof-of-concept, including three smart building applications. These include a Digital Twin application integrating sensor data with a BIM model, a web application merging real-time sensor data with semantic building graphs, and a data exploration tool using sensor data, the Brick ontology, and Grafana dashboards. Future implementations include real-time control applications such as Model Predictive Control (MPC). The proposed architecture and its implementations provide a blueprint for a reusable, modular, and scalable architecture in the smart building domain.

Keywords

• Building Information Modeling
• data-driven buildings
• data integration
• IoT
• linked building data
• microservices