OpenBlue Digital Twin

LEAP: Locations, Events, Assets and People come together with Johnson Control's Digital Twin as the Al-infused foundation to intelligent buildings.

Digital twins help organize and enrich multiple data silos to provide centralized context for your enterprise.

Al infusion across the data context and sources help to enable predictive outcomes in real time.

Using an API-driven approach, OpenBlue Digital Twin is developed on the building blocks of an open architecture. The brick standard is core to our interfaces and data structure.

Prediction: Digital Twins bring together all of the data necessary for predictive algorithms and artificial intelligence systems, from fault predictions on equipment to building utilization and optimization.

Operations: A digital twin of a building gives building managers and occupants a real-time view of the integrated systems of the building.

Cost reduction: Digital twins help buildings operate more efficiently by helping predict and avoid unexpected costs, identify system inefficiencies, and better estimate when replacement parts are needed.

Risk mitigation: Running simulations on a digital twin reduces risks and helps system engineers make better business cases for changes to the system. Experimenting on the digital twin also can help mitigate equipment downtime.

Understanding System Interactions: Digital twins from multiple systems and objects can be combined to better understand how they will interact with each other. This is particularly helpful when systems and products come from different suppliers.

Security: Digital Twins provide a real-time view of the building and its occupants while incorporating historic trend data. The digital twin can be used to highlight “abnormal” actions or events that could portend security issues.