Syracuse started with what it already had—roughly 5,400 Wi-Fi access points generating occupancy signals across campus. That data helped, but only to a point. Accuracy plateaued at about 80%, falling short of the room-level insight the university needed.
To close the gap, Syracuse and JMA piloted IoT enabled thermal sensors and cameras in two buildings. Privacy was key. AI analyzed heat signatures and movement patterns to understand presence and usage. PwC brought the data together. Using Microsoft’s Azure cloud platform, we routed real-time sensor and camera data into Microsoft Fabric, where it was cleansed, standardized, and unified with 10 cross-department data sources. Each data point was mapped to the right room, building, and moment in time. Power BI, Microsoft’s data visualization and reporting tool, translated that foundation into a single, real-time view, while Copilot AI made the data accessible through plain-language questions. A user could ask, “Which room is least used in the lab science building?” and receive an instant, trusted answer: “Room 309 which averages 10% usage of available capacity.”
Altogether, the tools formed one connected, holistic data ecosystem—physical signals in, governed insights out.
With the platform in place, the team put it to work with the SOM initiative. Insights surfaced fast and brought fresh clarity. In one building alone, data revealed that several rooms were used three hours a day or less, with some not used at all. Instead of building new structures, the university could pinpoint low-occupancy root causes and reclaim capacity to use the space it already had.
Syracuse gained reliable, scalable insight into how campus space was actually used—connecting the physical world to AI-governed intelligence. Microsoft Fabric provided a unified data backbone with a single dashboard. AI made it user-friendly. Together, they helped the university surge ahead of peer institutions.