Campus Space Optimization through Data and AI

Higher education institutions need better ways to understand how academic spaces are actually used so they can make smarter decisions about labs, software, and hardware investments. This poster shows how we combined login session data, weekly lab schedules, application telemetry, and machine resource baselines to measure lab utilization, identify which spaces are near capacity, and determine whether labs are provisioned appropriately for the work students are doing. The analysis reveals where seat-hours are concentrated, which applications and courses drive demand, and which labs may be underused or overprovisioned. It also shows how AI can help turn raw operational data into planning-ready insights more quickly by parsing, aggregating, correlating, and visualizing multiple data sources. Attendees will see a practical example of how institutions can use data and AI together to support space optimization, refresh planning, and better alignment between academic demand and campus IT resources.