The University of Portsmouth operates from a multi-building urban campus in the centre of Portsmouth, with a diverse estate comprising teaching spaces, laboratories, offices, research facilities, student services and social spaces. The University does not currently have a systematic, data-driven understanding of how its buildings and rooms are used. Timetabling data tells us when spaces are scheduled, but not whether anyone is in them, or how many people are present compared to room capacity, and whilst we monitor attendance in certain sessions this relies on physical registration by identity card and reader resulting in a high degree of inaccuracy. This gap has two practical consequences: • Energy waste: spaces are being heated, lit and ventilated regardless of whether they are occu-pied. Without occupancy data, the University cannot identify which spaces are consuming energy unnecessarily or target interventions effectively. • Space planning based on assumptions: decisions about room allocation, timetabling, and future estate investment are made without reliable utilisation evidence. The University needs accurate, granular data to make better decisions about how its estate is used. The University seeks to address both problems by deploying an occupancy sensor and monitoring solution across an initial set of campus buildings. The solution will provide real-time and historical data on room-level occupancy and headcount, accessible through a web-based reporting portal and integrated with the University´s existing data analytics environment.