The HIL building will be renovated and extended in five phases while remaining fully operational. During this period, offices, design studios, seminar rooms and entire departments will need to be relocated without disrupting teaching and research. Coordinating these moves across several years and construction phases presents a complex planning challenge.
This input project develops an AI-assisted planning tool that combines spatial building data, temporal construction information, AI-based reasoning and constrained optimisation. It matches changing space requirements with available rooms while considering factors such as capacity, daylight, technical infrastructure, proximity and operational needs.
The interactive tool allows the Living Lab HIL team to inspect and analyse data, develop and compare different relocation scenarios, lock decisions, and immediately assess their impact on subsequent construction phases. By minimising unnecessary moves and temporary fit-outs, the project aims to reduce disruption, costs and material use.
Starting with selected floors and a single construction phase, the model will gradually be expanded to cover the entire HIL building and all five phases. The resulting methodology and software tools could also be applied to other renovation projects where buildings remain in use during construction.
