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The title of the thesis: Bridging workplace flexibility and building efficiency: the role of high-resolution occupancy data

Thesis defender: Kiia Einola
Opponent: Dr. Suvi Nenonen, University of Helsinki, Finland
Custos: Prof. Jaakko Ketomäki, Aalto University School of Electrical Engineering

Flexible working practices, such as remote and hybrid work, have made office occupancy more variable and less predictable. This shift presents new challenges for facility managers, office users, and building systems. Facility managers must respond to fluctuating occupancy levels when planning and managing spaces, users may struggle to find available desks on busier days, and building systems may consume unnecessary energy if they operate based on higher-than-actual occupancy levels.

This dissertation investigates how high-resolution occupancy data can support flexible work environments by providing a more accurate understanding of how office spaces are used in practice. By analysing occupancy patterns across space and time, the research demonstrates how detailed insights can inform more effective space planning, assist users in navigating flexible offices, and enable building systems to respond more efficiently to real demand.

A key contribution of this work is the identification of passive occupancy as an important but often overlooked condition. Passive occupancy occurs when a desk is not physically occupied but remains unavailable due to personal belongings left behind. The research shows that this behaviour has a significant impact on space utilisation and perceived desk availability. When passive occupancy was taken into account, the calculated space utilisation increased to nearly twice the level obtained when only active occupancy detected by the sensors was considered. In addition, incorporating passive occupancy improved the accuracy of the sensor data by 17 percentage points.

Overall, the findings highlight the practical value of high-resolution occupancy data for organisations aiming to optimise space use, enhance user experience, and reduce energy consumption. The dissertation also emphasises the importance of user acceptance and economic feasibility when considering the real-world implementation of such data collection.

Key words: office occupancy, space utilization, flexible work, passive occupancy

Thesis available for public display 7 days prior to the defence at .