||Ofﬁce buildings are key energy consumers and thus require attention to achieve efﬁcient operation. While individual ofﬁce spaces are dynamically used, current building automation does not receive information on utilisation that could be used to adaptively adjust energy consumption. In this work, we propose an approach to estimate people count per ofﬁce space using distributed strategically placed PIR sensors and algorithms that can process the distributed sensor information. We detail our sensing node and evaluate its performance in an ofﬁce installation. A sensor model was subsequently used in a ﬂoor-wide simulation of realistic occupant behaviours to investigate two algorithms to estimate people count per ofﬁce space. The occupant behaviour simulations confirmed that our estimation algorithms can accurately predict people count in different ofﬁce use scenarios. The errors introduced by the PIR masking time after a detection can be partially compensated when using distributed sensor information. Our approach can be used for dynamic, occupancy-dependent lighting, climate, and appliances control of ofﬁce spaces.