The operational phase maintains the largest proportion of the building’s lifecycle cost. Moreover, the costs of the operational phase in a building’s lifecycle could be five to seven times higher than the initial investments. However, studies show that energy savings can be between 30-42% by performing occupancy detection in buildings. Therefore, this research paper is focused on assisting and facilitating BIM-based FM integration for occupancy assessment to support various evaluations of a building. The chosen approach to reach the aim of this study is the semantic web technology, considering the advantages it can provide in contrast to other web services such as SOAP or RESTful. A case study was conducted of a room located in the first floor of the school of engineering (JTH) building at Jönköping University. The case study investigated the data structure for the technologies which might be installed in the room later and the geometrical information of it. The used ontology in this study is RealEstateCore (REC). Furthermore, a literature review was conducted to investigate the occupancy information which can be gained by the technologies in that room. Results show that presence, location and count of occupancy can be obtained by CO2, temperature and WiFi positioning technol-ogy. However, every sensor has some exclusive properties and constraints for occupancy detection and estima-tion. Thus, the fusion of various sensors is an advantage as it can significantly increase the efficiency of indoor occupancy assessment. Also, the semantic web provided homogeneous data format that allows for greater in-teroperability between the BIM information and those technologies information. Moreover, REC ontology pro-vided most of the required semantics to describe room A and the CO2 and temperature sensors it might contain. However, the ontology lacked some of the required semantics to satisfy the description of the WiFi positioning system. Thus, extending the ontology to satisfy those required semantics is needed to reach more optimized results of the semantic web.