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Purpose The purpose of this paper is to provide local environmental information to raise community’s environmental awareness, as a cornerstone to improve the quality of the built environment. Next to that, it provides environmental information to professionals and academia in the fields of urbanism and urban microclimate, making it available for reuse. Design/methodology/approach The wireless sensor network (WSN) consists of sensor platforms deployed at fixed locations in the urban environment, measuring temperature, humidity, noise and air quality. Measurements are transferred to a server via long range wide area network (LoRaWAN). Data are also processed and publicly disseminated via the server. The WSN is made interactive as to increase user involvement, i.e. people who pass by a physical sensor in the city can interact with the sensor platform and request specific environmental data in near real time. Findings Microclimate phenomena such as temperature, humidity and air quality can be successfully measured with a WSN. Noise measurements are less suitable to send over LoRaWAN due to high temporal variations. Research limitations/implications Further testing and development of the sensor modules is needed to ensure consistent measurements and data quality. Practical implications Due to time and budget limitations for the project group, it was not possible to gather reliable data for noise and air quality. Therefore, conclusions on the effect of the measurements on the built environment cannot currently be drawn. Originality/value An autonomously working low-cost low-energy WSN gathering near real-time environmental data is successfully deployed. Ensuring data quality of the measurement results is subject for upcoming research.

The trend of increased usage of both BIM and 3D GIS and the similarity between the two has led to an increase in the overlap between them. A key application of such overlap is providing geospatial context data for BIM models through importing 3D GIS-data to BIM software to help in different design-related issues. However, this is currently difficult because of the lack of support in BIM software for the formats and data models of 3D Geo-information. This paper deals with this issue by developing and implementing a methodology to convert the common open 3D city model data model into the most common open BIM data format, namely CityGML (Gröger et al., 2012) to IFC (buildingsmart, 2019b). For the aim of this study, the two standards are divided into 5 comparable subparts: Semantics, Geometry, Geographical coordinates, Topology, and Encoding. The characteristics of each of these subparts are studied and a conversion method is proposed for each of them from the former standard to the latter. This is done by performing a semantic and geometrical mapping between the two standards, converting the georeferencing from global to local, converting the encoding that the two standards use from XML to STEP, and deciding which topological relations are to be retained. A prototype implementation has been created using Python to combine the above tasks. The work presented in this paper can provide a foundation for future work in converting CityGML to IFC. It provides an insight into the relationship between the two standards and a methodology for the conversion from one to the other, and the process of developing software to perform such conversion. This is done in a way that can be extended for future specific needs.