immo!nvest – Die Plattform für Standorte und Immobilien

Tag: Tools

  • CDE market analysis 2024 with a focus on BIM functionalities

    CDE market analysis 2024 with a focus on BIM functionalities

    In the updated white paper, 17 project CDE solutions were analysed in detail. It was found that the user-friendliness of many tools has been improved compared to the previous year in order to support user groups without extensive BIM expertise. Nevertheless, the operation of most CDEs remains complex. Only three tools received full marks in the “usability” criterion, while six tools achieved four out of a possible five points. Almost half of the tools analysed were rated with three or fewer points on the five-point scale, which shows that the expected improvements in terms of usability were only partially achieved.

    Focus on BIM functionalities
    The expansion of BIM functionalities in most CDE solutions is particularly striking. A third of the tools analysed now offer comprehensive functions for complete BIM information management. Significant improvements were noted in BIM viewers in particular, which now offer better graphics and performance for large models. Geometric model checking has also been improved, particularly through the ability to perform clash checks directly in the CDE and visually analyse geometric changes in different project statuses.

    Integration capabilities can be expanded
    Despite this progress, there is still a need to optimise the integration and consistency of information management. The options for checking information are still rarely available and the use of artificial intelligence remains inadequate. The transfer of data between different parties and the integration of executing companies are also often rated as inadequate at present. Only one of the tools analysed allows data to be processed directly in the tool, which highlights the shortcomings in this area.

    About the market analysis
    The CDE market analysis has been conducted annually since spring 2023. In the first update, 17 project CDEs were analysed using around 40 evaluation indicators in the areas of usability, information management, interfaces, file storage, BIM functions and data protection. The analysis provides a comprehensive overview of the current status of technical developments and shows where there is still room for improvement.

  • Intelligent building technology thanks to shared innovation

    Intelligent building technology thanks to shared innovation

    Today, real estate has to meet a multitude of requirements. As a significant driver of CO2 emissions in Switzerland, they play a central role in Swiss climate and energy policy. The requirements for economical and efficient energy use in buildings are correspondingly high. On the other hand, there are ever-increasing demands for safety and comfort on the part of the users – with a simultaneous reduction in the complexity of the application. One component for solving these sometimes seemingly contradictory requirements lies in the digital networking of sensors and devices in buildings.

    Valuable partnerships as innovation drivers
    The cooperation with the Swiss Federal Laboratories for Materials Testing and Research (Empa) in Dübendorf is proving to be an extremely valuable and fruitful partnership with regard to the development of intelligent and sustainable buildings. In the modular research and innovation building NEST, Empa develops and tests technologies, systems and materials together with partners from research, industry and the public sector.

    Bouygues Energies & Services supplied prefabricated HVAC components as part of the NEST unit HiLo (“High Performance – Low Emissions”). Using Building Information Modelling (BIM), a factory and assembly plan including manufacturer’s specifications were created, allowing materials to be ordered directly from the model. In the NEST unit “Sprint”, Empa has successfully put circular construction and “urban mining” into practice. Recycled materials and components were used to create flexible office space in a very short time, while conserving resources.

    In the field of predictive control, learning algorithms enable considerable energy savings compared to conventional, rule-based control algorithms, while at the same time increasing the comfort and user-friendliness of building systems.