Semantic and Inference-Based Techniques for IoT-Enabled Discovery of Escape Routes in Building Information Modeling

The Industry Foundation Classes (IFC) model is a foundational standard used by the construction industry for digital project representation. But in order to give a more thorough and intelligible description of the information found in construction projects, the ifcOWL semantic model was created. The ifcOWL model is expanded upon in this article by adding ideas about sensors and the Internet of Things (IoT). The potential uses of the IFC model in the domains of building management and security are greatly increased by the addition of data pertaining to Internet of Things devices, such as temperature and smoke sensors. The article gives a concrete example of how to create an expert system that can recognise the best escape routes in emergency scenarios, such a fire, by integrating smoke sensor data with IFC structure information. This expansion of the ifcOWL model opens up new avenues for enhancing building safety and creates the framework for a variety of uses, such as predictive maintenance and effective facility management. It is feasible to construct an intelligent environment that responds proactively to continuously changing conditions, assuring increased safety and resource efficiency, by combining data from IoT sensors with comprehensive information about building components.