Graph-based indoor navigation system using BIM data and optimization algorithms

This paper presents a smart navigation system that uses Building Information Modeling (BIM) data extracted from Industry Foundation Classes (IFC) files to generate a graph network for efficient path planning. The proposed method focuses on the construction of a graph networks, and the application of optimization algorithms to estimate optimal paths in a building environment. First, we extract relevant information about the building such as spaces, doors. This data serves to construct a graph network that represents the connectivity and relationships between different spaces in the building. Once the graph network is established, optimization algorithms are used to estimate optimal paths for navigation. The proposed method aims to provide accurate and efficient path recommendations, enhancing navigation in the building environment. The performance of our method is evaluated using a larger graph network derived from a real-world building. The results demonstrate the potential of the smart navigation system in achieving reliable path planning.