A 3D X-tree optimized for Complex Indoor Building Models

Abstract

Studying complex indoor buildings is crucial for population evacuation research in our modern world, where indoor spaces are the primary living environment. However, the existing spatial indexes do not fully align with the unique characteristics of indoor space, leading to a significant bottleneck in the efficiency of searching many space areas. This article introduces a novel model that can efficiently retrieve and update compact three-dimensional indoor space by introducing space X-trees. Our experiments, which have shown that the introduction of X-trees, which can dynamically adjust the size of space nodes, has significantly improved the retrieval speed during the query operation process, underscore the reliability and potential of our new model.