A spatial data model for accessibility with indoor temporal changes

Indoor accessibility is often evaluated with the networks extracted from buildings. For instance, circulation networks with depth cost are applied to floor design. A group of data models supports the extraction of indoor networks from buildings, and these networks are widely used to evaluate the accessibility of users. However, the existing cases are mostly devised for static environments, that is, without consideration of dynamic obstacles. This assumption may contradict the fact of daily changes such as pedestrian flow and temporal blockage. Except emergency scenarios, these daily temporal changes can interrupt the continuous movement of a user, and they shall be considered for data modeling of indoor networks. Thus, this article proposes a concise data model which can manage daily temporal changes of accessibility and support related accessibility queries. In the data model, we consider indoor accessibility on two levels of detail, that is, the room and sub-room levels. On the room level, we revise a gravity model to measure the accessibility variation of rooms influenced by temporal obstacles. On the sub-room level, we continuously update obstacle-avoiding networks adapted to temporal obstacles. In this case, the accessibility of a user at any location can be assessed and time-dependent accurate routes can be planned at different moments. We implemented this spatial data model in the DBMS PostgreSQL and its feasibility was demonstrated with the test in a campus building. The data model can be applied to daily checks of user accessibility and can be further incorporated with indoor sensor systems and simulation models to predict accessibility variation.

Automated summary

This article proposes a concise data model for indoor accessibility that can manage daily temporal changes and support related queries. The model considers accessibility at the room and sub-room levels, enabling assessment of user accessibility and planning of time-dependent routes.