Context aware indoor route planning using semantic 3D building models with cloud computing

Abstract

In recent years, an increasing number of route planning applications and services have been developed and were brought to the market for different specific use cases. Most of those products are based on the client-server framework that typically combines the database server with the application server for storing the relevant network model, performing the routing calculation, and sending the result back to the client. However, this client-server framework mostly restricts users from changing, modifying, or augmenting the network model with respect to their specific contextual routing requirements. This paper presents a new approach for context aware route planning through coupling of a multilevel cloud-based system architecture with the complex IndoorGML data model, which is an upcoming OGC standard for representing and exchanging semantics, geometry, and topology information of indoor 3D building models. The geometric and logical network model can be rapidly extracted from the IndoorGML data model within the framework of the Multilayered Space-Event Model (MLSEM). Unlike the classical two-tier client-server architecture, the proposed multilevel cloud-based system allows exporting and uploading the network model from a database server to the cloud services that serve as an intermediate system-level to make the exported network model modifiable over the Internet without altering the original data. All changes of the network model with respect to different specific events will be applied in real-time, and the corresponding route planning calculations can then be carried out at the client-side respectively.