Topological analysis in indoor shopping mall using ontology

Recently, human activities have expanded from outdoor spaces to indoor spaces since a lot of complex buildings were constructed over the world. Especially, visitors in a shopping mall would like to receive specific information of interest regarding various shopping-related activities as well as shopping itself. However, when it comes to providing the information, existing guide services have some drawbacks. Firstly, the existing services cannot provide visitors with the information of other stores simply and promptly on the current location. Secondly, the services have difficulties in representation and share of the shopping-related knowledge, and in providing inferred information. Thus, the purpose of this study is to develop a method that allows topological analysis utilizing ontology technique around the current position in such shopping mall in order to provide shopping-related information. For this, the shopping activity ontology model is designed, and based on the ontology model, inferencing rules are defined in order to extract the information of interest efficiently through semantic queries. Also, a geocoding method in indoor spaces is used regarding the current location, and optimal routing analysis, which is one of topological analysis, is applied with the result from the semantic queries. As a result, an Android application is developed for 3D visualization and user interface.