Research On Indexing Technique Of Moving Objects In Indoor Space

The increasing availability of wireless communication and indoor positioning enables a variety of indoor location-based services. As the core techniques to support the location based services, the index techniques for moving objects has recently been more and more important. The structure of the indoor spaces structure is complex and diverse, however most of the existing moving objects index techniques are for the outdoor environment and difficult to apply directly to the indoor spaces.This paper aims at several kinds of common queries in the indoor environment and puts forward some new indexing techniques and the corresponding query algorithms for indoor space, which can be used in various indoor spaces, such as office buildings, hospitals, hotels, shopping malls and so on. The main research work and contributions are summarized as follows:(1) Previous studies of indoor moving object indices regarded rooms, corridors, stairways and other indoor entities as the same cells and modeled a moving object by a moving point which can not distinguish different semantic meanings between them. In order to solve this problem, a new semantic-based index is proposed for indoor environment, which is consist of semantic layer, object layer and topology layer. Here the index considers the semantic information of the objects and cells, making it possible to meet the requirements of the semantic constraints based queries. In addition, we develop efficient algorithms for two new queries, which are the nearest neighbor queries based on semantic constraints for static indoor cells and moving objects respectively. The conducted experiment demonstrates that the proposed index structure is effective, robust and efficient.(2) According to the problem that ignoring the object in the indoor environment is limited by the access permissions, we increase the consideration of indoor access permission issues. A new indoor index technique and an efficient trajectory query Processing algorithm based on semantics and access permission are proposed. In addition, we also propose an indoor semantic-based model, which gives the formal description of semantics and access permission of indoor cells and moving objects. Extensive experiments demonstrate that the proposed index structure is more effective, robust and efficient than the ACII and RTR-tree from several aspects.(3) Existing moving objects index techniques only focus on the historical data query, and one index structure can support only a single query type. Another novel index is proposed, which supports not only history queries and present queries, but also object queries and range queries. The index is based on graph-based model, and can index two aspects with the object list and bucket list structure, such as the object and spatial-temporal scales. Experimental results show that compared with existing indoor moving object indices, the index we proposed n ot only supports history queries and present queries, but also provides efficient object location queries, trajectory queries and range queries.