Indoor Framework: Data Structure, Navigation, Routing, and Trajectories in Indoor Spaces

Related Works And Background

The mobility of objects in spatial environments requires more frequent database updates. In outside environments, for instance, vehicles such as trucks, aircraft, and buses are moving at varying speeds (Alamri et al., 2013b; Rahman & Kim, 2012). A lot of research effort has gone into resolving the issue regarding the frequency with which moving objects are updated and addressing a wide range of spatial concerns in outdoor areas. For instance, the TPR-tree (Time Parameterized R-tree) uses the R*-tree definition to handle the data structure of spatial objects (Tao et al., 2003). Many others have adopted the definition of the TPR-tree (Tao et al., 2003; Alamri et al., 2013a). Moreover, other works focus on building a data structure for spatial objects to satisfy the variety of indoor queries (Alamri et al., 2020). The most popular spatial data structures are Euclidean space, spatial road network, and cellular space (Susanti et al., 2018). Cellular space refers to indoor spaces that contain space-related objects. In cellular spaces, queries about spatial objects are based primarily on cellular notations, such as “Which objects are in room 87?” The cell/room number is then the identifier of the target location (Dionti et al., 2017).