Spatial uncertainty management in pedestrian navigation - Basiri, Anahid; Amirian, Pouria; Winstanley, Adam; Moore, Terry; Hill, Chris (Springer International Publishing, 2014)
Location-based services use location as contextual data to exclude irrelevant services from users. However almost all positioning technologies can only provide a location with a certain degree of accuracy. It is necessary to have a framework which can handle this inaccuracy and other uncertainties in order to provide a better and more adaptive service. In addition to positioning inaccuracy, location-based services can suffer from other aspects of uncertainty, such as data incompleteness and inconsistency. There is no universal positioning technique which can provide the position of the user seamlessly indoors and outdoors with an acceptable degree of accuracy. Consequently, it is possible to lose the position of the user for a period of time. To avoid this, some systems use more than one positioning technology, each having incomplete datasets; however they still may produce mutually inconsistent data. If an uncertain spatial dataset is stored and analysed in a framework which cannot handle uncertainty, some aspects of the input data may be missed and the outcome may not be fully applicable in real world applications. This chapter aims at developing a rough set-theory-based navigation application which can provide navigational instructions to users by taking spatial uncertainty into account.