Abstract
Vehicle navigation systems usually simply function by calculating the shortest fastest route over a road network. In contrast, pedestrian navigation can have more diverse concerns. Pedestrians are not constrained to road/path networks; their route may involve going into buildings (where accurate satellite locational signals are not available) and they have different priorities, for example, preferring routes that are quieter or more sheltered from the weather. In addition, there are differences in how people are best directed: pedestrians noticing landmarks such as buildings, doors, and steps rather than junctions and sign posts. Landmarks exist both indoors and outdoors. A system has been developed that uses quick response (QR) codes affixed to registered landmarks allowing users to localise themselves with respect to their route and with navigational instructions given in terms of these landmarks. In addition, the system includes images of each landmark helping users to navigate visually in addition to through textual instructions and route maps. The system runs on a mobile device; the users use the device’s camera to register each landmark’s QR code and so update their position (particularly indoors) and progress through the route itinerary.
Highlights
Location-based services (LBSs) are widely used by mobile users in many situations, such as finding their current location on the map or listing locations of nearby shops or facilities
Seamless indoor and outdoor navigation is one of the most important features which should be handled in a pedestrian navigation application and is still a topic of many research projects [2,3,4,5,6]
This paper focuses on positioning techniques using quick response (QR) codes which have a number of advantages over other methods
Summary
Location-based services (LBSs) are widely used by mobile users in many situations, such as finding their current location on the map or listing locations of nearby shops or facilities. As current turn-by-turn navigational instructions as given to vehicle’s drivers are mostly based on graph-based or street networkbased algorithms, this way of navigating is not fully suitable for pedestrians as they do not solely move on streets [8] Another characteristic of pedestrian movement is the lower speed, in comparison with vehicles. After finding the user location, using GPS for outdoors and QR code positioning for indoors and outdoors, the best path can be calculated and user is given the navigational instructions attaching text and pictures of nearest landmark on the way. Landmarks can be found both indoors and outdoors so this approach can provide navigation services seamlessly and pedestrians see an image of nearest landmark so they can enjoy visiting the campus by getting information about each building while moving.
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