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Building Tour Plan and Navigation System in Art Museum using Dijkstra Algorithm based on Geo-coded QR codes and Cloud Computing

Building Tour Plan and Navigation System in Art Museum using Dijkstra Algorithm based on Geo-coded QR codes and Cloud Computing

Sawsan Alshattnawi
Copyright: © 2014 |Volume: 6 |Issue: 2 |Pages: 13
ISSN: 1937-965X|EISSN: 1937-9668|EISBN13: 9781466652729|DOI: 10.4018/ijapuc.2014040101
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MLA

Alshattnawi, Sawsan. "Building Tour Plan and Navigation System in Art Museum using Dijkstra Algorithm based on Geo-coded QR codes and Cloud Computing." IJAPUC vol.6, no.2 2014: pp.1-13. http://doi.org/10.4018/ijapuc.2014040101

APA

Alshattnawi, S. (2014). Building Tour Plan and Navigation System in Art Museum using Dijkstra Algorithm based on Geo-coded QR codes and Cloud Computing. International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), 6(2), 1-13. http://doi.org/10.4018/ijapuc.2014040101

Chicago

Alshattnawi, Sawsan. "Building Tour Plan and Navigation System in Art Museum using Dijkstra Algorithm based on Geo-coded QR codes and Cloud Computing," International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC) 6, no.2: 1-13. http://doi.org/10.4018/ijapuc.2014040101

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Abstract

Several technologies have been proposed to support the indoor positioning and navigation. Some of these technologies are combined together to achieve a correct and accurate positioning. The used technologies for indoor navigation such as the RFID and the infrared combined with Wi-Fi have many problems; all these technologies need hardware installation which is costly and restrict, sometimes, the user to have additional hardware on his smartphone. In this paper, we will use Geo-coded QR codes because it is free cost technology for user's positioning. The QR codes have many benefits and it will be used to detect the user's location. A custom tour plan is built according to user preferences. The graph represents the environment and the navigation is provided to the user according to this plan and using only the QR codes. In addition, the cloud infrastructure will be used to store the data and to build the plan, data downloading is done according to user's location and plan. When the graph is dense and the number of nodes is very huge then the telephone may have a problem in processing and search the graph to build the plan. No additional hardware will be installed, the software development process will be easier and the cloud will support the limited mobile resources.

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