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 (Computer Science Department, Yarmouk University, Irbid, Jordan)
DOI: 10.4018/ijapuc.2014040101
OnDemand PDF Download:
List Price: $37.50


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.
Article Preview


A round in an art museum requires the user to concentrate on the exposed objects and the information about each object. In addition, he must be aware of the path to follow and the path that was already visited to avoid repetition. Reading also may bother the user and it is better to get audio information in such cases. Smartphones have got their popularity in this case to allow the visitors to concentrate more on the exposed objects by providing the information according to user's location and providing a plan adapted to his preferences.

The navigation systems used in outdoor such as GPS is a powerful system but it is not effective for indoor because of the obstacles encounter the signals traveling from sender to the receiving satellites (Fallah,N. et al., 2013; Barberis, C., et al., 2013; Baus, J., et al. 2002). For this reason, different technologies have been proposed to help the user to navigate inside buildings. All these systems need hardware installation which is costly and restrict, sometimes, the user to have additional hardware on his smart phone.

Our contribution in this paper is twofold: the first one is to build a navigation system and detect the user location by using a non-costly technology and the second is to use the cloud infrastructure to support the limited mobile resources. The proposed mobile guides in the literature do not use the cloud to support the limited user device resources: storage and processing. Our motivation is to guide a visitor in a large art museum according to an identified plan and to allow him to get all the necessary information via his mobile device. The system presented here will provide the user with information adapted to his location a pre built plan. If he changes the direction the system changes the plan according to the user preferences, and when the user goes in a direction that is already visited then the system will alert him.

The technology that will be used to detect the user location and navigate him is the Quick Response (QR) codes (Hoy, M., 2011). This type of codes used to provide a good amount of information and they are easily read and decoded by smart phones. The QR codes encode several data types such as: text, numeric, URL, email address,..., and geo-information. They are popular to provide the information in different fields and different locations. These codes are used effectively in education, marketing, tourism, etc. In education, for example, they have been used to enhance learning materials by providing “just in time support materials” (Ramsden, A., 2008) such as videos, explanatory text, URIs and staff details.

The QR codes and the bar code which holds less information than QR codes have been used only to localize the user (Chang, Y.-J. et al., 2007; Smailagic, A. et al., 1997). The user has a QR reader and he scans the QR codes while navigation. The QR code contains unique information (ID) which allows the system to determine the user's location and provide the information according to this location. The system presented in Chang, Y.-J. et al. (2007) uses the QR code for impaired cognitive persons who scan the QR codes in their path to work and another person receive these QR codes to verify that the impaired cognitive person in the correct path. The already presented works have not been used to build a tour plan or indoor navigation system based in this QR codes.

In this paper, we will use the QR codes to localize the user and, in addition. A tour plan will be built using Dijkstra algorithm. It will be used to navigate the user and direct him to the POI as prescribed in the plan. In case of scanning a wrong QR code, the system will react and guide the user to the correct path. If the visitor is not aware of the museum sections, then a default plan will be built according to the highly rate given to each section and within the time constraint.

To build our indoor navigation system, we will use the Geo-coded QR codes which encode geographic co-ordinates (latitude and longitude). This code will help the system in determining the user location and the system in this case will give him a suitable direction according to the plan and present location-aware information. The QR code must be distributed in a way that permit the system to guide the user effectively and must be in a location where the user can scan easily.

Complete Article List

Search this Journal:
Open Access Articles: Forthcoming
Volume 9: 4 Issues (2017)
Volume 8: 4 Issues (2016)
Volume 7: 4 Issues (2015)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing