A conceptual framework for personalized location-based Services (LBS) tourism mobile application leveraging semantic web to enhance tourism experience

Mahmood, Fadhlun Mohamed; Salam, Zailan Arabee Bin Abdul

doi:10.1109/iadcc.2013.6514237

Cited by 13 publications

(9 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After comparing on trial, the positioning precision of the algorithm is higher when k is equal to 3 or 4.The sym bol dj denotes Manhattan distance when P is equal to 1 in the formula (2), and the symbol di denotes Euclidean dis tance when P is equal to 2.The experimental results show that positioning accuracy of the method is relatively stable when P is equal to 2.…”

Section: In Online Stagementioning

confidence: 90%

See 1 more Smart Citation

Study of fingerprint location algorithm based on WiFi technology for indoor localization

Liao

2014

10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)

View full text Add to dashboard Cite

At outdoor environment, GPS can provide accurate loca tion services. But at indoor environment, it can not. In order to realize accurate positioning indoor, we propose a fingerprint localization algorithm based on WiFi in this paper. In the process of our research, we will divide the indoor environment that need provide accurate location services into a certain scale of virtual grid, and tag each vertex with the physical coordinates. Then use multiple wireless router indoor as WIFI signal source, and use smart phones as the target node. Sample more groups of WiFi signal strength values from each grid vertex, then the value and the physical coordinates form a position fingerprint database. In the process of localization, mul tiple WiFi signal strength value detected by the target node will be matched with the position fingerprint data base to find out a grid vertex most closest to the target node, and regard the physical coordinates of the grid ver tex as the final location information of the target node. In order to improve the positioning accuracy of the algorithm, we put the WiFi signal received by the target node into a filter, and use the least square method for error correction when calculating coordinates of the target node. Lastly, we did an experiment on the specific scenes. The experi mental results show that the positioning error of fmger print positioning algorithm based on WiFi is under the meter level at indoor environment, and the positioning accuracy can better meet the needs of business location services.

show abstract

Section: In Online Stagementioning

confidence: 90%

“…With the development of mobile communication technol ogy and the increasing of busines requirements, location aware computing [1] and LBS (location based services) [2] have attracted more and more attention. To realize the LBS, the key is how to determine the user's location.…”

Section: Introductionmentioning

confidence: 99%

Study of fingerprint location algorithm based on WiFi technology for indoor localization

Liao

2014

10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)

View full text Add to dashboard Cite

show abstract

“…R. Gobi proposes a communication framework for data management in LBS [5]. A conceptual framework for personalized location-based tourism apps leveraging semantic web to enhance tourism experience is proposed by Mahmood [6]. Rui Jose proposes the AROUND architecture for supporting location-based services in the Internet environment [7].…”

Section: ) Analyzing Test Results and Coveragesmentioning

confidence: 99%

Test Model and Coverage Analysis for Location-based Mobile Services

Zhang¹,

Gao²,

Aktouf³

et al. 2015

International Conferences on Software Engineering and Knowledge Engineering

View full text Add to dashboard Cite

Abstract-Location-based services (LBS) are very important mobile app services, which provide diverse mobility services for mobile users anywhere and anytime. This brings new demands, issues, and challenges in mobile application testing. Today, mobile applications provide location-based service functions based on dynamic location contexts, mobile users and their travel patterns to deliver location-based mobile data, and service actions. Current software testing methods do not consider location-based validation coverage. Hence, there is a lack of research results addressing location-based mobile application testing. This paper focuses on mobile LBS testing. A novel test object model is proposed for quality validation of location-based mobile information services. In addition, the related test coverage metrics are also presented. These metrics can be useful for test engineers in designing test cases. A case study based on student testers is reported to demonstrate the potential application of the proposed model.

show abstract

“…In the recent years, there have been a number of published research papers addressing LBS. However, most papers primarily focus on infrastructure [3,4], positioning techniques [5], location privacy preserving [6,7], and other areas.…”

Section: Introductionmentioning

confidence: 99%

How to Test Location-based Mobile Apps

Cheng

Zhu

Zhang

et al. 2016

Proceedings of the 2016 International Conference on Computer Science and Electronic Technology

View full text Add to dashboard Cite

Location-based services are growing in popularity due to the ubiquity of smartphone users. The availability and validity of location-based services are often effected by mobile user location contexts, which make mobile location-based services testing becomes one urgent and challenging issue. In this paper, we analyze location related features for location-based mobile apps. Then some test strategies are proposed to test those location related features and characteristics. Moreover, a case study is reported to describe our test approaches and test steps in details. CCS Concepts • Software and its engineering~Software testing and debugging • Human-centered computing~Mobile computing

show abstract

A conceptual framework for personalized location-based Services (LBS) tourism mobile application leveraging semantic web to enhance tourism experience

Cited by 13 publications

References 21 publications

Study of fingerprint location algorithm based on WiFi technology for indoor localization

Study of fingerprint location algorithm based on WiFi technology for indoor localization

Test Model and Coverage Analysis for Location-based Mobile Services

How to Test Location-based Mobile Apps

Contact Info

Product

Resources

About