Abstract—The aim of this paper is to design a prototype that integrates a big data framework with a mobile application on an iOS platform to support smart tourism; a case study in Lampang Province, Thailand. The research approach used Software Development Life Cycle (SDLC) methodologies to analyze, design, implement and test user satisfaction of the system. The results found that the design of the big data model used Apache Hadoop to co-ordinate with Apache Spark as the big data processing framework. The mobile application system was designed and developed on an iOS platform that works with user interaction and receives various information from the data base that stores information about tourism such as tourist attractions, accommodation, spa products, health, food, tourism routes, and emergency contacts. etc. The mobile application system was used and evaluated for effectiveness and satisfaction of 400 users with an in-depth interview of 10 users. The results found that the overall mobile application evaluation in six categories found the highest score was the benefit of the mobile application system (xˉ=4.46, S.D. =0.67), second the mobile application system design (xˉ=4.43, S.D. =0.66), third the mobile application content design (xˉ=4.32, S.D. =0.65) and finally the mobile application system ease of use (xˉ=4.32, S.D. =0.68), respectively. Moreover, the qualitative results found that users were satisfied with the design, functionality, content, and the system overall.
Index Terms—Big data, education, mobile application, tourism.
Pannee Suanpang is with the Suan Dusit University, Bangkok, Thailand (e-mail: email@example.com).
Pitchaya Jamjuntr is with Siam Technology College, Bangkok, Thailand (e-mail: firstname.lastname@example.org).
Cite: Pannee Suanpang and Pitchaya Jamjuntr, "The Integration of a Big Data Framework and a Mobile Application on the iOS Platform to Support Smart Tourism," International Journal of Machine Learning and Computing vol. 10, no. 6, pp. 714-722, 2020.Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).