Scholarlink

This study investigates the integration of augmented reality (AR) technology into the tourism sector, with a focus on developing a location-based AR application within the SmarTravel project. The main objective is to enhance tourist experiences through immersive gamified tours by leveraging advanced technologies such as Global Positioning System (GPS), Visual Positioning System (VPS), and geofencing. The system architecture consists of three primary layers: Data Cloud, Data Fusion and Core, and Application, which together enable the integration of diverse data sources, gamification frameworks, and personalized attraction recommendations. Methodologically, this research delves into the conversion of City Geography Markup Language (CityGML) data, highlighting the challenges associated with markerless location-based AR. The Attraction Recommendation Engine integrates with the Setur API, utilizing representational state transfer (REST) protocols for efficient data management. The user interface/user experience (UI/UX) design emphasizes intuitive interfaces and user-friendly interactions, aligned with gamification elements inspired by successful AR gaming paradigms. This study concludes by demonstrating the project’s success in overcoming localization challenges and delivering a scalable and adaptable system, thereby setting a benchmark for future advancements in location-based AR tourism experiences.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Location-Based AR Application in Tourism: A Case Study of SmarTravel

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Hüseyin Bahtiyar,
  • Eda Yüksel,
  • Turgut Türkmen,
  • Suayb Talha Özçelik,
  • Berke Güneş,
  • Meltem Turhan Yöndem

摘要

This study investigates the integration of augmented reality (AR) technology into the tourism sector, with a focus on developing a location-based AR application within the SmarTravel project. The main objective is to enhance tourist experiences through immersive gamified tours by leveraging advanced technologies such as Global Positioning System (GPS), Visual Positioning System (VPS), and geofencing. The system architecture consists of three primary layers: Data Cloud, Data Fusion and Core, and Application, which together enable the integration of diverse data sources, gamification frameworks, and personalized attraction recommendations. Methodologically, this research delves into the conversion of City Geography Markup Language (CityGML) data, highlighting the challenges associated with markerless location-based AR. The Attraction Recommendation Engine integrates with the Setur API, utilizing representational state transfer (REST) protocols for efficient data management. The user interface/user experience (UI/UX) design emphasizes intuitive interfaces and user-friendly interactions, aligned with gamification elements inspired by successful AR gaming paradigms. This study concludes by demonstrating the project’s success in overcoming localization challenges and delivering a scalable and adaptable system, thereby setting a benchmark for future advancements in location-based AR tourism experiences.