Context-Aware QoE for Mobility-Driven Applications Through Dynamic Surveys

Abstract

The integration of outdoor smartphone applications with fitness trackers has introduced new opportunities and challenges for user interaction, particularly in mobility-driven activities. While these innovations offer significant benefits, they also pose challenges due to the many factors influencing the user’s quality of experience. Traditional methods of assessing user experiences, such as offline surveys and static questionnaires, often fail to capture the dynamic nature of outdoor activities. This research proposes a novel Quality of Experience (QoE) methodology for mobile applications to enhance the assessment of user experiences in cycling. Focusing on a use case in Blekinge, Sweden, where residents were encouraged to adopt cycling for daily transportation, we extracted land cover data and developed a server-side workflow for bicycle path segmentation. By incorporating dynamic surveys that adapt to users’ real-time experiences, we aim to generate a more accurate and context-aware dataset. This study makes several key contributions: First, it presents a scalable method for bicycle path segmentation; second, it demonstrates the utility and benefits of land cover data extraction; and finally, it evaluates the effectiveness of QoE influence factors through user surveys based on real-world cyclist feedback. This approach is expected to enhance the planning and development of cycling infrastructure by providing urban planners and stakeholders with valuable user insights using adaptable surveys based on route segmentation.