Geofence-to-Conversation: Hierarchical Geofencing for Augmenting City Walks with Large Language Models

This study presents a geofence-based service architecture for city-wide audio augmented reality, tailored for the era of large language models. Traditional geofencing mechanisms, which monitor user entry to geofences, struggle to provide continuous storytelling in areas with few points of interest, degrading the audio tour experiences for pedestrians. Our proposed geofencing architecture consistently incorporates complex and multilayered city features, enabling seamless audio tour experiences. Furthermore, this paper introduces prompt engineering for generating entertaining guide scripts for large language models, that is, the geofence-to-conversation technique. The mobile application developed for the actual field demonstrates the feasibility of our proposed architecture and highlights future challenges in enhancing users’ interaction with a city.