Beyond Sensors: A Rule-Based Approach for Cost-Effective Visitor Guidance

Tourism is an important economic driver for numerous regions, attracting more than one billion visitors annually. While economically significant, excessive numbers of visitors lead to local overcrowding, which negatively impacts visitors’ experience and safety, and causes environmental harm. This paper proposes a practical approach to empowering destination management organizations (DMOs) to manage tourist flows. We advocate for a rule-based approach that models visitor occupancy based on easily understandable influence factors like weather and date. As a central component, an ontology-guided knowledge graph ensures compatibility with diverse touristic data models and allows seamless integration into existing infrastructures. By digitizing DMOs’ experiential knowledge, we facilitate the implementation of lean and cost-effective visitor guidance. We demonstrate our approach by implementing two applications for two different use cases. The results of our qualitative evaluation reveal the compelling potential for rule-based occupancy modeling approaches serving as a baseline for future visitor management systems.