AIR: Using Artificial Intelligence to Manage Visitor Flow

Crowded hiking trails, full parking lots, and heavily visited attractions: These problems have long been a reality at tourist hotspots. The COVID-19 pandemic has exacerbated the situation in many places; at times, the only option left to prevent overcrowding is to close off areas. However, restrictions, bans, and barriers are costly to implement and frustrating for visitors, as they often aren’t visible until it’s already too late. That’s why researchers are exploring smart solutions to provide people with digital information, thereby enabling timely and voluntary guidance. The goal is to “nudge” people toward destinations that aren’t too crowded or overloaded.

Nationwide Pilot Project for Digital Visitor Management

The AIR project (AI-based recommender for sustainable tourism) is investigating, through a nationwide network of destination practitioners and research partners, how such a digital visitor management system must be designed to provide visitors with timely, relevant information about current or expected occupancy levels at their desired destination. All necessary elements of a digital visitor management system—from visitor count measurement to data exchange and the development of intelligent recommendations, through to delivery via smartphone or other digital touchpoints—are being investigated by the research partners Outdooractive (Immenstadt), WTZ Füssen (Kempten University of Applied Sciences), Westküste University of Applied Sciences (Heid), and Kiel University of Applied Sciences, as well as the Institute for Tourism and Spa Research in Northern Europe in Kiel, are being examined through pilot applications. Integration with other smart initiatives in the destinations also plays a role in this process.

Pilot Regions in North Rhine-Westphalia: Sauerland and the Ruhrgebiet

In addition to tourist destinations in Bavaria and Schleswig-Holstein, two of the pilot regions are located in North Westphalia—the Sauerland and the Ruhr Metropolis. The Ruhrgebiet is represented by a “use case” along the RuhrtalRadweg, a long-distance cycling trail known throughout the region. Given that the Ruhrtal can become very crowded or congested—especially during nice weather in the spring and summer (e.g., at Kemnader See or Baldeneysee)—an assessment is being conducted in the area of the Ruhr reservoirs to determine which measures would be necessary, appropriate, practical, and likely to succeed in guiding the behavior of cycling vacationers and day-trippers.

Project Goal: Identification of Success Factors

The goal of this three-year project, which began in January 2022, is to develop data and solutions that will help the pilot regions test and improve effective visitor management while identifying success factors that can be applied to other destinations. “Artificial intelligence” algorithms play an important role in forecasting and generating recommendations.

The project is funded by the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety, and Consumer Protection through the “AI Lighthouses” program with a total of approximately 3 million euros.

Click here to visit the project website.