Interdisciplinary research project "PredTour" started
Konstanz, December 2016. In the Lake Konstanz region popular with holidaymakers and excursionists, many and different visitors meet. In the main season this often leads to an overloading of the infrastructure. The aim of the project is to identify the various traffic and human flows, to predict local behavioral tendencies, and to relieve the infrastructure of the visitor streams.
Prof. Dr. Marcel Hüttermann, Prof. Dr. Tatjana Thimm, Christine Bild, Prof. Dr. Ralf Seepold, Maksym Gaiduk, Agnes Klein, Daniel Scherz (l.t.r)
The international Lake Region is a popular holiday destination for tourists and residents alike. Due to the differences in the currency of the countries close to the Lake Constance, a year-round shopping tourism has developedalongside recreational tourism. Shopping tourists come from Switzerland to the neighboring cities. In the main season and at certain events the different visitor streams meet. The infrastructure, in any case limited by the special location on the lake, is overloaded as a result of the concentration of space and time. In order to relieve the infrastructure, it makes sense to identify different visiting groups with specific needs and to manage the individual groups according to their needs. The aim of the project "Predicting Tourism Movements" (PredTour), sponsored by the International Lake Constance University, is to analyze the various traffic and human streams of the Bodenseeregion in detail.
Over the next two years, an interdisciplinary research team from science and practice will deal with various questions on the subject. The cooperation is carried out between Computer Scientists (Prof. Dr. Seepold), Tourism Scientists (Prof. Dr. Thimm) of the HTWG Konstanz and marketing department scientits of the ZHAW Zurich (Dr. Seiler) as well as tourism and city marketing Radolfzell GmbH as a practice partner. In a first step, different visitor groups are identified with specific movement patterns. Touristic hot spots and "non-places" are determined based on the patterns of movement. An algorithm is developed, which allows to predict local and temporal traffic volumes and behavioral tendencies. The timely forecast of the tourist flows will make it possible to direct them precisely. Through a smartphone app, private users can plan their own "optimal" route based on the projected traffic volume and individual boundary conditions. Providers can use the data obtained to provide personalized, consumer-relevant offers in real-time and thus contribute to the management of visitor flows. The targeted management of visitors flows will improve the use of the infrastructure.