• The Journal of Bigdata
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• v.5 no.1
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• pp.29-39
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• 2020

Purpose The atmosphere of respect for individual tastes that have spread throughout society has changed the consumption trend. As a result, the travel industry is also seeing customized travel as a new trend that reflects consumers' personal tastes. In particular, there is a growing interest in 'film-induced tourism', one of the areas of travel industry. We hope to satisfy the individual's motivation for traveling while watching movies with customized travel proposals, which we expect to be a catalyst for the continued development of the 'film-induced tourism industry'. Design/methodology/approach In this study, we implemented a methodology through 'OCR' of extracting and suggesting film location information that viewers want to visit. First, we extract a scene from a movie selected by a user by using 'OpenCV', a real-time image processing library. In addition, we detected the location of characters in the scene image by using 'EAST model', a deep learning-based text area detection model. The detected images are preprocessed by using 'OpenCV built-in function' to increase recognition accuracy. Finally, after converting characters in images into recognizable text using 'Tesseract', an optical character recognition engine, the 'Google Map API' returns actual location information. Significance This research is significant in that it provides personalized tourism content using fourth industrial technology, in addition to existing film tourism. This could be used in the development of film-induced tourism packages with travel agencies in the future. It also implies the possibility of being used for inflow from abroad as well as to abroad.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.63-72
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• 2022

Purpose: After the Crona Pandemic, all countries are interested in developing various programs to attract tourists. In order to activate the attraction of tourists, it is necessary to discover the information needed by tourists and provide the information based on the visitor's location. Method: This research proposes a system configuration method for creating tourist-oriented tourism contents information. To this end, it creates GIS and QR code-based content and provides necessary information from the tourist's current location. In addition, by using QR codes installed at various points, it provides travel time and other destination information from the current location, and AR image information based on QR codes. Result: The existing tourism content system provides information using a fixed location-based QR code. This research creates and provides customized tourism information based on the location of tourists by generating GIS-based QR codes. Conclusion: This research aims to contribute to the construction of a new tourism information contents and the activation of tourist-oriented tourism information provision.