碩士 / 國立暨南國際大學 / 資訊工程學系 / 106 / In this study, we presented a new large-scale crowd navigation system for visitors to the zoo. The system uses machine learning to analyze the interests of visitors and provides a dynamic path recommendation service for each visitor. By taking advantage of the convenience of smartphones, the system can simply collect the tourist's interests and basic information. Finally, based on the zoo’s current population distribution, visitor feedback, and visitor’s GPS history, the system dynamically calculates and recommends suitable routes for each visitor or group.
The machine learning techniques used in our system include K-Means Clustering, Collaborative Filtering Recommendations, and Markov Chain Monte Carlo Method to calculate user interest information to the server for path recommendation. And regularly update the status of the zoo and the status of visitors in order to achieve a more correct path recommended results.
Through a game similar to Pokémon GO, the system uses animal portrait morphing technology and gamified crowd evacuation system as the basis of the ingenuity. Compared with traditional zoo-visiting, visitors can play games at the zoo and get more interesting feedback and experience. Visitors can receive the game quest from the server through the game app on the smartphone, and move to a specific location and answer questions from the mini-games to get game points and collect vivid, interesting personal morphing portrait.
By integrating the above technologies, our system not only provides visitors with an edutainment system but also reduce the crowdedness of the zoo.
| Identifer | oai:union.ndltd.org:TW/106NCNU0392005 |
| Date | January 2018 |
| Creators | YOU, ZONG-HAN, 游宗翰 |
| Contributors | Lieu-Hen Chen, 陳履恆 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 37 |
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