International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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A Stay Detection Algorithm Using GPS Trajectory and Points of Interest Data

  • Eunchong Koh (Graduate School of Smart Convergence Kwangwoon University) ;
  • Changhoon Lyu (LOYQU Inc.) ;
  • Goya Choi (LOYQU Inc.) ;
  • Kye-Dong Jung (Ingenium College of liberal arts, Kwangwoon University) ;
  • Soonchul Kwon (Graduate School of Smart Convergence, Kwangwoon University) ;
  • Chigon Hwang (Department of Computer Engineering, Institute of Information Technology, Kwangwoon University)
  • Received : 2023.07.07
  • Accepted : 2023.07.16
  • Published : 2023.08.31
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Abstract

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

Keywords

Acknowledgement

This research was supported by Seoul R&BD Program (IC220005) through the Seoul Business Agency (SBA) funded by The Seoul Metropolitan Government

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