Location-based technology is key for ubiquitous society. To enhance the location-based services, recognizing the places and the patterns where a person and an object have visited in addition to geographical locations is needed. Although some researchers have developed methods that extract outdoor stay regions from GPS trajectories to recognize the visiting places, there is no technology that recognizes stay regions, such as spatial location in a living house and an office building, from indoor trajectories. Technology for extracting indoor stay regions is required to achieve more intelligent indoor-location-based services, such as smart-home and smart-office. Therefore, we developed a method which extracts stay regions from an ultra-wideband (UWB) indoor trajectory. An UWB indoor positioning technology provides location information with a few-tens-of-centimeters error. Our developed method was evaluated comparing with conventional methods.


  • Tessai Hayama, Hiroki Takahashi, Kazuya Nagatomo, “Extracting Stay Regions from UWB Indoor Trajectory and its Evaluation”, International Journal of Service and Knowledge Management, Vol. 4, No. 1, pp.27 – 40 (2020)
  • Tessai Hayama, Tsuyoshi Nariai, Nagatomo, “Extracting Stay Regions from UWB Indoor Trajectory”, 4th International Conference on Business Management of Technology (BMOT 2019), 2019.
  • Tessai Hayama, Hiroki Takahashi, Kazuya Nagatomo, “Extracting Stay Regions from Indoor Geospatial Trajectory Using Time-based Clustering”, 14th International Conference on Knowledge, Information, Creativity Support Systems (KICSS 2019), 2019.
  • 成相毅,長友和也,羽山徹彩: “UWB屋内軌道データからの滞在領域抽出“, 第33回人工知能学会全国大会講演論文集, pp.1-4(2019).