UWB屋内軌道からの滞在領域抽出手法の開発

概要：

位置情報技術はユビキタス社会のキーテクノロジーである．位置ベースサービスを促進するためには，人/モノが行動目的とする場所とそのパターンを認識する必要がある．これまで，アウトドアを対象にGPS軌道データから滞在場所を抽出手法は研究されてきたものの，スマートホームやスマートオフィスで利活用されると思われるインドアを対象にはほとんど取り組まれてこなかった．そこで，本研究ではインドアでのUWB軌道データを対象に，時間準拠アルゴリズムを基づいた滞在領域手法を開発した．通常の時間準拠アルゴリズムと比較し，有効性を示したとともに，UWB位置検出では屋内で十数センチ程度の誤差で検出できることも確認した．

Ａｂｓｔｒａｃｔ：

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.

研究成果：

• 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).