EasyTrack: Zero-Calibration Smart-Home Tracking System

• Nathavuth, Kitbutrawat

• Hirozumi, Yamaguchi

• Teruo, Higashino

抄録

Location-based services in household enable not only estimating activities but also detecting the accident location of residents including children, parents and elderly people. Furthermore, home management systems make use of location information of residents for encouraging residents to live comfortably in their own homes. Passive infrared binary motion sensors are widely used in home tracking systems because of low energy consumption and flexibility on deployment. However, it's hard for non-specialists like residents to manage such location information of sensors which are very important for tracking systems. To mitigate human efforts and errors, we propose a sensor localization method to automatically identify the location of multiple binary motion sensors in a house from the observed motion detection event sequences by binary sensors. The method finds the movement patterns and characteristics of sojourn time of residents to identify the rooms where those sensors are located as well as the proximity relations among sensors assisted by prior knowledge such as from floorplan. The experimental results in actual houses show that our method can estimate the location of sensors placed close to the anchor locations within a one-day observation, and the accuracy of our approach is above 80% after three-day observation.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.27(2019) (online)DOI　http://dx.doi.org/10.2197/ipsjjip.27.445------------------------------

Location-based services in household enable not only estimating activities but also detecting the accident location of residents including children, parents and elderly people. Furthermore, home management systems make use of location information of residents for encouraging residents to live comfortably in their own homes. Passive infrared binary motion sensors are widely used in home tracking systems because of low energy consumption and flexibility on deployment. However, it's hard for non-specialists like residents to manage such location information of sensors which are very important for tracking systems. To mitigate human efforts and errors, we propose a sensor localization method to automatically identify the location of multiple binary motion sensors in a house from the observed motion detection event sequences by binary sensors. The method finds the movement patterns and characteristics of sojourn time of residents to identify the rooms where those sensors are located as well as the proximity relations among sensors assisted by prior knowledge such as from floorplan. The experimental results in actual houses show that our method can estimate the location of sensors placed close to the anchor locations within a one-day observation, and the accuracy of our approach is above 80% after three-day observation.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.27(2019) (online)DOI　http://dx.doi.org/10.2197/ipsjjip.27.445------------------------------

収録刊行物

• 情報処理学会論文誌

  情報処理学会論文誌 60 (7), 2019-07-15

キーワード

• [一般論文] unsupervised learning, localization, home passive sensor

詳細情報

• CRID: 1050564288341444864
• NII論文ID: 170000150486
• NII書誌ID: AN00116647
• ISSN: 18827764
• Web Site: http://id.nii.ac.jp/1001/00198260/
• 本文言語コード: en
• 資料種別: journal article
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