WO2021192398A1 - 行動認識サーバ、および、行動認識方法 - Google Patents
行動認識サーバ、および、行動認識方法 Download PDFInfo
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- WO2021192398A1 WO2021192398A1 PCT/JP2020/042056 JP2020042056W WO2021192398A1 WO 2021192398 A1 WO2021192398 A1 WO 2021192398A1 JP 2020042056 W JP2020042056 W JP 2020042056W WO 2021192398 A1 WO2021192398 A1 WO 2021192398A1
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- WIPO (PCT)
- Prior art keywords
- behavior
- sensor information
- observed person
- sensor
- unit
- Prior art date
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/04—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using a single signalling line, e.g. in a closed loop
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
Definitions
- the change detection unit 18 compares the current behavior pattern of FIG. 9 with the normal behavior pattern of FIG. 10 for each behavior (S111), and finds the following abnormalities in the current behavior pattern of the observed person 2u. Extract actions. ⁇ I didn't get up until 9 o'clock and there was no movement indoors. ⁇ Meal time is different from usual and meal time is long. ⁇ I am temporarily returning home at an unexpected time (15:00) while I am out. ⁇ Bathing time is different and bathing time is long.
- the change detection unit 18 detects the abnormality of the observed person 2u as illustrated below.
- the normal behavior defined in the normal behavior pattern is not currently performed in the behavior pattern.
- Unnatural behaviors that are not in the normal behavior pattern have been performed in the current behavior pattern.
- the normal behavior defined in the normal behavior pattern was also performed in the current behavior pattern, but it was different from the time defined in the normal behavior pattern.
- the normal behavior defined in the normal behavior pattern was also performed in the current behavior pattern, but the length was different from the length defined in the normal behavior pattern.
- the behavioral speed of the observed person 2u in the current behavioral pattern deviated from (greatly lower than) the behavioral speed defined as the normal behavioral pattern.
- the process of acquiring the behavioral speed of the observed person 2u from the current behavioral pattern in (5) includes a method exemplified below. -Measure the moving speed between the washroom and the kitchen from the operation interval between the washing machine and the refrigerator 2a (range, IH). -Measure the reaction speed from changes in the behavior (opening / closing speed, opening / closing interval, opening / closing time, etc.) related to the door of the refrigerator 2a. ⁇ Measure the action speed from the interval between the opening and closing of the entrance door and the ON / OFF of the lighting. -Measure the walking speed during cleaning from the acceleration of the vacuum cleaner 2b.
- FIG. 11 is a screen view showing a display screen of the observer terminal 3 when the current behavior pattern is normal (S111, No).
- the change detection unit 18 informs the observer 3u of the healthy state of the observer 2u by displaying a display screen including the following display contents on the observer terminal 3.
- -Message column 221 showing the outline of the current behavior pattern ⁇
- Time chart column 222 of current behavior pattern ⁇
- Statistical data column 224 of the difference between this week and last week -Statistical data column 225 of the difference from the history so far
- FIG. 12 is a screen view showing a display screen (S112) of the observer terminal 3 when the current behavior pattern is abnormal (S111, Yes).
- the room names such as the bedroom and the living room and the sensor information (temperature, humidity, illuminance) measured by the environmental sensor for each room are displayed for each room of the home 2h.
- the estimated position 212 of the observed person 2u and the warning message 213 (emergency signal) indicating the abnormal behavior of the observed person 2u are also displayed in the floor plan column 211.
- the observer 3u can easily grasp the details of the abnormality of the observed person 2u such as a person falling down.
- the present embodiment is compared with the method of constructing a living behavior database as in Patent Document 1.
- Patent Document 1 it takes time and effort to manually input the rule of which sensor information affects the behavior and how much.
- the rule of which sensor information affects the behavior to what extent is automatically discovered by machine learning, so that a human can handle the rule. You can save the trouble of inputting in the work. Furthermore, even rules that humans did not know are automatically discovered by machine learning, improving the accuracy of behavior recognition.
- control lines and information lines indicate those that are considered necessary for explanation, and do not necessarily indicate all the control lines and information lines in the product. In practice, it can be considered that almost all configurations are interconnected.
- the communication means for connecting each device is not limited to the wireless LAN, and may be changed to a wired LAN or other communication means.
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- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Alarm Systems (AREA)
- Emergency Alarm Devices (AREA)
Priority Applications (1)
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CN202080066478.8A CN114424263B (zh) | 2020-03-25 | 2020-11-11 | 行为识别服务器和行为识别方法 |
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JP2020054434A JP7366820B2 (ja) | 2020-03-25 | 2020-03-25 | 行動認識サーバ、および、行動認識方法 |
JP2020-054434 | 2020-03-25 |
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WO2021192398A1 true WO2021192398A1 (ja) | 2021-09-30 |
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PCT/JP2020/042056 WO2021192398A1 (ja) | 2020-03-25 | 2020-11-11 | 行動認識サーバ、および、行動認識方法 |
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JP (1) | JP7366820B2 (zh) |
CN (1) | CN114424263B (zh) |
WO (1) | WO2021192398A1 (zh) |
Families Citing this family (1)
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JP2023090273A (ja) * | 2021-12-17 | 2023-06-29 | 株式会社日立製作所 | センシングシステム、センシング装置、およびセンシング方法 |
Citations (4)
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JP2002352352A (ja) * | 2001-05-29 | 2002-12-06 | Mitsubishi Electric Corp | 生活行動パターンの異常度判定システム及び生活行動パターンの異常度判定方法 |
JP2017117492A (ja) * | 2017-03-13 | 2017-06-29 | 株式会社日立製作所 | 見守りシステム |
JP2017216006A (ja) * | 2017-08-10 | 2017-12-07 | パラマウントベッド株式会社 | 見守り支援装置 |
JP2018124639A (ja) * | 2017-01-30 | 2018-08-09 | 日本電気株式会社 | データ分析システム、データ分析方法およびプログラム |
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JP5143780B2 (ja) * | 2009-03-31 | 2013-02-13 | 綜合警備保障株式会社 | 監視装置及び監視方法 |
JP5726792B2 (ja) * | 2012-03-12 | 2015-06-03 | 株式会社東芝 | 情報処理装置、画像センサ装置及びプログラム |
JP5877135B2 (ja) * | 2012-07-20 | 2016-03-02 | 株式会社日立製作所 | 画像認識装置及びエレベータ装置 |
JP6683199B2 (ja) * | 2015-04-27 | 2020-04-15 | コニカミノルタ株式会社 | 監視装置、監視方法、監視プログラムおよび監視システム |
JP2017023055A (ja) * | 2015-07-22 | 2017-02-02 | 大日本印刷株式会社 | 細胞管理システム、プログラム、及び、細胞管理方法 |
WO2017038035A1 (ja) * | 2015-08-31 | 2017-03-09 | 富士フイルム株式会社 | 行動履歴情報生成装置、システム、及び方法 |
JP6713837B2 (ja) * | 2016-05-31 | 2020-06-24 | 株式会社日立製作所 | 輸送機器制御システム、及び、輸送機器制御方法 |
KR101810853B1 (ko) * | 2016-10-27 | 2017-12-20 | 숭실대학교산학협력단 | 신경망 알고리즘을 이용한 내부 정보 유출 방지 방법, 이를 수행하기 위한 기록 매체 및 장치 |
JP7370857B2 (ja) * | 2017-04-06 | 2023-10-30 | コニカミノルタ株式会社 | 行動検知装置および行動検知方法ならびに被監視者監視支援システム |
WO2019028016A1 (en) * | 2017-07-31 | 2019-02-07 | Cubic Corporation | REPORT AND RECOGNITION OF AUTOMATED SCENARIO USING NEURAL NETWORKS |
JP6999399B2 (ja) * | 2017-12-19 | 2022-01-18 | 日本信号株式会社 | 異常判定装置 |
JP2019149039A (ja) * | 2018-02-27 | 2019-09-05 | パナソニックIpマネジメント株式会社 | 見守りシステム及び見守り方法 |
KR102152717B1 (ko) * | 2018-08-28 | 2020-09-07 | 한국전자통신연구원 | 휴먼 행동 인식 장치 및 방법 |
KR101999213B1 (ko) * | 2019-03-28 | 2019-07-11 | 한국건설기술연구원 | 신호강도 패턴을 이용한 cctv 기반 행동 인식 시스템, 방법, 및 상기 방법을 실행시키기 위한 컴퓨터 판독 가능한 프로그램을 기록한 기록 매체 |
CN110058699B (zh) * | 2019-04-28 | 2021-04-27 | 电子科技大学 | 一种基于智能移动设备传感器的用户行为识别方法 |
CN110533889B (zh) * | 2019-08-30 | 2021-08-13 | 中国电子科技网络信息安全有限公司 | 一种敏感区域电子设备监测定位装置与方法 |
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- 2020-03-25 JP JP2020054434A patent/JP7366820B2/ja active Active
- 2020-11-11 CN CN202080066478.8A patent/CN114424263B/zh active Active
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Patent Citations (4)
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JP2002352352A (ja) * | 2001-05-29 | 2002-12-06 | Mitsubishi Electric Corp | 生活行動パターンの異常度判定システム及び生活行動パターンの異常度判定方法 |
JP2018124639A (ja) * | 2017-01-30 | 2018-08-09 | 日本電気株式会社 | データ分析システム、データ分析方法およびプログラム |
JP2017117492A (ja) * | 2017-03-13 | 2017-06-29 | 株式会社日立製作所 | 見守りシステム |
JP2017216006A (ja) * | 2017-08-10 | 2017-12-07 | パラマウントベッド株式会社 | 見守り支援装置 |
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CN114424263A (zh) | 2022-04-29 |
JP2021157274A (ja) | 2021-10-07 |
JP7366820B2 (ja) | 2023-10-23 |
CN114424263B (zh) | 2023-06-27 |
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