Device and system for detecting abnormality

• US 6,989,742 B2
• Filed: 12/23/2002
• Issued: 01/24/2006
• Est. Priority Date: 12/25/2001
• Status: Expired due to Term

• Current Assignee: Matsushita Electric Industrial Company Limited (Panasonic Holdings Corporation)
• Original Assignee: Matsushita Electric Industrial Company Limited (Panasonic Holdings Corporation)
• Inventors: Tanaka, Shinji, Inoue, Shigeyuki, Yamamoto, Hiroshi, Hara, Kousuke, Omori, Takashi, Ueno, Reiko, Kaneda, Noriko
• Primary Examiner(s): Wu, Daniel
• Assistant Examiner(s): RODRIGUEZ, JOSEPH C
• Application Number:
  US10/326,447
• Publication Number:
  US 20030117279A1
• Time in Patent Office: 1,128 Days
• Field of Search: 340/511, 340/539.14, 340/539.25, 348/155, 348/153, 348/154, 348/159
• US Class Current: 340/511
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06F 18/2433 Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
• CPC Class Codes: G06F 18/295 Markov models or related models, e.g. semi-Markov models; Markov random fields; Networks embedding Markov models
• CPC Class Codes: G06V 10/762 using clustering, e.g. of similar faces in social networks
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 10/85 Markov-related models; Markov random fields
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G08B 21/0423 detecting deviation from an expected pattern of behaviour or schedule
• CPC Class Codes: G08B 21/0469 Presence detectors to detect unsafe condition, e.g. infrared sensor, microphone G08B21/0476 takes precedence
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data

Abstract

An abnormality detection device includes small motion sensors that detect small motions of a person in a house; a data collecting unit that collects and stores sensor signals from the small motion sensors as sensor patterns, and a Markov chain operating unit 33 that transforms the sensor patterns into a cluster sequence by vector-quantizing input patterns which are obtained by averaging and normalizing the sensor patterns, and calculates a transition number matrix and a duration time distribution of a Markov and so on using a Markov chain model. The abnormality detection device also includes a comparing unit that calculates a characteristic amount (Euclid distance and average log likelihood in an appearance frequency of a Markov chain and an average log likelihood to the duration time distribution of a Markov chain) of a sample activity as against a daily activity based on the obtained transition number matrix and the duration time distribution and so on.

Claims

1. An abnormality detection device that detects an occurrence of an abnormality in an event under observation, said abnormality detection device comprising:

an input unit operable to acquire a sequence of an input pattern that is data depending upon the event;

a transition analyzing unit operable to analyze a characteristic of a transition in the sequence of the input pattern acquired by said input unit;

a comparing unit operable to compare the characteristic of the transition analyzed by said transition analyzing unit with a predetermined reference value, and to judge that an abnormality has occurred in the event when the characteristic and the reference value are not approximate to each other within a predetermined range; and

an output unit operable to output an occurrence of the abnormality when said comparing unit judges that the abnormality has occurred;

wherein said input unit includes a plurality of small motion detection sensors located in a plurality of places in a house, and said input unit is operable to acquire, as the input pattern, a sensor pattern that is a combination of data indicating whether or not there is a small motion outputted from a plurality of said plurality of small motion detection sensors; and

wherein said transition analyzing unit is operable to calculate a Markov chain in the sequence of the input pattern and to analyze a characteristic of the calculated Markov chain as the analysis.

2. The abnormality detection device according to claim 1,

wherein said transition analyzing unit is operable to calculate an appearance frequency for each type of the transition in the sequence of the input pattern as the analysis, and

said comparing unit is operable to judge whether or not an abnormality has occurred by comparing the input pattern acquired by said input unit with a reference input pattern for the appearance frequency.

3. The abnormality detection device according to claim 2,

wherein said transition analyzing unit is operable to calculate a probability distribution for each type of the transition as the appearance frequency, and

said comparing unit is operable to calculate a distance between the input pattern acquired by said input unit and a reference input pattern for the probability distribution, and to judge that an abnormality has occurred when the calculated distance exceeds a predetermined value.

4. The abnormality detection device according to claim 2,

wherein said transition analyzing unit is operable to calculate probability distribution for each type of the transition as the appearance frequency, and

said comparing unit is operable to calculate a likelihood of the input pattern acquired by said input unit to the reference input pattern for the probability distribution, and to judge that an abnormality has occurred when the calculated likelihood is a predetermined value or less.

5. The abnormality detection device according to claim 1,

wherein said transition analyzing unit calculates a duration time distribution which is a distribution of time that is required for the transition in the sequence of the input pattern as the analysis, and

said comparing unit is operable to judge whether or not an abnormality has occurred by comparing the input pattern acquired by said input unit with a reference input pattern for the duration time distribution.

6. The abnormality detection device according to claim 5, wherein said comparing unit is operable to calculate a likelihood of the input pattern acquired by said input unit to the reference input pattern for the duration time distribution, and to judge that an abnormality has occurred when the calculated likelihood is a predetermined value or less.

7. The abnormality detection device according to claim 1, further comprising a clustering unit operable to transform the sequence of the input pattern acquired by said input unit into a cluster sequence that is a predetermined representative input pattern,

wherein said transition analyzing unit is operable to analyze the characteristic in the cluster sequence which is transformed by said clustering unit.

8. The abnormality detection device according to claim 7, wherein said clustering unit is operable to obtain the cluster sequence after averaging and normalizing the sequence of the input pattern acquired by said input unit.

9. The abnormality detection device according to claim 8, wherein said clustering unit is operable to obtain the cluster sequence after specifying all the clusters by vector-quantizing the sequence of the input pattern obtained by the normalization.

10. The abnormality detection device according to claim 1, wherein the reference value is a value, for a reference event, obtained by acquiring the sequence of the input pattern in advance through said input unit and analyzing the characteristic through said transition analyzing unit.

11. The abnormality detection device according to claim 10, wherein the reference value is a value determined based on data given by an operator which is learned with a teacher and the input pattern which is acquired repeatedly by the said input unit.

12. The abnormality detection device according to claim 1, wherein the reference value is a value specified by an operator.

13. The abnormality detection device according to claim 1, wherein said input unit is operable to assume that a new sensor pattern has occurred each time the sensor pattern changes, and to acquire a sequence of an input pattern corresponding to a sequence of the sensor pattern.

14. The abnormality detection device according to claim 13, wherein said input unit is operable to acquire the input pattern by averaging and normalizing the sensor pattern in the time domain.

15. The abnormality detection device according to claim 1, wherein said input unit is operable to acquire the sequence of the input pattern from an operator.

16. The abnormality detection device according to claim 1, wherein said output unit is operable to report to a predetermined destination via a transmission channel that the abnormality has occurred.

17. The abnormality detection device according to claim 1,

wherein said transition analyzing unit is operable to calculate an appearance frequency of the Markov chain as the analysis, and

said comparing unit is operable to judge whether or not an abnormality has occurred by comparing the input pattern acquired by said input unit with a reference input pattern for the appearance frequency.

18. The abnormality detection device according to claim 17,

wherein said comparing unit is operable to calculate an Euclid distance between the input pattern acquired by said input unit and the reference input pattern for the appearance frequency of the Markov chain, and to judge that an abnormality has occurred when the calculated Euclid distance exceeds a predetermined value.

19. The abnormality detection device according to claim 18, wherein said comparing unit is operable to calculate a likelihood of the input pattern acquired by said input unit to the reference input pattern for the appearance frequency of the Markov chain, and to judge that an abnormality has occurred when the calculated likelihood is a predetermined value or less.

20. The abnormality detection device according to claim 1,

wherein said transition analyzing unit is operable to calculate a duration time distribution of the Markov chain as the analysis, and

said comparing unit is operable to judge whether or not an abnormality has occurred by comparing the input pattern acquired by said input unit with the reference input pattern for the duration time distribution.

21. The abnormality detection device according to claim 20, wherein said comparing unit is operable to calculate a likelihood of the input pattern acquired by said input unit to the reference input pattern for the duration time distribution of the Markov chain, and to judge that an abnormality has occurred when the calculated likelihood is a predetermined value or less.

22. The abnormality detection device according to claim 1,

wherein the reference value is a collection of local reference values in each time interval which satisfies a predetermined condition, and

said comparing unit is operable to judge whether or not an abnormality has occurred by comparing the characteristic with the local reference value in each time interval which satisfies the predetermined condition.

23. The abnormality detection device according to claim 22, further comprising:

a local reference value generating unit operable to generate the local reference value in each time interval which satisfies the predetermined condition by acquiring a plurality of the sequences of the input patterns through said input unit, resolving the sequences in each time interval where the acquired input patterns are similar to each other within a predetermined range, and collecting the resolved sequences in each time interval which satisfies the predetermined condition; and

a local reference value selecting unit operable to predict and select an optimum reference value from among all the local reference values belonging to each time interval which satisfies the predetermined condition based on the input patterns for abnormality detection,

wherein said comparing unit is operable to judge whether or not an abnormality has occurred by comparing the characteristic with the local reference value selected by said local reference value selecting unit in each time interval which satisfies the predetermined condition.

24. The abnormality detection device according to claim 23, wherein said local reference value generating unit is operable to sample a time interval with a high correlation according to template matching by using a time window, and to resolve the sequence in the each sampled time interval.

25. The abnormality detection device according to claim 23, wherein said local reference value selecting unit is operable to calculate probability distributions for each transition type in the sequences of the input patterns for abnormality detection and the input patterns of the reference event, respectively, and to predict and select the optimum local reference value based on a distance between the calculated probability distributions.

26. An abnormality detection system comprising:

an abnormality detection device is operable to be located in a place where an event for abnormality detection occurs;

a communication device operable to monitor an occurrence of an abnormality; and

a transmission channel operable to connect said abnormality detection device and said communication device;

wherein said abnormality detection device includes;

an input unit operable to acquire a sequence of an input pattern that is data depending upon the event;

a transition analyzing unit operable to analyze a characteristic of a transition in the sequence of the input pattern acquired by said input unit;

a comparing unit operable to compare the characteristic of the transition analyzed by said transition analyzing unit with a predetermined reference value, and to judge that an abnormality has occurred in the event when the characteristic and the reference value are not approximate to each other within a predetermined range; and

an output unit operable to output an occurrence of an abnormality when said comparing unit judges that the abnormality has occurred;

wherein said input unit includes a plurality of small motion detection sensors located in a plurality of places in a house, and said input unit is operable to acquire, as the input pattern, a sensor pattern that is a combination of data indicating whether or not there is a small motion outputted from a plurality of said plurality of small motion detection sensors;

wherein said transition analyzing unit is operable to calculate a Markov chain in the sequence of the input pattern and to analyze a characteristic of the calculated Markov chain as the analysis; and

wherein said communication device includes;

a receiving unit operable to receive a report from said abnormality detection device; and

a showing unit operable to show an operator that the report has been received when said receiving unit receives the report.

28. The abnormality detection system according to claim 26, wherein said input unit includes an operation state detection sensor operable to detect an operation state of equipment which is located in the place, and to acquire a sensor signal from said operation state detection sensor as the input pattern.

29. The abnormality detection system according to claim 26, wherein:

the place is a house;

said abnormality detection system further comprises;

a home network operable to connect a plurality of electrical household appliances which are located in the house; and

a controller operable to control a plurality of the electrical household appliances via said home network; and

said input unit is operable to detect operation states of a plurality of the electrical household appliances via said home network and to acquire the detected operation states as the input patterns.

30. The abnormality detection system according to claim 26, wherein:

the place is a house;

said abnormality detection system further comprises a home network operable to connect a plurality of electrical household appliances which are located in the house;

said abnormality detection device further includes a controller operable to control a plurality of the electrical household appliances via said home network; and

said input unit is operable to detect operation states of a plurality of the electrical household appliances via said home network and to acquire the detected operation states as the input patterns.

27. An abnormality detection system comprising:

an abnormality detection device operable to be located in a place where an event for abnormality detection occurs;

a communication device operable to monitor an occurrence of an abnormality; and

a transmission channel operable to connect said abnormality detection device and said communication device;

wherein said abnormality detection device includes;

an input unit operable to acquire a sequence of an input pattern that is data depending upon the event; and

a sending unit operable to send the input pattern acquired by said input unit to said communication device via said transmission channel;

wherein said input unit includes a plurality of small motion detection sensors located in a plurality of places in a house, and said input unit is operable to acquire, as the input pattern, a sensor pattern that is a combination of data indicating whether or not there is a small motion outputted from a plurality of said plurality of small motion detection sensors; and

wherein said communication device includes;

a receiving unit operable to receive the input pattern sent from said sending unit of said abnormality detection device;

a transition analyzing unit operable to analyze a characteristic of a transition in the sequence of the input pattern received by said receiving unit by calculating a Markov chain in the sequence of the input pattern and analyzing a characteristic of the calculated Markov chain as the analysis;

a comparing unit operable to compare the characteristic of the transition analyzed by said transition analyzing unit with a predetermined reference value, and to judge that an abnormality has occurred in the event when the characteristic and the reference value are not approximate to each other within a predetermined range; and

a showing unit operable to show an operator the occurrence of the abnormality when said comparing unit judges that the abnormality has occurred.

41. The abnormality detection system according to claim 27, wherein said input unit includes an operation state detection sensor operable to detect an operation state of equipment which is located in the place, and to acquire a sensor signal from said operation state detection sensor as the input pattern.

42. The abnormality detection system according to claim 27, wherein:

the place is a house;

said abnormality detection system further comprises;

a home network operable to connect a plurality of electrical household appliances which are located in the house; and

a controller operable to control a plurality of the electrical household appliances via said home network; and

said input unit is operable to detect operation states of a plurality of the electrical household appliances via said home network and to acquire the detected operation states as the input patterns.

43. The abnormality detection system according to claim 27, wherein:

the place is a house;

said abnormality detection system further comprises a home network operable to connect a plurality of electrical household appliances which are located in the house;

said abnormality detection device further includes a controller operable to control a plurality of the electrical household appliances via said home network; and

said input unit is operable to detect operation states of a plurality of the electrical household appliances via said home network and to acquire the detected operation states as the input patterns.

31. An abnormality detection method for detecting an occurrence of an abnormality in an event under observation, said abnormality detection method comprising:

acquiring a sequence of an input pattern that is data depending upon the event;

analyzing a characteristic of a transition in the sequence of the input pattern acquired in said acquiring of the sequence of the input pattern;

comparing the characteristic of the transition analyzed in said analyzing of the characteristic of the transition with a predetermined reference value, and judging that an abnormality has occurred in the event when the characteristic and the reference value are not approximate to each other within a predetermined range; and

outputting an occurrence of the abnormality when said judging that the abnormality has occurred judges that the abnormality has occurred;

wherein in said acquiring of the sequence of the input pattern, a plurality of small motion detection sensors located in a plurality of places in a house are utilized for acquiring the input pattern, and a sensor pattern that is a combination of data indicating whether or not there is a small motion outputted from a plurality of the small motion detection sensors is acquired as the input pattern; and

wherein in said analyzing of the characteristic of the transition, a Markov chain in the sequence of the input pattern is calculated, and a characteristic of the calculated Markov chain is analyzed as the analysis.

32. The abnormality detection method according to claim 31, wherein:

in said analyzing of the characteristic of the transition, an appearance frequency for each type of the transition in the sequence of the input pattern is calculated as the analysis; and

in said comparing of the characteristic of the transition, whether or not an abnormality has occurred is judged by comparing the input pattern acquired in said acquiring of the sequence of the input pattern with a reference input pattern for the appearance frequency.

33. The abnormality detection method according to claim 31, wherein:

said analyzing of the characteristic of the transition, a duration time distribution that is a distribution of time which is required for the transition in the sequence of the input pattern is calculated as the analysis; and

in said comparing of the characteristic of the transition, whether or not an abnormality has occurred is judged by comparing the input pattern acquired in said acquiring of the sequence of the input pattern with a reference input pattern for the duration time distribution.

34. The abnormality detection method according to claim 31, further comprising transforming the sequence of the input pattern acquired in said acquiring of the sequence of the input pattern into a cluster sequence that is a predetermined representative input pattern;

wherein in said analyzing of the characteristic of the transition, the characteristic in the cluster sequence which is transformed in said transforming of the sequence of the input pattern is analyzed.

35. The abnormality detection method according to claim 31, wherein the reference value is a value, for a reference event, which is obtained by

acquiring the sequence of the input pattern in advance in said acquiring of the of the sequence of the input pattern, and

analyzing the characteristic in said analyzing of the characteristic of the transition.

36. The abnormality detection method according to claim 31, wherein the reference value is a value specified by an operator.

37. The abnormality detection method according to claim 31, wherein in said acquiring of the sequence of the input pattern, the sequence of the input pattern is acquired from an operator.

38. The abnormality detection method according to claim 31, wherein said outputting of the occurrence of the abnormality reports that the abnormality has occurred, to a predetermined destination via a transmission channel.

39. The abnormality detection method according to claim 31, wherein:

the reference value is a collection of local reference values in each time interval which satisfies a predetermined condition; and

in said judging that an abnormality has occurred, whether or not an abnormality has occurred is judged by comparing the characteristic with the local reference value in each time interval which satisfies the predetermined condition.

40. A program for detecting that an abnormality has occurred in an event under observation, said program causing a computer to execute:

acquiring a sequence of an input pattern that is data depending upon the event;

analyzing a characteristic of a transition in the sequence of the input pattern acquired in said acquiring of the sequence of the input pattern;

comparing the characteristic of the transition analyzed in said analyzing of the characteristic of the transition with a predetermined reference value, and judging that an abnormality has occurred in the event when the characteristic and the reference value are not approximate to each other within a predetermined range; and

outputting an occurrence of the abnormality when said judging that the abnormality has occurred judges that the abnormality has occurred;

wherein in said acquiring of the sequence of the input pattern, a plurality of small motion detection sensors located in a plurality of places in a house are utilized for acquiring the input pattern, and a sensor pattern that is a combination of data indicating whether or not there is a small motion outputted from a plurality of the small motion detection sensors is acquired as the input pattern; and

wherein in said analyzing of the characteristic of the transition, a Markov chain in the sequence of the input pattern is calculated, and a characteristic of the calculated Markov chain is analyzed as the analysis.