Anomaly detection system, anomaly detection method, and program

Abstract

The present disclosure addresses the problem of detecting the occurrence of physical abnormality. An abnormality detection system (10) comprises an acquisition unit (51), a determination unit (52), and an accumulation processing unit (53). The acquisition unit (51) acquires, from an emergency notification system (90), detection data detected by one or more sensors (91). The emergency notification system (90) comprises: the one or more sensors (91) that detect detection data relating to the living conditions of a resident (P1) living in a residence (H1); a monitoring device (92) that monitors the occurrence of an abnormality relating to the living conditions on the basis of the detection data detected by the one or more sensors (91); and a monitoring server (94) which is notified by the monitoring device (92) of an occurrence of an abnormality. The determination unit (52) determines whether or not the resident (P1) is experiencing a physical abnormality on the basis of the detection data acquired by the acquisition unit (51). The accumulation processing unit (53) accumulates, in a storage unit (6), detection data detected by the one or more sensors (91) during a period following the determination by the determination unit (52) that the resident (P1) has been experiencing a physical abnormality.

Description

[Technical Field]

[0001] The present disclosure relates to an anomaly detection system, an anomaly detection method, and a program. [Background technology]

[0002] Patent Document 1 describes an anomaly detection system. The anomaly detection system of Patent Document 1 includes a sensor, a behavior prediction unit, and an alert mode operation control unit. The sensor detects human behavior. The behavior prediction unit predicts human behavior using a machine learning model based on information detected by the sensor. When the difference between an average behavior label indicating a person's normal behavior and a predicted behavior label determined by the behavior prediction unit exceeds a threshold, the alert mode operation control unit sets the sensor to an alert mode for detailed detection and determines whether or not there is an abnormality in the person.

[0003] Patent document 1 describes that the alert mode operation control unit shortens the measurement interval of the sensor and sets it to alert mode, and that in the sensor's alert mode, it determines whether or not there is something wrong with the person based on images captured by a camera, determines whether or not there is something wrong with the person based on audio picked up by a microphone, determines whether or not there is something wrong with the person based on information detected by a vital sign monitor, and determines whether or not there is something wrong with the person based on a sensor installed in a self-propelled home appliance. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2020-160608 Summary of the Invention

[0005] In an anomaly detection system such as the anomaly detection system described in Patent Document 1, it is sometimes desirable to detect the occurrence of a physical anomaly that may be a sign of an abnormality in a person.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and aims to provide an anomaly detection system, an anomaly detection method, and a program that are capable of detecting the occurrence of a physical anomaly.

[0007] An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, No. 1 The acquisition unit receives one or more emergency call information from an emergency call system. No. 1 Detected by the sensor No. 1 The emergency notification system acquires detection data related to the living conditions of the resident living in the dwelling unit. No. 1 The one or more detecting data No. 1 a sensor and the one or more No. 1 The sensor detects No. 1 The system includes a monitoring device that monitors for the occurrence of an abnormality in the living situation based on the detected data, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. No. 1 The determination unit determines the No. 1 The accumulation processing unit determines whether or not there is any physical abnormality in the resident based on the detected data. No. 1 The one or more occurrences of the physical abnormality in the resident during a period after the determination unit determines that the physical abnormality has occurred in the resident. No. 1 The sensor detects No. 1 The detected data is stored in a storage unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor, and detects second detection data related to the living situation of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit. The second determination unit makes a determination regarding the resident's lifestyle habits based on at least one of the first detection data and the second detection data. The second determination unit makes a determination regarding lack of exercise as the resident's lifestyle habits based on the length of time outside the resident, which is the length of time the resident spends outside the dwelling unit in a day, and the amount of movement of the resident within the dwelling unit, which are obtained from at least one of the first detection data and the second detection data. The second determination unit determines that the resident is at risk regarding the lifestyle habits when the proportion of days in which the length of time outside the dwelling unit is shorter than the length of time outside the dwelling unit threshold and the amount of movement smaller than the movement amount threshold, among the number of days in a determination period of two or more days, is equal to or greater than a determination threshold. An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, a first determination unit, and an accumulation processing unit. The acquisition unit acquires first detection data detected by one or more first sensors from an emergency notification system. The emergency notification system includes the one or more first sensors that detect the first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. The first determination unit determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit. The accumulation processing unit accumulates the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident in a memory unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor that detects second detection data related to the living conditions of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit. The second determination unit determines the lifestyle habits of the resident based on at least one of the first detection data and the second detection data. The second determination unit determines whether the resident is at risk for lack of exercise as the lifestyle habit of the resident based on a sedentary duration, which is the length of time the resident is continuously sitting, obtained from at least one of the first detection data and the second detection data. The second determination unit determines that the resident is at risk for the lifestyle habit when the proportion of days in which the sedentary duration is longer than a sedentary duration threshold, out of the number of days in a determination period of two or more days, is equal to or greater than a determination threshold. An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, a first determination unit, and an accumulation processing unit. The acquisition unit acquires first detection data detected by one or more first sensors from an emergency notification system. The emergency notification system includes the one or more first sensors that detect the first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. The first determination unit determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit. The accumulation processing unit accumulates the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident in a memory unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor that detects second detection data related to the living conditions of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit that determines the lifestyle habits of the resident based on at least one of the first detection data and the second detection data. The second determination unit determines that the resident is at risk for the lifestyle habits if the proportion of days during which the number of meals is less than a threshold number of times among the number of days in a determination period that is two or more days is equal to or greater than a determination threshold, or if the variation in the meal start times within the determination period is equal to or greater than a determination threshold. An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, a first determination unit, and an accumulation processing unit. The acquisition unit acquires first detection data detected by one or more first sensors from an emergency notification system. The emergency notification system includes the one or more first sensors that detect the first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. The first determination unit determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit. The accumulation processing unit accumulates the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident in a memory unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor that detects second detection data related to the living conditions of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit. The second determination unit determines the lifestyle habits of the resident based on at least one of the first detection data and the second detection data. The second determination unit determines the sleep habits of the resident as the lifestyle habits based on a bedtime, which is the time when the resident goes to bed, and a sleep duration, which is the length of time the resident is asleep, obtained from at least one of the first detection data and the second detection data. The second determination unit determines that the resident is at risk for the lifestyle habits when a variation in at least one of the bedtime and the sleep duration within a determination period of two days or more is equal to or greater than a determination threshold. An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, a first determination unit, and an accumulation processing unit. The acquisition unit acquires first detection data detected by one or more first sensors from an emergency notification system. The emergency notification system includes the one or more first sensors that detect the first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. The first determination unit determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit. The accumulation processing unit accumulates the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident in a memory unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor that detects second detection data related to the living conditions of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit. The second determination unit makes a determination regarding the resident's lifestyle habits based on at least one of the first detection data and the second detection data. The second determination unit makes a determination regarding the resident's biological clock as the lifestyle habits of the resident based on the brightness of a room in the dwelling unit assigned to the resident at a wake-up time, which is the time the resident wakes up, obtained from at least one of the first detection data and the second detection data. The second determination unit determines that the resident is at risk regarding the lifestyle habits when the brightness of the room at the wake-up time is equal to or less than a brightness threshold. An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, a first determination unit, and an accumulation processing unit. The acquisition unit acquires first detection data detected by one or more first sensors from an emergency notification system. The emergency notification system includes the one or more first sensors that detect the first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. The first determination unit determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit. The accumulation processing unit accumulates the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident in a memory unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor that detects second detection data related to the living conditions of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit. The second determination unit determines the lifestyle habits of the resident based on at least one of the first detection data and the second detection data. The second determination unit determines the living environment as the lifestyle habits of the resident based on the room temperature when the resident is present in a room of the dwelling unit, which is obtained from at least one of the first detection data and the second detection data. The second determination unit determines that the resident is at risk for the lifestyle habits when the proportion of days during which the low temperature time length, which is the length of time the room temperature is lower than the temperature threshold, is greater than or equal to a determination threshold, among the number of days in a determination period of two or more days. An anomaly detection system according to one aspect of the present disclosure includes an acquisition unit, a first determination unit, and an accumulation processing unit. The acquisition unit acquires first detection data detected by one or more first sensors from an emergency notification system. The emergency notification system includes the one or more first sensors that detect the first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. The first determination unit determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit. The accumulation processing unit accumulates the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident in a memory unit. The acquisition unit further acquires the second detection data from a second sensor. The second sensor is a sensor other than the first sensor that detects second detection data related to the living conditions of the resident living in the dwelling unit. The anomaly detection system further includes a second determination unit. The second determination unit makes a determination regarding the resident's lifestyle habits based on at least one of the first detection data and the second detection data. A plurality of the residents live in the dwelling unit. The plurality of residents are assigned to a plurality of rooms in the dwelling unit, respectively. The anomaly detection system further includes a setting unit that sets a room among the plurality of rooms in which the function of the second determination unit is to be enabled.

[0008] A method for detecting an anomaly according to one aspect of the present disclosure includes: No. 1 The acquisition step includes a determination step and a storage step. No. 1 The emergency notification system acquires detection data detected by a sensor. No. 1The one or more detecting data No. 1 a sensor and the one or more No. 1 The sensor detects No. 1 The system includes a monitoring device that monitors for the occurrence of an abnormality in the living situation based on the detected data, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device. No. 1 The determining step is performed by determining whether the No. 1 The accumulation processing step includes determining whether or not there is any physical abnormality in the resident based on the detected data. No. 1 During a period after it is determined in the determining step that the physical abnormality has occurred in the resident, No. 1 The sensor detects No. 1 This includes storing the detected data in a storage unit. The acquisition step further includes acquiring the second detection data from a second sensor. The second sensor is a sensor other than the first sensor, and detects second detection data related to the living situation of the resident living in the dwelling unit. The anomaly detection system further includes a second determination step. The second determination step includes making a determination regarding the resident's lifestyle habits based on at least one of the first detection data and the second detection data. The second determination step includes making a determination regarding lack of exercise as the resident's lifestyle habits based on a length of time outside the resident, which is the length of time the resident spends outside the dwelling unit each day, and an amount of movement by the resident within the dwelling unit, which are obtained from at least one of the first detection data and the second detection data. The second determination step includes determining that the resident is at risk regarding the lifestyle habits when the proportion of days during a determination period, which is two or more days, during which the length of time outside the dwelling unit is shorter than a threshold for length of time outside the dwelling unit and the amount of movement by the resident is smaller than a threshold for amount of movement is equal to or greater than a determination threshold.

[0009] A program according to one aspect of the present disclosure is a program for causing one or more processors to execute the anomaly detection method. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram of a monitoring system including an anomaly detection system according to the first embodiment. [Figure 2] FIG. 2 is a diagram for explaining an outline of a dwelling unit to which the monitoring system is applied. [Figure 3] FIG. 3 is a flowchart of a processing method executed in the monitoring system. [Figure 4] FIG. 4 is a block diagram of a monitoring system including the anomaly detection system of the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] The drawings described in the following embodiments are schematic drawings, and the ratios of the sizes and thicknesses of the components in the drawings do not necessarily reflect the actual dimensional ratios.

[0012] (1) Embodiment 1 An anomaly detection system 10 according to a first embodiment will be described with reference to the drawings.

[0013] (1.1) Overview The anomaly detection system 10 (see FIG. 1) of this embodiment is a system for detecting the occurrence of a physical anomaly in a resident P1 living in a dwelling unit H1 (see FIG. 2). The anomaly detection system 10, in particular, works in cooperation with an emergency notification system 90 to detect the occurrence of a physical anomaly in the resident P1.

[0014] The dwelling unit H1 may be a detached house or one or more dwelling units in an apartment building. The resident P1 of the dwelling unit H1 may be one or more. In this embodiment, it is assumed that the dwelling unit H1 is a detached house and that the resident P1 lives alone in the dwelling unit H1.

[0015] As shown in FIG. 1, the anomaly detection system 10 includes an acquisition unit 51, a determination unit 52, and an accumulation processing unit 53.

[0016] The acquisition unit 51 acquires detection data from the emergency notification system 90. The emergency notification system 90 monitors the occurrence of abnormalities related to the living conditions of the resident P1 living in the dwelling unit H1. As shown in Figures 1 and 2, the emergency notification system 90 includes one or more sensors 91, a monitoring device 92, and a monitoring server 94. The sensor 91 detects detection data related to the living conditions of the resident P1 living in the dwelling unit H1. The monitoring device 92 monitors the occurrence of abnormalities related to the living conditions of the resident P1 living in the dwelling unit H1 based on the detection data. The monitoring server 94 is notified by the monitoring device 92 of the occurrence of abnormalities related to the living conditions of the resident P1 living in the dwelling unit H1.

[0017] The determination unit 52 determines whether or not there is a physical abnormality in the resident P1 based on the detection data acquired by the acquisition unit 51. The determination unit 52 detects the occurrence of a physical abnormality that may be a sign of a physical abnormality in the resident P1 detected (monitored) by the emergency notification system 90, for example. In the present disclosure, "a physical abnormality in the resident P1" may include an abnormality related to the physical functions of the resident P1. An abnormality related to the physical functions may include, for example, a decline in various physical functions such as muscle strength, eyesight, the circulatory system, and the nervous system. "A physical abnormality in the resident P1" may include an abnormality related to the brain functions of the resident P1. An abnormality related to the brain functions may include, for example, a decline in various brain functions such as a decline in cognitive function.

[0018] The accumulation processing unit 53 accumulates in the storage unit 6 the detection data detected by one or more sensors 91 during the period after the determination unit 52 determines that a physical abnormality has occurred in the resident P1.

[0019] In the anomaly detection system 10 of this embodiment, the determination unit 52 determines whether or not there is a physical anomaly in the resident P1, using detection data detected by one or more sensors 91 provided in the emergency notification system 90. By cooperating with the emergency notification system 90, the anomaly detection system 10 of this embodiment can detect the occurrence of a physical anomaly in the resident P1 that may be a sign of an abnormality in the person detected by the emergency notification system 90.

[0020] (1.2) Details (1.2.1) Overall structure A monitoring system 100 including an anomaly detection system 10 of this embodiment will be described below with reference to FIGS.

[0021] The monitoring system 100 is a system for monitoring a resident P1 living in a dwelling unit H1, and for reporting to the outside of the dwelling unit H1 if an event that requires reporting to the outside occurs in the dwelling unit H1 or the resident P1. As shown in FIG. 1, the monitoring system 100 includes an emergency reporting system 90 in addition to an anomaly detection system 10.

[0022] The emergency notification system 90 monitors for abnormalities in the living conditions of the resident P1 residing in the dwelling unit H1. In this disclosure, "an abnormality in the living conditions of the resident P1 residing in the dwelling unit H1" refers to a situation in which the dwelling unit H1 or the resident P1 is in a state different from normal and requires immediate attention from another person. The "other person" here refers to a person other than the resident P1 residing in the dwelling unit H1, such as the resident P1's family, relatives, or friends, a member of a national or local government, a member of a nonprofit organization or company providing a monitoring service, or, if the dwelling unit H1 is an apartment building, the apartment manager. The term "immediately" here refers to a time period ranging from approximately one second to one day, depending on the type of abnormality. Specific examples of "an abnormality in the living conditions of the resident P1 residing in the dwelling unit H1" include the intrusion of a suspicious person into the dwelling unit H1, the occurrence of a disaster (fire, flooding, earthquake, etc.) in the dwelling unit H1, or the occurrence of a physical abnormality in the resident P1.

[0023] The anomaly detection system 10 works in conjunction with the emergency notification system 90 (using data detected by the emergency notification system 90) to detect a "physical anomaly" in the resident P1 of the dwelling unit H1. A "physical anomaly" is, for example, a sign of a "physical abnormality" detected by the emergency notification system 90. A person's physical condition may transition, for example, from a relatively minor "anomaly" to a relatively serious "abnormality."

[0024] In this way, the monitoring system 100, which includes the anomaly detection system 10 in addition to the emergency notification system 90, can detect not only physical abnormalities in the resident P1, but also physical anomalies in the resident P1.

[0025] (1.2.2) Emergency notification system As shown in FIG. 1, the emergency notification system 90 includes one or more sensors (hereinafter also referred to as "first sensors") 91, a monitoring device 92, a gateway device (hereinafter also referred to as "first gateway device") 93, and a monitoring server 94. As shown in FIG. 2, the first sensor 91, the monitoring device 92, and the first gateway device 93 are installed in a dwelling unit H1. The monitoring server 94 is installed outside the dwelling unit H1. The emergency notification system 90 detects the presence or absence of an abnormality in the living situation of a resident P1 living in the dwelling unit H1 using the first sensor 91 and the monitoring device 92, and when an abnormality occurs, the monitoring device 92 sends an abnormality signal S10 to the monitoring server 94 to notify the user of the monitoring server 94 of the occurrence of the abnormality.

[0026] 2, the first sensor 91 is disposed at an appropriate location in the dwelling unit H1. The first sensor 91 detects detection data related to the living situation of a resident P1 living in the dwelling unit H1. Hereinafter, for convenience, the detection data detected by the first sensor 91 will also be referred to as "first detection data."

[0027] The first sensor 91 may include a security sensor 911 that is installed on a window or door of the dwelling unit H1 to detect the intrusion of a suspicious person. The first detection data detected by the security sensor 911 may indicate, for example, the open / closed state (whether the window or door on which the security sensor 911 is installed) of the window or door.

[0028] The first sensor 91 may include an infrared human sensor 912 that is installed inside or outside the dwelling unit H1 and detects the presence or absence of a suspicious person. The first detection data detected by the infrared human sensor 912 may indicate, for example, the presence or absence of a human body within the detection area.

[0029] The first sensor 91 may include a fire detector 913 that is installed on the ceiling of the dwelling unit H1 or the like and detects the occurrence of a fire. The first detection data detected by the fire detector 913 may indicate, for example, the status of the occurrence of a fire within the detection area (the determination result as to whether or not a fire has occurred).

[0030] The first sensor 91 may include an emergency notification device 914 that is held by the resident P1 and is operated by the resident P1 to notify the resident P1 of an abnormality when a physical abnormality occurs or when an abnormality occurs in the dwelling unit H1 (such as an intrusion by a suspicious person or a disaster). The first detection data detected by the emergency notification device 914 may indicate, for example, the state (on or off) of whether an operation button (emergency notification button) is being operated by the resident P1.

[0031] The first sensor 91 transmits a detection signal (hereinafter also referred to as "first detection signal") S1 to the monitoring device 92. The first sensor 91 transmits the first detection signal S1 to the monitoring device 92, for example, wirelessly. The first detection signal S1 is a signal that includes first detection data related to the living situation of a resident P1 living in the dwelling unit H1, detected by the first sensor 91.

[0032] The monitoring device 92 is installed in the dwelling unit H1. The monitoring device 92 receives a first detection signal S1 from a first sensor 91. The monitoring device 92 monitors the occurrence of an abnormality in the living conditions of a resident P1 of the dwelling unit H1 based on the first detection data included in the first detection signal S1.

[0033] The monitoring device 92 determines whether or not there is an abnormality in the living situation based on the received first detection data. For example, the monitoring device 92 has an alert mode and a normal mode as operation modes. The alert mode is a mode that is set, for example, when the resident P1 leaves the dwelling unit H1. The normal mode is a mode that is set, for example, when the resident P1 is in the dwelling unit H1. The monitoring device 92 determines whether or not there is an abnormality in the living situation based on the first detection data and the operation mode.

[0034] For example, in alert mode, the monitoring device 92 determines that an abnormality (an intrusion of a suspicious person) has occurred when it receives first detection data indicating that a window or door has been opened from a security sensor 911 serving as the first sensor 91. For example, in alert mode, the monitoring device 92 determines that an abnormality (an intrusion of a suspicious person) has occurred when it receives first detection data indicating that a human body has been detected within the detection area from an infrared human presence sensor 912 serving as the first sensor 91. For example, in alert mode, the monitoring device 92 determines that an abnormality (a fire) has occurred when it receives first detection data indicating that a fire has occurred from a fire detector 913 serving as the first sensor 91, regardless of whether it is in alert mode or normal mode. For example, in alert mode, the monitoring device 92 determines that an abnormality (an event that the resident P1 has determined to be abnormal) has occurred when it receives first detection data indicating that an operation button has been operated from an emergency call switch serving as the first sensor 91.

[0035] When the monitoring device 92 determines that there is an abnormality in the living conditions, it transmits an abnormality signal S10 to the monitoring server 94. As shown in FIG. 1 , the monitoring device 92 is communicatively connected to the monitoring server 94 via a first gateway device 93. The first gateway device 93 is a device that mainly relays communication between the monitoring device 92 and the monitoring server 94. The first gateway device 93 is installed in the dwelling unit H1. The first gateway device 93 relays communication between the monitoring device 92 and the monitoring server 94 via a communication network NT1 that includes the Internet. The monitoring device 92 transmits the abnormality signal S10 to the monitoring server 94 via the first gateway device 93 and the communication network NT1.

[0036] The monitoring device 92 transmits the abnormality signal S10 including information on the type of abnormality that has occurred. For example, if it is determined that an abnormality has occurred based on the first detection data from the security sensor 911 or the infrared human presence sensor 912, the monitoring device 92 outputs the abnormality signal S10 including information that a suspicious person may have intruded. For example, if it is determined that an abnormality has occurred based on the first detection data from the fire detector 913, the monitoring device 92 outputs the abnormality signal S10 including information that a fire may have occurred. For example, if it is determined that an abnormality has occurred based on the first detection data from the emergency notification device 914, the monitoring device 92 outputs the abnormality signal S10 including information that the emergency notification device 914 has been operated by the resident P1.

[0037] The monitoring server 94 receives the abnormality signal S10 from the monitoring device 92. The monitoring server 94 is capable of receiving the abnormality signal S10 from a plurality of monitoring devices 92 installed in a plurality of dwelling units H1, respectively.

[0038] When the monitoring server 94 receives the abnormality signal S10, it presents abnormality occurrence information indicating that the abnormality signal S10 has been received to the user of the monitoring server 94 via a display device such as a monitor, an audio output device such as a speaker, or the like. The abnormality occurrence information may include, for example, the address of the dwelling unit H1 in which the monitoring device 92 that sent the abnormality signal S10 is installed, the name of the resident P1 of that dwelling unit H1, the type of abnormality that has occurred, etc. Depending on the content of the abnormality occurrence information, the user of the monitoring server 94 may check with the resident P1, for example, by calling the resident P1 to confirm his or her safety or by rushing to the dwelling unit H1.

[0039] (1.2.3) Anomaly detection system As shown in FIG. 1, the anomaly detection system 10 includes a sensor 1 other than the first sensor 91 (hereinafter also referred to as the "second sensor"), a gateway device 2 other than the first gateway device 93 (hereinafter also referred to as the "second gateway device"), and a processing device 3.

[0040] (1.2.3.1) Second sensor The second sensor 1 is installed in the dwelling unit H1 as shown in Fig. 2. The second sensor 1 is a sensor that is not included in the emergency notification system 90. The second sensor 1 is placed in an appropriate location in the dwelling unit H1.

[0041] The second sensor 1 detects detection data related to the living situation of the resident P1 living in the dwelling unit H1, similar to the first sensor 91. Hereinafter, for convenience, the detection data detected by the second sensor 1 will also be referred to as "second detection data."

[0042] The second sensor 1 may include an opening / closing sensor 11 that is installed on a window or door of the dwelling unit H1 and detects whether the resident P1 is at home and the movement status within the dwelling unit H1. The second detection data detected by the opening / closing sensor 11 may indicate, for example, the opening / closing status (open or closed) of the window or door on which the opening / closing sensor 11 is installed.

[0043] The second sensor 1 may include a temperature and humidity sensor 12 that is installed on a wall surface of the dwelling unit H1 or the like and detects at least one of temperature and humidity. The second detection data detected by the temperature and humidity sensor 12 may indicate, for example, the value of temperature and / or humidity.

[0044] The second sensor 1 may include an illuminance sensor 13 that is installed on the ceiling of the dwelling unit H1 or the like and detects illuminance. The second detection data detected by the illuminance sensor 13 may indicate, for example, the value of illuminance.

[0045] The second sensor 1 may include a radio wave sensor 14 that is installed on the ceiling of the dwelling unit H1 or the like and detects the movement of residents within the dwelling unit H1. The second detection data detected by the radio wave sensor 14 may indicate, for example, the presence or absence of a human body within the detection area.

[0046] The second sensor 1 may include a power sensor 15 that detects power data related to electricity usage in the dwelling unit H1. The power sensor 15 is installed, for example, in a distribution board D1 installed in the dwelling unit H1. The power sensor 15 may be at least one of a current sensor and a voltage sensor. The second detected data detected by the power sensor 15 may indicate, for example, a power value, a current value, a voltage value, etc.

[0047] It should be noted that the function of the second sensor 1 may overlap at least partially with the function of the first sensor 91.

[0048] The second sensor 1 outputs a detection signal (hereinafter also referred to as "second detection signal") S2. The second sensor 1 outputs the second detection signal S2, for example, in the form of a wireless signal. The second detection signal S2 is a signal that includes second detection data related to the living situation of the resident P1 living in the dwelling unit H1, detected by the second sensor 1.

[0049] (1.2.3.2) Second gateway device The second gateway device 2 is installed in the dwelling unit H1. The second gateway device 2 has a function of relaying communication between the second sensor 1 and the processing device 3. The second gateway device 2 relays communication between the second sensor 1 and the processing device 3 via a communication network NT1 including the Internet. The second sensor 1 transmits a second detection signal S2 to the processing device 3 via the second gateway device 2 and the communication network NT1.

[0050] In the monitoring system 100 of this embodiment, the second gateway device 2 further has a function of relaying communication between the first sensor 91 and the processing device 3. The second gateway device 2 relays communication between the first sensor 91 and the processing device 3 via a communication network NT1. The first sensor 91 transmits a first detection signal S1 to the processing device 3 via the second gateway device 2 and the communication network NT1.

[0051] The second gateway device 2 may further have a function as a controller of a Home Energy Management System (HEMS) in addition to the function of a gateway.

[0052] (1.2.3.3) Processing Unit The processing device 3 is located outside the dwelling unit H1. The processing device 3 may be a server. The processing device 3 may be composed of one or more server devices, and such server devices may constitute a cloud system.

[0053] 1, the processing device 3 includes a communication unit 4, a processing unit 5, and a storage unit 6. The processing device 3 may include an operation unit (touch screen panel, mouse, switch, etc.) that accepts operations from a user, and a presentation unit (display, speaker, etc.) that presents various information to the user of the processing device 3.

[0054] The communication unit 4 includes a communication interface. The communication unit 4 is communicatively connected to the first sensor 91 via the communication network NT1. The communication unit 4 is communicatively connected to the second sensor 1 via the communication network NT1.

[0055] The processing unit 5 includes a computer system having one or more processors and a memory. The processor of the computer system executes a program recorded in the memory of the computer system to realize the functions of the processing unit 5. The program may be recorded in the memory, may be provided via a telecommunications line such as the Internet, or may be provided by recording it on a non-transitory recording medium such as a memory card.

[0056] The storage unit 6 stores various information. The storage unit 6 includes, for example, a RAM (Random Access Memory), an EEPROM (Electrically Erasable Programmable Read Only Memory), etc. The storage unit 6 may be integrated with the memory of the processing unit 5.

[0057] 1, the processing unit 5 includes an acquisition unit 51, a determination unit 52, an accumulation processing unit 53, a progress monitoring unit 54, a report creation unit 55, a notification unit 56, and a warning unit 57. The acquisition unit 51, the determination unit 52, the accumulation processing unit 53, the progress monitoring unit 54, the report creation unit 55, the notification unit 56, and the warning unit 57 represent various functions of the processing unit 5 (functions for performing various processes).

[0058] The processing performed by each unit of the processing unit 5 will be described below.

[0059] (1.2.3.3.1) Acquisition process The acquisition unit 51 acquires first detection data detected by the first sensor 91 from the emergency notification system 90. Here, the communication unit 4 of the processing device 3 receives the first detection signal S1 from the first sensor 91, and the acquisition unit 51 acquires the first detection data included in the first detection signal S1.

[0060] The acquisition unit 51 acquires, as first detection data, data indicating the open / close state of a window or door on which the security sensor 911 is installed, from, for example, a security sensor 911 serving as the first sensor 91. The acquisition unit 51 acquires, as first detection data, data indicating the presence or absence of a human body within a detection area, from, for example, an infrared human presence sensor 912 serving as the first sensor 91. The acquisition unit 51 does not necessarily have to acquire first detection data from all of the first sensors 91.

[0061] The acquisition unit 51 also acquires second detection data detected by the second sensor 1. Here, the communication unit 4 of the processing device 3 receives the second detection signal S2 from the second sensor 1, and the acquisition unit 51 acquires the second detection data included in the second detection signal S2.

[0062] The acquisition unit 51 acquires, as second detection data, data indicating the open / close status of the window or door on which the opening / closing sensor 11 is installed, for example, from the opening / closing sensor 11 serving as the second sensor 1. The acquisition unit 51 acquires, as second detection data, data indicating temperature and / or humidity values, for example, from the temperature and humidity sensor 12 serving as the second sensor 1. The acquisition unit 51 acquires, as second detection data, data indicating illuminance values, for example, from the illuminance sensor 13 serving as the second sensor 1. The acquisition unit 51 acquires, as second detection data, data indicating the presence or absence of a human body within the detection area, for example, from the radio wave sensor 14 serving as the second sensor 1. The acquisition unit 51 acquires, as second detection data, data related to the electricity usage status in the dwelling unit H1 (power data), for example, from the power sensor 15 serving as the second sensor 1. The power data may include power values, current values, voltage values, etc. detected by the power sensor 15.

[0063] The acquisition unit 51 also acquires operation data indicating the manner of operation performed on an operation unit for operating the electrical appliance. The electrical appliance is disposed in the dwelling unit H1. The electrical appliance is, for example, a television set, an intercom unit (indoor station), an information terminal, etc. The operation unit is, for example, an operation button on a remote controller for operating the television set, etc., a touch screen panel or operation button provided in the intercom unit, a touch screen panel or operation button provided in the information terminal, etc. The electrical appliance may be, for example, a monitoring device 92 or an emergency call device 914 provided in the emergency call system 90. In this case, the operation unit may be, for example, a touch screen panel or operation button (emergency call button) provided in the monitoring device 92, or an operation button (emergency call button) provided in the emergency call device 914, etc.

[0064] The operation mode indicated by the operation data includes at least one of a ratio of the number of long presses and a ratio of the number of consecutive presses. The ratio of the number of long presses is the ratio of the number of times a button as an operation unit is pressed for a time period longer than a reference time to the number of times the button is pressed. The ratio of the number of consecutive presses is the ratio of the number of times the button is pressed at a time interval shorter than a reference time to the number of times the button is pressed.

[0065] "Operation data" is data that indicates the manner of operation performed on the operation unit, and can be detected by a current sensor, pressure sensor, capacitive touch sensor, etc., that the operation unit is equipped with. Therefore, in the following explanation, "operation data" will also be considered as a type of "detection data."

[0066] (1.2.3.3.2) Judgment process The determination unit 52 determines whether or not there is any physical abnormality in the resident P1 based on the detection data acquired by the acquisition unit 51. The determination unit 52 has the function of determining whether or not there is any physical abnormality in the resident P1 based on at least the first detection data. Here, the determination unit 52 determines whether or not there is any physical abnormality in the resident P1 based on the first detection data, the second detection data, and the operation data. That is, the determination unit 52 determines whether or not there is any physical abnormality in the resident P1 based further on the power data. Furthermore, the determination unit 52 determines whether or not there is any physical abnormality in the resident P1 based further on the operation data.

[0067] In the anomaly detection system 10 of this embodiment, the determination unit 52 determines that a decline in cognitive function of the resident P1 is a physical anomaly of the resident P1.

[0068] The following describes an example of a method for determining whether or not there is a physical abnormality (decline in cognitive function) in the resident P1 based on the detection data.

[0069] When the judgment conditions are satisfied, the judgment unit 52 judges that something physically unusual has occurred in the resident P1. The judgment conditions include the following first to seventh conditions. For example, when any one of the first to seventh conditions is satisfied, the judgment unit 52 judges that the judgment conditions are satisfied. However, this is not limiting, and the judgment unit 52 may also judge whether the judgment conditions are satisfied based on an appropriate logical sum or logical product of the judgment results for two or more of the first to seventh conditions. Furthermore, the judgment conditions may include conditions other than the first to seventh conditions.

[0070] The first condition is that the temperature and / or humidity in the room where resident P1 is present in dwelling unit H1 is outside the normal living range, even though the air conditioner is running. In this case, it is possible that resident P1 is unable to sense the appropriate temperature, etc., with his / her skin, and therefore it can be determined that resident P1's cognitive function has declined. Whether the air conditioner is running can be determined, for example, based on detection data from power sensor 15, which serves as second sensor 1. Furthermore, whether the temperature and / or humidity in the room is outside the normal living range can be determined based on detection data from temperature and humidity sensor 12, which serves as second sensor 1.

[0071] The second condition is that the room in which resident P1 is located in dwelling unit H1 is dark, but the lighting fixtures in the room are not turned on. In this case, it is possible that resident P1 is unable to see the brightness necessary for daily life, and it can be determined that resident P1's cognitive function is impaired. Whether the room is dark or not can be determined, for example, based on detection data from illuminance sensor 13, which serves as second sensor 1. Furthermore, the lighting status of the lighting fixtures can be determined, for example, based on detection data from power sensor 15, which serves as second sensor 1.

[0072] The third condition is that the illuminance detected by the illuminance sensor 13 is not an appropriate value even though the lighting fixture in the room where the resident P1 is located in the dwelling unit H1 is turned on. In this case, it is possible that the resident P1 is unable to visually recognize the brightness necessary for daily life, and it can be determined that the resident P1's cognitive function has declined. Note that whether the lighting fixture is turned on can be determined based on, for example, detection data from the power sensor 15 serving as the second sensor 1. Furthermore, the event in which the illuminance detected by the illuminance sensor 13 is not an appropriate value can include cases where the light from the lighting is too bright or too dark.

[0073] The fourth condition is that there is an abnormality in the operation of the operation unit of the electrical device. The fourth condition may include the operation of the operation button (emergency call button) of the emergency call device 914 or the monitoring device 92 even though it is not an emergency. In this case, the resident P1's judgment, etc. may be impaired, and therefore it can be determined that the resident P1's cognitive function is impaired. The fourth condition may include the abnormality in the manner of operation performed on the operation unit. The fourth condition may include the percentage of long presses being lower than a threshold level. The fourth condition may include the percentage of continuous presses being equal to or higher than a threshold level. In this case, the resident P1 may not be operating the button normally, and therefore it can be determined that the resident P1's cognitive function is impaired. The fourth condition may include the operation method of the operation unit being changed compared to the previous method (e.g., one month ago). In this case, the resident P1's judgment, memory, etc. may be impaired, and therefore it can be determined that the resident P1's cognitive function is impaired. Note that the abnormality in the operation of the operation unit may be determined based on operation data, for example.

[0074] The fifth condition is that there is something abnormal about the resident P1's activities within the dwelling unit H1. The fifth condition may include the resident P1 being in a room (e.g., the living room) within the dwelling unit H1 all day. The fifth condition may include the resident P1 going to the toilet less than a threshold number of times per day (e.g., twice). In this case, there is a possibility that the resident P1 has few opportunities to go out, eat, or defecate, and is not performing activities necessary for daily life, so it can be determined that the resident P1's cognitive function is declining. Note that an abnormality in the resident P1's activities within the dwelling unit H1 may be determined, for example, based on detection data from the infrared human sensor 912 as the first sensor 91 or the radio wave sensor 14 as the second sensor 1.

[0075] The sixth condition is that there is an abnormality in the resident P1's movement within the dwelling unit H1. The sixth condition may include abnormalities in the resident P1's walking footsteps and / or moving speed. If the resident P1's walking footsteps and / or moving speed indicate signs of mild cognitive impairment (MCI), it can be determined that the resident P1's cognitive function is declining. The sixth condition may include the resident P1 not attempting to head to the room where the intercom device is installed (e.g., the living room) or the front door despite receiving a call from a visitor via the intercom device. The sixth condition may include an increase in the frequency of the resident P1 turning back in the hallway while attempting to move from one room to another. In this case, it can be determined that the resident P1's cognitive function is declining because there is a possibility that their judgment, memory, etc. are declining. The resident P1's walking footsteps and moving speed may be calculated based on detection data from the infrared human sensor 912 as the first sensor 91 or the radio wave sensor 14 as the second sensor 1. Furthermore, whether or not there has been movement from room to room can be determined based on, for example, detection data from the infrared human presence sensor 912 as the first sensor 91 or the radio wave sensor 14 as the second sensor 1.

[0076] The seventh condition is that there is an abnormality in the locking status of the dwelling unit H1. The seventh condition may include a high frequency of forgetting to lock the windows, front door, etc. when going out, at night, etc. (e.g., four or more times a week). In this case, the resident P1's judgment, attention, etc. may be declining, and therefore it can be determined that the resident P1's cognitive function has declined. Note that whether the resident P1 is out can be determined based on, for example, detection data from the infrared motion sensor 912 as the first sensor 91 or the radio wave sensor 14 as the second sensor 1. Furthermore, forgetting to lock the windows, front door, etc. can be determined based on, for example, detection data from the security sensor 911 as the first sensor 91 or the open / close sensor 11 as the second sensor 1. For example, if forgetting to lock the doors at night occurs, a record of this is stored in the memory unit 6 of the processing device 3. The determination unit 52 can determine the decline in the resident P1's cognitive function based on the history of records of forgetting to lock stored in the memory unit 6. If the door is left unlocked at night, the determination unit 52 may notify the monitoring device 92, for example, to notify the resident P1 that the door has been left unlocked (for example, by a speaker, buzzer, etc.).

[0077] (1.2.3.3.3) Accumulation processing The accumulation processing unit 53 accumulates in the memory unit 6 the detection data detected during the period after the determination unit 52 determines that a physical abnormality has occurred in the resident P1. Hereinafter, for convenience, the time when the determination unit 52 determines that a physical abnormality has occurred in the resident P1 will also be referred to as the "time of abnormality occurrence," and the period after the determination unit 52 determines that a physical abnormality has occurred in the resident P1 will also be referred to as the "warning period." In other words, the accumulation processing unit 53 accumulates in the memory unit 6 the detection data detected during the warning period (after the abnormality has occurred).

[0078] The accumulation processing unit 53 accumulates the first detection data in the storage unit 6. The accumulation processing unit 53 also accumulates the second detection data in the storage unit 6. The accumulation processing unit 53 also accumulates the operation data in the storage unit 6. The accumulation processing unit 53 stores the detection data in the storage unit 6 in chronological order, for example.

[0079] The accumulation processing unit 53 may accumulate, in the memory unit 6, detection data detected during a period in which the determination unit 52 determines that no physical abnormality has occurred in the resident P1. For convenience, the period in which the determination unit 52 determines that no physical abnormality has occurred in the resident P1 will hereinafter also be referred to as a "normal period." The types of detection data accumulated during normal periods may be the same as or less than the types of detection data accumulated during caution periods.

[0080] (1.2.3.3.4) Follow-up treatment During the caution period, the follow-up observation unit 54 observes changes over time in the physical abnormality of the resident P1 based on the detection data accumulated in the memory unit 6. When the determination unit 52 determines that a physical abnormality has occurred in the resident P1, the follow-up observation unit 54 observes whether there is a change (worsening or improvement) in the degree of the abnormality. For example, when the determination unit 52 determines that the cognitive function of the resident P1 has declined, the follow-up observation unit 54 observes whether the degree of decline has worsened from the stage of so-called mild cognitive impairment (MCI) to the stage of dementia.

[0081] The follow-up monitoring unit 54 may infer the extent of the abnormality by comparing the results with past follow-up monitoring results of the subject, resident P1, himself, or by comparing the results with other subjects. In the latter case, if a subject that can be used as a comparison standard can be set in the data, the follow-up monitoring unit 54 may compare the resident P1 with a specific subject as the comparison standard. Alternatively, the follow-up monitoring unit 54 may classify and group subjects based on similarities in their original symptoms, age, the nature of the abnormality, etc., and infer the extent of the abnormality for each group.

[0082] (1.2.3.3.5) Report creation process The report creation unit 55 creates a report. As shown in Fig. 1, the report creation unit 55 includes a normal time report creation unit 551 and an abnormal time report creation unit 552.

[0083] The normal time report creation unit 551 creates a report during a period (normal time period) in which the determination unit 52 determines that no physical abnormalities have occurred in the resident P1. For convenience, the report created by the normal time report creation unit 551 during a normal time period will be referred to below as a "normal time report."

[0084] The normal state report is a report that indicates that there is no physical abnormality in the resident P1. The content of the normal state report is not particularly limited as long as it can indicate that there is no physical abnormality in the resident P1 (that the resident P1 is in good health). The normal state report creation unit 551 may create the normal state report based on the detection data accumulated in the memory unit 6 (detection data accumulated during normal periods).

[0085] The normal state report creating unit 551 creates a normal state report, for example, periodically (for example, once a week, once a month, etc.).

[0086] The normal state report may include analysis results for five indicators of daily living activities related to the cognitive function of the resident P1. The five indicators of daily living activities related to the cognitive function are, for example, "activity level," "social participation level," "independence level," "device utilization level," and "quality of sleep." Each indicator is determined based on the content of the resident P1's activities. For example, the "activity level" is determined based on the resident P1's "walking" (amount of movement, walking pattern, etc.). The "social participation level" is determined based on the resident P1's "going out" (frequency of going out, time spent going out, etc.). The "independence level" is determined based on the resident P1's "toileting" (frequency of going to the toilet, time spent using the toilet, etc.). The "device utilization level" is determined based on the resident P1's "appliance operation" (amount of operation of the appliance, operation time, etc.). The "quality of sleep" is determined based on the resident P1's "sleep" (sleep duration, depth of sleep, etc.). The content of the resident P1's activities is obtained, for example, from the second detection data of the second sensor 1. In normal times reports, for example, evaluation results for each indicator are shown on a five-point scale.

[0087] The abnormality report creation unit 552 creates a report during the caution period. For convenience, the report created by the abnormality report creation unit 552 during the caution period will also be referred to as an "abnormality report" below. The abnormality report creation unit 552 creates a report (abnormality report) regarding physical abnormalities (decline in cognitive function) of the resident P1 based on the detection data accumulated in the memory unit 6 (detection data accumulated during the caution period). The abnormality report creation unit 552 creates the abnormality report, for example, using information on changes over time in physical abnormalities of the resident P1 observed by the follow-up observation unit 54.

[0088] The abnormality report creation unit 552 creates an abnormality report, for example, periodically (for example, once a week, once a month, etc.). The abnormality report creation unit 552 may create an abnormality report on an ad hoc basis, for example, when the determination unit 52 determines that a physical abnormality has occurred (when an abnormality occurs) or when the follow-up observation unit 54 determines that the degree of the abnormality has worsened. The abnormality report creation unit 552 may create an abnormality report on an ad hoc basis in response to a request from a notification destination of the abnormality report.

[0089] An abnormality report is a report indicating that a physical abnormality may have occurred in resident P1. The abnormality report may include, for example, the time when the physical abnormality is estimated to have occurred, the type of physical abnormality, the stage of progression of the physical abnormality, etc. The abnormality report may also include changes in the physical condition of resident P1 since the previous report. The abnormality report may also include improvement suggestions to alleviate the physical abnormality (e.g., recommended exercise, improved diet, etc.).

[0090] (1.2.3.3.6) Notification Processing The notification unit 56 notifies the content of the notification based on the determination result of the determination unit 52 to the outside.

[0091] As shown in FIG. 1, the notification unit 56 includes a normal time notification unit 561 and an abnormal time notification unit 562.

[0092] The normal state notification unit 561 notifies the outside that there is no physical abnormality in the resident P1. The normal state notification unit 561 notifies the notification destination of the normal state report.

[0093] The recipients of the normal report may be people related to resident P1. The recipients of the normal report may be, for example, family members or relatives of resident P1. The recipients of the normal report may include resident P1 himself. The recipients of the normal report may include resident P1's regular medical institution. The recipients of the normal report may be set in advance by resident P1, for example, when the anomaly detection system 10 is installed in dwelling unit H1.

[0094] The normal state notification unit 561 notifies the notification destination of a normal state report periodically (for example, once a week, once a month, etc.) during a normal state period. The notification interval of the normal state report is set in advance by the resident P1, etc., when the anomaly detection system 10 is installed in the dwelling unit H1, etc.

[0095] The normal state notification unit 561 notifies the normal state report in the form of electronic data to, for example, an information terminal (smartphone, personal computer, etc.) that can be operated by the notification recipient. The electronic data can be sent to the notification recipient by, for example, email, SMS (Short Message Service), SNS (Social Networking Service), etc.

[0096] Since the anomaly detection system 10 is provided with the normal state notification unit 561, people related to the resident P1 can know that no physical anomaly has occurred in the resident P1.

[0097] The abnormality notification unit 562 notifies the outside that a physical abnormality has occurred in the resident P1. The abnormality notification unit 562 notifies the notification destination of an abnormality report.

[0098] The recipients of the abnormality report may be persons related to the resident P1. The recipients of the abnormality report may be, for example, the family or relatives of the resident P1. The recipients of the abnormality report may include the resident P1 himself. The recipients of the abnormality report may include the resident P1's regular medical institution. The recipients of the abnormality report are set in advance by the resident P1, for example, when the abnormality detection system 10 is installed in the dwelling unit H1. The recipients of the abnormality report may be the same as the recipients of the normal state report.

[0099] The abnormality notification unit 562 notifies the notification destination of an abnormality report periodically (for example, once a week, once a month, etc.) during a caution period, for example. The interval for notifying the abnormality report is set in advance by the resident P1, for example, when the abnormality detection system 10 is installed in the dwelling unit H1. The abnormality notification unit 562 may also notify the notification destination of an abnormality report on an ad hoc basis, for example, when an abnormality occurs or when the degree of the abnormality worsens. The abnormality notification unit 562 may also notify the notification destination of an abnormality report on an ad hoc basis, in response to a request from the notification destination of the abnormality report.

[0100] The abnormality notification unit 562 notifies the abnormality report in the form of electronic data to, for example, an information terminal (smartphone, personal computer, etc.) that can be operated by the notification recipient. The electronic data can be sent to the notification recipient by, for example, email, SMS (Short Message Service), SNS (Social Networking Service), etc.

[0101] Because the anomaly detection system 10 is equipped with an anomaly notification unit 562, those related to resident P1 can be informed that resident P1 has experienced a physical anomaly (decline in cognitive function) and that attention is required.

[0102] (1.2.3.3.7) Attention Processing The attention calling unit 57 notifies the emergency notification system 90 that something unusual has happened to the resident P1 and that attention is required. The attention calling unit 57 notifies the emergency notification system 90 that something unusual has happened to the resident P1 during a period (attention required period) after the determination unit 52 determines that something unusual has happened to the resident P1.

[0103] For example, when an abnormality occurs (the point at which the judgment unit 52 judges that a physical abnormality has occurred in resident P1), the warning unit 57 sends a notification (hereinafter also referred to as a "warning notification") to the emergency notification system 90 indicating that a physical abnormality has occurred in resident P1.

[0104] Furthermore, the alert unit 57 may issue an alert notification to the emergency notification system 90, for example, when it receives a signal from the emergency notification system 90 notifying that an abnormality related to the living situation of the resident P1 living in the dwelling unit H1 has occurred during the caution period (the period after the occurrence of an abnormality). In other words, when an abnormality related to the living situation of the resident P1 of the dwelling unit H1 has occurred and a user of the emergency notification system 90 (a user of the monitoring server 94) needs to check on the resident P1 (by rushing to the dwelling unit H1 or by phone to check on his / her safety), if a physical abnormality has occurred in the resident P1, the alert unit 57 issues an alert notification to the emergency notification system 90. In one specific example, when the alert unit 57 receives an abnormality signal S10 (an abnormality signal S10 that should be transmitted to the monitoring server 94) from the monitoring device 92 during the caution period, the alert unit 57 issues an alert notification to the emergency notification system 90. In one specific example, when the warning unit 57 receives a signal from the monitoring server 94 notifying that an abnormality related to the living situation of the resident P1 living in the dwelling unit H1 has occurred during the caution period, the warning unit 57 sends a warning notice to the emergency notification system 90. In this case, the warning notice may include information about the degree of physical abnormality of the resident P1 at the current time (when the abnormality occurred).

[0105] The destination of the warning notification may include the monitoring server 94. The destination of the warning notification may include an information terminal (smartphone, personal computer, etc.) that can be operated by the user of the monitoring server 94.

[0106] The contents of the warning notice may include, for example, the type of physical abnormality, various pieces of warning information, and the like.

[0107] The warning information may include, for example, information that resident P1 has impaired cognitive function and may not be able to understand the situation, so care should be taken when visiting dwelling unit H1 so as not to startle him.

[0108] The warning information may include, for example, information that, because resident P1's cognitive function has declined, resident P1's family members should be contacted before and after checking with resident P1 to avoid any trouble.

[0109] The warning information may include, for example, information that resident P1's declining cognitive function may lead to problems such as wandering, and therefore that more care should be taken, such as by increasing the frequency of regular checks with resident P1.

[0110] The warning information may include, for example, information about a room in dwelling unit H1 where resident P1 is likely to be staying. If the room in dwelling unit H1 where resident P1 is likely to be staying is known in advance, there is a higher chance that a user of emergency notification system 90 (user of monitoring server 94) will be able to find resident P1 early when rushing to dwelling unit H1. Information about the room where resident P1 is likely to be staying can be obtained, for example, from detection data by infrared human sensor 912, detection data by radio wave sensor 14, etc.

[0111] The warning information may include, for example, information that the abnormality signal S10 caused by operating the operation button (emergency call button) of the emergency call device 914 may be a false alarm.

[0112] The warning notice does not have to include the warning information. The user of the emergency notification system 90 who receives the warning notice may determine matters corresponding to the contents of the warning information listed above.

[0113] By receiving the warning notice, the user of the emergency notification system 90 (the user of the monitoring server 94) can recognize that he or she needs to pay attention to any physical abnormalities in the resident P1. In addition, by receiving the warning notice, the user of the emergency notification system 90 (the user of the monitoring server 94) can recognize that he or she needs to pay attention when rushing to the dwelling unit H1 or when contacting the resident P1 by phone to check on their safety, etc.

[0114] (1.2.4) Operation An example of the operation of the monitoring system 100 will be described below with reference to the flowchart of FIG.

[0115] The acquisition unit 51 of the anomaly detection system 10 acquires detection data (ST1). The detection data may include first detection data, second detection data, and operation data.

[0116] The determination unit 52 determines whether or not there is a physical abnormality in the resident P1 (decline in cognitive function) based on the detection data (ST2). If the determination unit 52 determines that there is no physical abnormality (ST3: No), the abnormality detection system 10 operates in normal mode (ST4) and periodically sends a normal status report to the notification destination (ST5). The abnormality detection system 10 then returns to step ST1 and continues monitoring for physical abnormalities in the resident P1. The emergency notification system 90 monitors for the occurrence of abnormalities related to the living conditions of the resident P1 in the dwelling unit H1 based on the first detection data of the first sensor 91. If an abnormality related to the living conditions (disaster, intrusion of a suspicious person, etc.) occurs, the emergency notification system 90 will check with the resident P1, etc.

[0117] If the determination unit 52 determines that there is a physical abnormality (ST3: Yes), the abnormality detection system 10 transitions to an abnormality mode (ST6). In the abnormality mode, the abnormality detection system 10 acquires detected data and stores it in the memory unit 6. Also, in the abnormality mode, the abnormality detection system 10 sends a warning notice to the emergency notification system 90.

[0118] In the anomaly mode, if the emergency notification system 90 determines that no abnormality has occurred in the living situation (ST7: No), the anomaly detection system 10 monitors the situation (ST8) and periodically or ad hoc notifies the notification destination of an anomaly report (ST9).The anomaly detection system 10 also returns to step ST6 and operates in the anomaly mode, continuing to acquire and store detected data.

[0119] In the abnormality mode, if the emergency notification system 90 determines that an abnormality has occurred in the living situation (ST7: Yes), the emergency notification system 90 checks with the resident P1. The emergency notification system 90 has received a warning notice from the abnormality detection system 10. Therefore, the user of the emergency notification system 90 can check with the resident P1, taking into account that a physical abnormality has occurred in the resident P1 (ST10).

[0120] The operation of the monitoring system 100 is not limited to the flowchart of Fig. 3. For example, in the anomaly detection mode, the anomaly detection system 10 may send a warning notice to the emergency notification system 90 when the emergency notification system 90 determines that an abnormality related to the living situation has occurred (ST7: Yes). Also, for example, even if it has once determined that an abnormality has occurred (ST3: Yes), the system may return to step ST1 and re-determine whether an abnormality has occurred in the resident P1's body.

[0121] The anomaly detection system 10 of this embodiment can detect the occurrence of physical anomalies in the resident P1 living in the dwelling unit H1 in cooperation with the emergency notification system 90, which monitors for abnormalities in the living conditions of the resident P1. Furthermore, the monitoring system 100 equipped with the anomaly detection system 10 of this embodiment can check with the resident P1 taking into consideration whether or not there are any physical anomalies in the resident P1, improving convenience for the resident P1.

[0122] (1.3) Variations The above-described first embodiment is merely one of various embodiments of the present disclosure. The above-described first embodiment can be modified in various ways depending on the design, etc., as long as the object of the present disclosure can be achieved. Furthermore, functions similar to those of the anomaly detection system 10 according to the above-described first embodiment may be embodied in an anomaly detection method, a computer program, a non-transitory recording medium on which a computer program is recorded, or the like.

[0123] Specifically, one aspect of the anomaly detection method includes an acquisition step, a determination step, and a storage step. The acquisition step includes acquiring detection data detected by one or more sensors 91 from an emergency notification system 90. The emergency notification system 90 includes one or more sensors 91 that detect detection data related to the living situation of a resident P1 living in a dwelling unit H1, a monitoring device 92 that monitors for the occurrence of an abnormality related to the living situation based on the detection data detected by the one or more sensors 91, and a monitoring server 94 that is notified of the occurrence of the abnormality from the monitoring device 92. The determination step includes determining whether or not there is a physical abnormality in the resident P1 based on the detection data acquired in the acquisition step. The storage step includes storing, in a memory unit 6, the detection data detected by the one or more sensors during a period after it is determined in the determination step that a physical abnormality has occurred in the resident P1.

[0124] Below, we will list some modified examples of the above-described embodiment 1. The modified examples explained below can be applied in appropriate combinations.

[0125] The processing unit 5 of the processing device 3 in the present disclosure includes a computer system. The computer system is primarily composed of a processor and memory as hardware. The processor executes a program stored in the memory of the computer system to realize the functions of the processing unit 5 in the present disclosure. The program may be pre-stored in the memory of the computer system, provided via a telecommunications line, or provided in a non-transitory recording medium readable by the computer system, such as a memory card, optical disk, or hard disk drive. The processor of the computer system is composed of one or more electronic circuits including a semiconductor integrated circuit (IC) or a large-scale integrated circuit (LSI). The integrated circuits, such as ICs and LSIs, are referred to by different names depending on the degree of integration, and include integrated circuits called system LSIs, very large-scale integrations (VLSIs), and ultra-large-scale integrations (ULSIs). Furthermore, field-programmable gate arrays (FPGAs), which are programmable after the LSI is manufactured, or logic devices that allow the reconfiguration of internal connections or circuit partitions within the LSI, can also be used as processors. The electronic circuits may be integrated into one chip or distributed across multiple chips. The chips may be integrated into one device or distributed across multiple devices. The computer system referred to here includes a microcontroller having one or more processors and one or more memories. Therefore, the microcontroller is also composed of one or more electronic circuits including a semiconductor integrated circuit or a large-scale integrated circuit.

[0126] Furthermore, it is not essential that the multiple functions of each processing unit 5 are concentrated in one housing. The components of each processing unit 5 may be distributed across multiple housings. Conversely, the multiple functions of each processing unit 5 may be concentrated in one housing. Furthermore, at least some of the functions of each processing unit 5 may be realized by the cloud (cloud computing) or the like.

[0127] The processing unit 5 may perform various processes (e.g., determination processes) using a trained model generated by machine learning. The trained model is generated, for example, by supervised learning using a plurality of training data indicating the relationship between the detection data and the determination result of the presence or absence of a physical abnormality. For example, by inputting the detection data to the trained model, the processing unit 5 can obtain the determination result of the presence or absence of a physical abnormality as the output of the trained model.

[0128] An example of the machine learning algorithm is a neural network. However, the machine learning algorithm is not limited to a neural network and may be, for example, an XGB (eXtreme Gradient Boosting) regression, a Random Forest, a decision tree, a Logistic Regression, a Support Vector Machine (SVM), a Naive Bayes classifier, or a k-nearest neighbors method. Furthermore, the machine learning algorithm may be, for example, a Gaussian Mixture Model (GMM), or a k-means clustering method.

[0129] Furthermore, the learning method is not limited to supervised learning, but may be unsupervised learning or reinforcement learning.

[0130] Additionally, the trained model may be updated by performing additional training.

[0131] In one modified example, the physical abnormality of the resident P1, the presence or absence of which is determined by the determination unit 52, is not limited to a decline in cognitive function. The physical abnormality of the resident P1, the presence or absence of which is determined by the determination unit 52, may be, for example, a decline in the resident P1's physical function. For example, if a first condition is satisfied, the determination unit 52 may determine that the resident P1 has a skin disease that reduces the resident P1's temperature sensation on the skin. For example, if a high temperature condition continues for a long period of time, particularly in summer, among the cases where the first condition is satisfied, the determination unit 52 may determine that the resident P1 has suffered from heatstroke. For example, if a second condition is satisfied, the determination unit 52 may determine that the resident P1 is depressed (has a tendency toward depression). For example, if a third condition is satisfied, the determination unit 52 may determine that the resident P1 has a tendency toward glaucoma or cataracts. For example, if a fourth condition is satisfied, the determination unit 52 may determine that the resident P1 has a tendency toward glaucoma or cataracts. For example, if the fifth condition is satisfied, the determination unit 52 may determine that the resident P1 may have a decreased sense of hunger or excretion.

[0132] In one variation, the determination unit 52 may detect not only physical changes in the resident P1 but also the presence or absence of a physical abnormality in the resident P1 based on the detection data. For example, the determination unit 52 may determine that a physical abnormality has occurred in the pedestrian if the determination unit 52 detects that the resident P1's walking speed suddenly slows or stops. In this case, the determination unit 52 may notify the monitoring server 94, the resident P1's family, the resident P1's regular medical institution, etc., of the occurrence of a physical abnormality in the resident P1.

[0133] In one variation, the anomaly detection system 10 may determine whether a physical anomaly has occurred in multiple residents P1 living in the dwelling unit H1. In this case, the anomaly detection system 10 may determine that "an anomaly has occurred" if a physical anomaly has occurred in at least one of the multiple residents P1. The anomaly detection system 10 may distinguish between the multiple residents P1, for example, by their walking style (the gait and / or speed of human walking, etc.).

[0134] In the above-described first embodiment, the detection data is transmitted to the processing device 3 only via the second gateway device 2, not via the first gateway device 93. Examples of the detection data transmitted to the processing device 3 via the second gateway device 2 include the following first to ninth data. The first data is power data relating to the electricity usage status, obtained by the power sensor 15 (current sensor) in the distribution board D1. The second data is monitoring data on whether a window or door has been left closed, obtained by the security sensor 911 or the opening / closing sensor 11. The third data is monitoring data indicating the presence of a human body, obtained by the radio wave sensor 14. The fourth data is monitoring data indicating the presence of a human body, obtained by the infrared human presence sensor 912. The fifth data is monitoring data on the room temperature, obtained by the temperature sensor of the temperature and humidity sensors 12. The sixth data is monitoring data on the indoor humidity, obtained by the humidity sensor of the temperature and humidity sensors 12. The seventh data is data indicating on / off information of lighting fixtures as electrical devices and the operating status of lighting (on / off, lighting brightness level when on, and time information) obtained by the power sensor 15 (current sensor) in the distribution board D1. The eighth data is data indicating on / off information of air conditioners and the operating status of air conditioners (on / off, temperature level when air conditioning is on) obtained by the power sensor 15 and the temperature / humidity sensor 12 (temperature sensor) in the distribution board D1. The ninth data is data indicating information regarding operation input to the home information panel (intercom master unit) installed in the dwelling unit H1 (measurement results regarding the button pressed, the time of pressing, and the strength of finger pressure). However, the present disclosure is not limited to this, and detection data such as the first data to the ninth data may be transmitted to the processing device 3 via the first gateway device 93. In this case, the second gateway device 2 may be omitted. Note that the detection data such as the first data to the ninth data only need to be transmitted to the processing device 3, and do not necessarily need to be transmitted to the monitoring server 94.

[0135] In one modified example, the acquisition unit 51 may acquire only the second detection data and / or operation data from the second sensor 1 without acquiring the first detection data from the first sensor 91, and the determination unit 52 may determine whether or not there is a physical abnormality in the resident P1 based only on the second detection data and / or operation data. In other words, the abnormality detection system 10 may determine whether or not there is a physical abnormality in the resident P1 based on the second detection data and / or operation data, and notify the emergency notification system 90 of the determination result.

[0136] (2) Embodiment 2 An anomaly detection system 10 of embodiment 2 will be described with reference to the drawings. Embodiment 2 can be applied in appropriate combination with embodiment 1 (including modified examples). Note that in a monitoring system 100 including the anomaly detection system 10 of embodiment 2, descriptions of configurations that overlap with the monitoring system 100 of embodiment 1 will be omitted where appropriate.

[0137] As shown in FIG. 4, the anomaly detection system 10 includes a communication unit 4, a processing unit 5, and a storage unit 6.

[0138] The processing unit 5 includes an acquisition unit 51, a first determination unit 52, an accumulation processing unit 53, a progress monitoring unit 54, a report creation unit 55, a notification unit 56, and an alert unit 57. The first determination unit 52 of this embodiment has the same functions as the determination unit 52 of embodiment 1. The acquisition unit 51, accumulation processing unit 53, progress monitoring unit 54, report creation unit 55, and alert unit 57 of this embodiment have the same functions as those of embodiment 1. The notification unit 56 of this embodiment has the functions of a normal state notification unit 561 and an abnormal state notification unit 562, similar to the notification unit 56 of embodiment 1. The processing unit 5 performs acquisition processing, determination processing, accumulation processing, progress monitoring processing, report creation processing, notification processing, and alert processing using the functions of the acquisition unit 51, the first determination unit 52, accumulation processing unit 53, progress monitoring unit 54, report creation unit 55, notification unit 56, and alert unit 57.

[0139] Moreover, the processing unit 5 of this embodiment further includes a second determination unit 58, a setting unit 59, and an introduction unit 60. The second determination unit 58, the setting unit 59, and the introduction unit 60 indicate various functions (functions for performing various processes) of the processing unit 5. Moreover, in the processing unit 5 of this embodiment, the notification unit 56 further includes a risk notification unit 563.

[0140] The following describes the additional processing performed by the processing unit 5 of this embodiment.

[0141] (2.1) Second Determination Process The second determination unit 58 makes a determination regarding the lifestyle habits of the resident P1 based on the detection data acquired by the acquisition unit 51.

[0142] As described in the first embodiment, the acquisition unit 51 acquires, in addition to the first detection data, which is detection data obtained by the first sensor 91 provided in the emergency notification system 90, second detection data from the second sensor 1, which is a sensor other than the first sensor 91 and detects second detection data related to the living situation of a resident P1 living in the dwelling unit H1 (see FIG. 2 ). Then, the second determination unit 58 makes a determination regarding the living habits of the resident P1 based on at least one of the first detection data and the second detection data.

[0143] In the anomaly detection system 10 of this embodiment, the second determination unit 58 makes determinations regarding various lifestyle habits of the resident P1. The second determination unit 58 determines whether or not the resident P1 has a lifestyle-related risk based on the detection data (at least one of the first detection data and the second detection data). "There is a lifestyle-related risk" means, for example, that continuing the current lifestyle may have a negative impact on the health condition of the resident P1 in the future.

[0144] The following (first to seventh examples) illustrate methods for determining whether or not there is a risk related to the lifestyle habits of the resident P1 based on the detection data.

[0145] In the first example, the second determination unit 58 determines whether the resident P1 is physically inactive based on the amount of time the resident P1 spends outside the dwelling unit H1 in a day, which is the amount of time the resident P1 spends outside the dwelling unit H1, and the amount of movement the resident P1 makes within the dwelling unit H1. If the resident P1 leaves the dwelling unit H1 multiple times in a day, the amount of time the resident P1 spends outside the dwelling unit H1 may be the total amount of time the resident P1 spends outside the dwelling unit H1 in that day. The amount of time the resident P1 spends outside the dwelling unit H1 may be calculated based on, for example, the detection data of the radio wave sensor 14 installed at the entrance of the dwelling unit H1 (and the detection data of the radio wave sensor 14 or the infrared motion sensor 912 installed in each room within the dwelling unit H1). Specifically, the amount of time the resident P1 spends outside the dwelling unit H1 may be calculated based on the difference between the time the resident P1 spends outside the dwelling unit H1 and the time the resident P1 returns home, which are calculated based on the detection data of the radio wave sensor 14. The amount of movement the resident P1 makes within the dwelling unit H1 may be calculated based on the detection data of the radio wave sensor 14 or the infrared motion sensor 912 installed in each room within the dwelling unit H1.

[0146] For example, the second determination unit 58 compares the length of time the resident P1 has been outside with a threshold for the length of time the resident P1 has been outside. The threshold for the length of time the resident P1 has been outside is not particularly limited, but may be, for example, about one hour. The second determination unit 58 also compares the amount of movement with a threshold for the amount of movement. The threshold for the amount of movement is not particularly limited, but may be, for example, about 8,000 steps converted into the number of steps taken by the resident P1. The second determination unit 58, for example, determines the number of days (shortage days) during the determination period during which the length of time the resident P1 has been outside is shorter than the threshold for the length of time the resident P1 has been outside and the amount of movement is smaller than the threshold for the amount of movement. The determination period is not particularly limited, but may be, for example, about one month. If the proportion of the shortfall in the number of days during the determination period is equal to or greater than the determination threshold, the second determination unit 58 determines that the resident P1 has a lifestyle-related risk (has a tendency toward lack of exercise). The determination threshold is not particularly limited, but may be, for example, a proportion of about three weeks during the one-month determination period.

[0147] Lack of exercise increases the risk of developing heart disease, etc. By having the second determination unit 58 make such a determination, it is possible to reduce the risk.

[0148] In short, in the first example, the second judgment unit 58 judges that resident P1 has a lifestyle risk if the proportion of days in a judgment period of two or more days during which the length of time spent outside is shorter than the threshold for the length of time outside and the amount of movement is smaller than the threshold for the amount of movement is equal to or greater than the judgment threshold.

[0149] In the second example, the second determination unit 58 determines the amount of time the resident P1 has been out based on the length of time that the resident P1 has been out of the dwelling unit H1 during the day (the time period from sunrise to sunset). The length of time that the resident P1 has been out of the dwelling unit H1 during the day can be calculated based on, for example, the detection data of the radio wave sensor 14 installed at the entrance of the dwelling unit H1 (and the detection data of the radio wave sensor 14 or the infrared motion sensor 912 installed in each room in the dwelling unit H1).

[0150] For example, the second determination unit 58 compares the daytime outside time with a daytime outside time threshold. The daytime outside time threshold is not particularly limited, but may be, for example, about one hour. For example, the second determination unit 58 determines the number of days (shortage days) during which the daytime outside time is shorter than the daytime outside time threshold during the determination period. The determination period is not particularly limited, but may be, for example, about one month. If the proportion of shortfall days in the determination period is equal to or greater than the determination threshold, the second determination unit 58 determines that the resident P1 has a lifestyle risk (tends to have insufficient sunlight). The determination threshold is not particularly limited, but may be, for example, a proportion of about three weeks during the one-month determination period.

[0151] Insufficient exposure to sunlight can lead to an increase in blood pressure, increasing the risk of developing heart disease, stroke, etc. By having second determination unit 58 make such a determination, it is possible to reduce the risk.

[0152] In short, in the second example, the second judgment unit 58 judges that resident P1 has a lifestyle risk if the proportion of days in which the daytime outside time is shorter than the daytime outside time threshold among the number of days in the judgment period, which is two days or more, is equal to or greater than the judgment threshold.

[0153] In the third example, the second determination unit determines whether the resident P1 is physically inactive based on the length of continuous sitting time, which is the length of time the resident P1 is continuously sitting. The length of continuous sitting time can be calculated, for example, based on detection data from a radio wave sensor 14 installed in each room of the dwelling unit H1 (such as a room assigned to the resident P1 in the dwelling unit H1, the living room, etc.). Specifically, the length of continuous sitting time can be calculated based on the length of time the resident P1 maintains a seated position in a fixed position in the room, which is calculated based on the detection data from the radio wave sensor 14.

[0154] The second determination unit 58, for example, compares the length of continuous sitting time with a sitting time threshold. The second determination unit 58, for example, determines the number of days (excess days) during the determination period during which the length of continuous sitting time is longer than the sitting time threshold. The determination period is not particularly limited, but may be, for example, about one month. If the proportion of the excess days within the determination period is equal to or greater than the determination threshold, the second determination unit 58 determines that the resident P1 has a lifestyle risk (tends to exercise less or sit too long). The determination threshold is not particularly limited, but may be, for example, a proportion of about three weeks within the one-month determination period.

[0155] Lack of exercise increases the risk of developing heart disease, etc. Furthermore, sitting for long periods of time puts strain on the lower back, increasing the risk of developing heart disease, etc., and the risk of death. By having the second determination unit 58 make such a determination, it is possible to reduce the risk.

[0156] In short, in the third example, the second judgment unit 58 judges that resident P1 has a lifestyle risk if the proportion of days in a judgment period of two or more days during which the sitting duration is longer than the sitting duration threshold is equal to or greater than the judgment threshold.

[0157] In the fourth example, the second determination unit 58 determines the eating habits of the resident P1 based on the number of meals the resident P1 eats per day and the meal start times. The number of meals the resident P1 eats per day and the meal start times can be determined, for example, based on detection data from the radio wave sensor 14 installed in the living room of the dwelling unit H1 where the dining table is located. Specifically, it can be determined that the resident P1 has eaten (one meal) based on the length of time the resident P1 has been continuously seated in a chair at the dining table, which is determined based on the detection data from the radio wave sensor 14 (the resident P1 is determined to have eaten if he or she has been seated for a length of time equivalent to a meal). Then, the second determination unit 58 can determine the number of meals the resident P1 eats per day and the meal start times based on the determination result that the resident P1 has eaten. Note that whether the resident P1 has eaten may also be determined by taking into account the resident P1's movements before and after sitting down in a chair at the dining table. For example, a condition for determining that resident P1 has eaten may be that resident P1 has moved to the refrigerator (at least once) to prepare a meal, then moved to the kitchen (at least once), and then sat down in a chair at the dining table. Alternatively, a condition for determining that resident P1 has eaten may be that resident P1 has moved to the sink to put away the dishes after leaving the chair at the dining table. The movement status of resident P1 before and after sitting down in a chair at the dining table can be determined based on, for example, detection data from a radio wave sensor 14 installed in the living room. Note that second determination unit 58 may also determine that a meal has been prepared based on, for example, detection data from an open / close sensor installed on the refrigerator door, power data from a power sensor 15 that indicates the power usage status of the induction cooker, and the like.

[0158] The second determination unit 58, for example, compares the number of meals eaten per day with a threshold number of meals. The threshold number of meals is not particularly limited, but may be, for example, two or three times. The second determination unit 58, for example, determines the number of days (shortage days) during the determination period during which the number of meals eaten per day is less than the threshold number of meals. The determination period is not particularly limited, but may be, for example, about one month. If the proportion of shortfall days within the determination period is equal to or greater than the determination threshold, the second determination unit 58 determines that the resident P1 is at risk for lifestyle habits (has a tendency toward dietary deficiencies). The determination threshold is not particularly limited, but may be, for example, a proportion of about three weeks within the one-month determination period.

[0159] Instead of or in addition to comparing the number of meals eaten per day with a threshold number of meals, the second judgment unit 58 may make a judgment regarding the lifestyle habits of resident P1 based on a determination of whether resident P1 has eaten during breakfast time.

[0160] Furthermore, the second determination unit 58, for example, determines the variation in meal start times within a determination period. The determination period is not particularly limited, but may be, for example, about one month. The variation may be, for example, a variance or a standard deviation. If the determined variation is equal to or greater than a determination threshold, the second determination unit 58 determines that the resident P1 is at risk for lifestyle habits (has a tendency toward disrupted eating rhythms).

[0161] The second judgment unit 58 may make a judgment regarding resident P1's lifestyle habits (nocturnal lifestyle) based on the start times of meals taken during the dinner hour, instead of or in addition to comparing the variation in meal start times with the judgment threshold.

[0162] If the number of meals is low or the eating rhythm is disrupted, the risk of developing obesity etc. By having the second determination unit 58 make such a determination, it is possible to reduce the risk.

[0163] In short, in the fourth example, the second judgment unit 58 judges that resident P1 has a lifestyle-related risk if the proportion of days in which the number of meals is less than the threshold number among the number of days in the judgment period, which is a period of two days or more, is equal to or greater than the judgment threshold, or if the variation in meal start times within the judgment period is equal to or greater than the judgment threshold.

[0164] In the fifth example, the second determination unit 58 determines the sleeping habits of the resident P1 based on the bedtime, which is the time when the resident P1 went to bed, and the sleep duration, which is the length of time the resident P1 was asleep. The bedtime and sleep duration can be calculated based on, for example, detection data (data on the presence and movement of the resident P1) of the radio wave sensor 14 installed in the room (private room / bedroom) assigned to the resident P1.

[0165] The second determination unit 58, for example, determines the variation in bedtime and / or sleep duration within a determination period. The determination period is not particularly limited, but may be, for example, about one month. The variation may be, for example, a variance or a standard deviation. If the determined variation is equal to or greater than a determination threshold, the second determination unit 58 determines that the resident P1 has a lifestyle-related risk (possibly has poor sleep quality).

[0166] Instead of or in addition to comparing the variation in bedtime and / or sleep duration with a judgment threshold, the second judgment unit 58 may make a judgment regarding the lifestyle habits (sleeping habits) of resident P1 based on the judgment result of whether the sleep duration (e.g., average) is less than a first sleep duration threshold (e.g., 5 hours) or whether the sleep duration (e.g., average) is greater than or equal to a second sleep duration threshold (e.g., 9 hours).

[0167] For example, variations in bedtime or sleep duration lead to poor sleep quality and a higher risk of sleep disorders. Furthermore, variations in bedtime or sleep duration disrupt lifestyles and increase the risk of developing depression. Research has also shown that short (e.g., less than 5 hours) or long (e.g., more than 9 hours) sleep duration increases the risk of death. The second determination unit 58's determination of this type can reduce the risk.

[0168] In short, in the fifth example, the second judgment unit 58 judges that resident P1 has a lifestyle risk if the variation in at least one of the bedtime and sleep duration within a judgment period of two days or more is greater than or equal to the judgment threshold.

[0169] In the sixth example, the second determination unit 58 determines the resident's biological clock based on the brightness of the room assigned to the resident P1 in the dwelling unit H1 at the wake-up time, which is the time the resident P1 wakes up. The wake-up time can be determined, for example, based on detection data (data on the resident P1's presence and movement) from a radio wave sensor 14 installed in the room (private room / bedroom) assigned to the resident P1 and a timekeeping device (real time clock), etc. The brightness of the room can be determined based on detection data from an illuminance sensor 13 installed in the room, etc.

[0170] For example, the second determination unit 58 compares the brightness of the room at wake-up time with a brightness threshold. The brightness threshold is not particularly limited, but may be, for example, the brightness when sunlight is expected to be shining into the room at wake-up time. If the brightness of the room is equal to or less than the brightness threshold, the second determination unit 58 determines that the resident P1 has a lifestyle risk.

[0171] For example, if you are not exposed to enough sunlight at wake-up time, your body clock cannot be reset, which may lead to a disruption of your daily rhythm, etc. By having the second determination unit 58 make such a determination, it is possible to reduce the risk.

[0172] In short, in the sixth example, the second determination unit 58 determines that the resident P1 has a lifestyle-related risk when the brightness of the room at wake-up time is equal to or less than the brightness threshold value.

[0173] In the seventh example, the second determination unit 58 determines the living environment of the resident P1 based on the room temperature when the resident P1 is present in the room of the dwelling unit H1. The presence of a resident in the room can be determined, for example, based on the detection data of the radio wave sensor 14 installed in the room. The room temperature can be determined, for example, based on the detection data of the temperature and humidity sensor 12 installed in the room.

[0174] For example, the second determination unit 58 compares the room temperature with a temperature threshold. The temperature threshold is not particularly limited, but may be, for example, about 18°C ​​in winter. The second determination unit 58 also calculates a low-temperature time length, which is the length of time during a day during which the room temperature is lower than the temperature threshold. The second determination unit 58 then compares the calculated low-temperature time length with a low-temperature time threshold. The low-temperature time threshold is not particularly limited, but may be, for example, about three hours. The second determination unit 58 also calculates, for example, the number of days (low-temperature days) during the determination period during which the low-temperature time length is longer than the low-temperature time threshold. The determination period is not particularly limited, but may be, for example, about one month. The second determination unit 58 determines that the resident P1 has a lifestyle-related risk if the proportion of low-temperature days within the determination period is equal to or greater than the determination threshold. The determination threshold is not particularly limited, but may be, for example, a proportion of about three weeks within a one-month determination period.

[0175] Staying in a low-temperature room for a long period of time increases the risk of developing heart disease, etc. Research has shown that staying in a room with a temperature below 18°C ​​in winter, in particular, increases the risk of respiratory and cardiovascular diseases, as well as the risk of death. By having the second determination unit 58 make such a determination, it is possible to reduce the risk.

[0176] In short, in the seventh example, the second judgment unit 58 judges that resident P1 has a lifestyle-related risk if the proportion of days in a judgment period of two or more days during which the low temperature time length, which is the length of time during which the room temperature is lower than the temperature threshold, is longer than the low temperature time length threshold is equal to or greater than the judgment threshold.

[0177] The method by which the second determination unit 58 determines whether or not there is a risk in the lifestyle habits of the resident P1 is not limited to the first to seventh examples. For example, the second determination unit 58 may determine whether the resident P1 is lacking exercise based on detection data from an activity level (METs) sensor, the radio wave sensor 14, etc. In this case, the second determination unit 58 may determine that the resident P1 is lacking exercise if the resident P1 does not engage in physical activity of moderate intensity or more for 150 minutes or more per week. Alternatively, the second determination unit 58 may determine the quality of the sleep of the resident P1 based on detection data from a sleep quality sensor (such as a mat-type sleep monitor), the radio wave sensor 14, etc. In this case, the second determination unit 58 may determine that the parasympathetic nervous activity of the resident P1 is decreasing if the time spent in REM sleep is decreasing.

[0178] (2.2) Risk Notification Processing When the second determination unit 58 determines that the resident P1 has a lifestyle-related risk, the risk notification unit 563 notifies the resident P1 of the lifestyle-related risk.

[0179] The risk notification unit 563 notifies the resident P1 of the risk according to the type of lifestyle habit determined to be at risk by the second determination unit 58. For example, if the second determination unit 58 determines that the resident P1 is not getting enough exercise, the risk notification unit 563 notifies the resident P1 of the risk by issuing a report indicating that the resident P1 is not getting enough exercise.

[0180] The risk notification unit 563 may not only notify the resident of the risk but also suggest ways to reduce or avoid the risk. For example, in the case of a lack of exercise, the risk notification unit 563 may suggest a guideline for the amount of exercise required. Furthermore, for example, in the case where the room is not bright enough at the time when the resident P1 wakes up, the risk notification unit 563 may suggest the introduction of fully automatic curtains in the room, or the suggestion of inspection or repair.

[0181] The risk notification unit 563 notifies the notification recipient of risks related to the lifestyle habits of the resident P1. The notification recipient may include the resident P1 or a person related to the resident P1. For example, the risk notification unit 563 may send the notification in the form of electronic data to an information terminal (smartphone, personal computer, etc.) that can be operated by the notification recipient. The risk notification unit 563 may notify the risk by sending information to the second gateway device 2 (HEMS controller) or the home information panel (intercom master unit) and displaying it.

[0182] (2.3) Setting process The setting unit 59 sets the rooms in which the function of the second determination unit 58 is to be enabled among the multiple rooms in the dwelling unit H1. For example, multiple residents P1 live in the dwelling unit H1, and the multiple residents P1 are respectively assigned to the multiple rooms in the dwelling unit H1. The setting unit 59 sets the rooms in which the function of the second determination unit 58 is to be enabled among the rooms (private rooms, bedrooms, etc.) to which the multiple residents P1 are respectively assigned. By setting the rooms in which the function of the second determination unit 58 is to be enabled, it becomes possible to select and change the resident P1 to be judged for, for example, "sitting too much (see example 3)," "sleeping habits (see example 5)," "biological clock (see example 6)," "living environment (see example 7)," etc., from among the multiple residents P1.

[0183] (2.4) Introduction process The functions of the second determination unit 58 and the risk notification unit 563 may be provided in advance in the processing unit 5 of the processing device 3, or may be added to the processing unit 5 as needed (at the request of the resident P1).

[0184] In order to add the functions of the second determination unit 58 and the risk notification unit 563, the processing unit 5 is provided with an introduction unit 60. The introduction unit 60 downloads and installs a program that realizes the functions of the second determination unit 58 from an external device in response to, for example, an operation by the resident P1 on an operation unit (such as the operation unit of the processing device 3 or the operation buttons of the monitoring device 92).

[0185] In this way, by providing the introduction section 60, it is possible to add the function of the second determination section 58.

[0186] (2.5) Target Audience The assessment of physical abnormalities (decline in cognitive function) described in the first embodiment may primarily target elderly people. On the other hand, the assessment of lifestyle habits described in the second embodiment may target people of all ages. The setting of which assessment to perform may be appropriately changed, for example, when the anomaly detection system 10 is installed in the dwelling unit H1. For example, if the age of the resident P1 is equal to or greater than a predetermined age (e.g., 65 years old), only the assessment of physical abnormalities may be performed, or both the assessment of physical abnormalities and the assessment of lifestyle habits may be performed. For example, if the age of the resident P1 is less than a predetermined age (e.g., 65 years old), only the assessment of lifestyle habits may be performed. Of course, the assessment of physical abnormalities may also be performed even if the age of the resident P1 is less than the predetermined age (e.g., 65 years old). The age information of the resident P1 may be acquired, for example, from an external server or may be input by operating an operation unit of the second gateway device 2 or the like. The age information of the resident P1 may be obtained, for example, using a trained model that inputs detection data from the radio wave sensor 14 and outputs age. If the age of the resident P1 cannot be acquired, both a determination of physical abnormalities and a determination of lifestyle habits may be performed.

[0187] (3) Mode As described above, the anomaly detection system (10) of the first aspect includes an acquisition unit (51), a determination unit (52), and a storage processing unit (53). The acquisition unit (51) acquires detection data detected by one or more sensors (91) from an emergency notification system (90). The emergency notification system (90) includes one or more sensors (91) that detect detection data related to the living situation of a resident (P1) living in a dwelling unit (H1), a monitoring device (92) that monitors the occurrence of an abnormality related to the living situation based on the detection data detected by the one or more sensors (91), and a monitoring server (94) that is notified of the occurrence of an abnormality from the monitoring device (92). The determination unit (52) determines whether or not there is a physical abnormality in the resident (P1) based on the detection data acquired by the acquisition unit (51). The accumulation processing unit (53) accumulates in the memory unit (6) detection data detected by one or more sensors (91) during a period after the determination unit (52) determines that a physical abnormality has occurred in the resident (P1).

[0188] According to this embodiment, it is possible to detect the occurrence of any physical abnormality in the resident (P1).

[0189] In the anomaly detection system (10) of the second aspect, in the first aspect, the determination unit (52) determines that the physical anomaly of the resident (P1) is a decline in cognitive function of the resident (P1).

[0190] According to this embodiment, it is possible to detect the occurrence of a decline in cognitive function of the resident (P1).

[0191] The anomaly detection system (10) of the third aspect is the same as that of the first or second aspect, and further includes a report creation unit (55) and an anomaly notification unit (562). The report creation unit (55) creates a report on a physical anomaly of the resident (P1) based on the detection data accumulated in the memory unit (6). The anomaly notification unit (562) notifies the notification destination of the report.

[0192] According to this embodiment, it is possible to notify the person to be notified of the physical abnormality of the resident (P1), and to encourage them to take appropriate measures as necessary.

[0193] In the anomaly detection system (10) of the fourth aspect, in any one of the first to third aspects, the acquisition unit (51) further acquires power data from a power sensor (15) that detects power data related to the electricity usage status in the dwelling unit (H1). The determination unit (52) further determines whether or not there is a physical anomaly in the resident (P1) based on the power data.

[0194] According to this aspect, the determination unit (52) uses the power data to determine whether or not there is a physical abnormality in the resident (P1), thereby improving the accuracy of detecting the occurrence of a physical abnormality in the resident (P1).

[0195] In the anomaly detection system (10) of the fifth aspect, in any one of the first to fourth aspects, the acquisition unit (51) further acquires operation data indicating the manner of operation performed on an operation unit for operating electrical equipment arranged in the dwelling unit (H1). The determination unit (52) determines whether or not there is a physical anomaly in the resident (P1) based on the operation data.

[0196] According to this aspect, the judgment unit (52) uses the operation data to determine whether or not there is a physical abnormality in the resident (P1), thereby improving the accuracy of detecting the occurrence of a physical abnormality in the resident (P1).

[0197] In the anomaly detection system (10) of the sixth aspect, in the fifth aspect, the operation aspect includes at least one of the ratio of the number of times the button as an operation unit is pressed down for a longer time than a reference time to the number of times the button is pressed down, and the ratio of the number of times the button is pressed down continuously at a time interval equal to or shorter than a reference time interval to the number of times the button is pressed down.

[0198] According to this embodiment, it is possible to improve the accuracy of detecting the occurrence of a physical abnormality in the resident (P1).

[0199] The anomaly detection system (10) of a seventh aspect is any one of the first to sixth aspects, and further includes a normal state notification unit (561). The normal state notification unit (561) notifies the notification destination of a report indicating that no physical anomaly has occurred in the resident (P1) during a period in which the determination unit (52) has determined that no physical anomaly has occurred in the resident (P1).

[0200] According to this embodiment, the notification recipient can be informed that there is nothing physically wrong with the resident (P1), which can give the notification recipient a sense of security.

[0201] The anomaly detection system (10) of an eighth aspect is the anomaly detection system (10) of any one of the first to seventh aspects, further including an alert unit (57). The alert unit (57) notifies the emergency notification system (90) that a physical anomaly has occurred in the resident (P1) during a period after the determination unit (52) determines that a physical anomaly has occurred in the resident (P1).

[0202] According to this embodiment, the user of the emergency notification system (90) can recognize the need to pay attention to any physical abnormalities in the resident (P1), and can recognize the need to pay attention when rushing to the dwelling unit (H1) or contacting the resident (P1) to check on their safety by phone, etc.

[0203] In a ninth aspect of the anomaly detection system (10), in any one of the first to eighth aspects, the acquisition unit (51) acquires, in addition to first detection data that is detection data obtained by a first sensor (91) that is one or more sensors (91), second detection data from a second sensor (1) that is a sensor other than the first sensor (91) and that detects second detection data related to the living situation of a resident (P1) living in the dwelling unit (H1). In addition to the first determination unit (52) that is a determination unit (52), the anomaly detection system (10) further includes a second determination unit (58) that makes a determination regarding the living habits of the resident (P1) based on at least one of the first detection data and the second detection data.

[0204] According to this embodiment, it is possible to make a determination regarding the lifestyle habits of the resident (P1).

[0205] In the anomaly detection system (10) of the tenth aspect, in the ninth aspect, the second determination unit (58) determines whether the resident (P1) has a lack of exercise as a lifestyle habit based on the length of time outside, which is the length of time that the resident (P1) spends outside the dwelling unit (H1) in a day, and the amount of movement of the resident (P1) within the dwelling unit (H1), which are obtained from at least one of the first detection data and the second detection data. The second determination unit (58) determines that the resident (P1) has a lifestyle risk when the proportion of days in which the length of time outside is shorter than the threshold for length of time outside and the amount of movement is smaller than the threshold for amount of movement, among the number of days in a determination period of two or more days, is equal to or greater than a determination threshold.

[0206] According to this aspect, it is possible to determine the risk of lifestyle habits that may lead to heart disease and the like.

[0207] In the anomaly detection system (10) of the eleventh aspect, in the ninth or tenth aspect, the second determination unit (58) determines whether the resident (P1) has a lack of exercise as a lifestyle habit based on a sedentary duration, which is the length of time the resident (P1) has been continuously seated, obtained from at least one of the first detection data and the second detection data. The second determination unit (58) determines that the resident (P1) has a lifestyle risk when the proportion of days in which the sedentary duration is longer than the sedentary duration threshold, among the number of days in a determination period of two or more days, is equal to or greater than a determination threshold.

[0208] According to this aspect, it is possible to determine the risk of lifestyle habits that may lead to heart disease and the like.

[0209] In the anomaly detection system (10) of the twelfth aspect, in any one of the ninth to eleventh aspects, the second determination unit (58) determines the eating habits of the resident (P1) as lifestyle habits based on the number of meals eaten per day and the meal start times of the resident (P1) obtained from at least one of the first detection data and the second detection data. The second determination unit (58) determines that the resident (P1) has a lifestyle risk when the proportion of days in which the number of meals eaten is less than a threshold number among the number of days in a determination period of two or more days is equal to or greater than a determination threshold, or when the variation in meal start times within the determination period is equal to or greater than a determination threshold.

[0210] According to this aspect, it is possible to determine the risk of lifestyle habits that may lead to obesity, etc.

[0211] In a thirteenth aspect of the anomaly detection system (10), in any one of the ninth to twelfth aspects, the second determination unit (58) makes a determination regarding the sleeping habits of the resident (P1) as lifestyle habits based on the bedtime, which is the time when the resident (P1) goes to bed, and the sleep duration, which is the length of time the resident (P1) is asleep, obtained from at least one of the first detection data and the second detection data. The second determination unit (58) determines that the resident (P1) has a lifestyle risk when the variation in at least one of the bedtime and the sleep duration within a determination period of two days or more is equal to or greater than a determination threshold.

[0212] According to this aspect, it is possible to determine the risk of lifestyle habits that may lead to sleep disorders, depression, etc.

[0213] In the anomaly detection system (10) of the fourteenth aspect, in any one of the ninth to thirteenth aspects, the second determination unit (58) makes a determination related to the biological clock as a lifestyle habit of the resident (P1) based on the brightness of a room in the dwelling unit (H1) assigned to the resident (P1) at the wake-up time, which is the time the resident (P1) wakes up, obtained from at least one of the first detection data and the second detection data. The second determination unit (58) determines that the resident (P1) has a lifestyle-related risk when the brightness of the room at the wake-up time is equal to or less than a brightness threshold.

[0214] According to this aspect, it is possible to determine the risk of lifestyle habits that may lead to disruptions in daily rhythms, etc.

[0215] In a fifteenth aspect of the anomaly detection system (10), in any one of the ninth to fourteenth aspects, the second determination unit (58) makes a determination regarding the living environment as a lifestyle habit of the resident (P1) based on the room temperature when the resident (P1) is present in a room in the dwelling unit (H1), which is obtained from at least one of the first detection data and the second detection data. The second determination unit (58) determines that the resident (P1) has a lifestyle-related risk when the proportion of days during which the low-temperature time length, which is the length of time during which the room temperature is lower than the temperature threshold, is greater than the low-temperature time length threshold, among the number of days in a determination period of two or more days, is equal to or greater than a determination threshold.

[0216] According to this aspect, it is possible to determine the risk of lifestyle habits that may lead to heart disease and the like.

[0217] The anomaly detection system (10) of the 16th aspect, in any one of the 9th to 15th aspects, further includes a risk notification unit (563) that notifies the resident (P1) of a risk related to lifestyle habits when the second judgment unit (58) judges that the resident (P1) has a risk related to lifestyle habits.

[0218] According to this aspect, it is possible to notify the resident (P1) or related parties of risks related to the resident (P1)'s lifestyle habits.

[0219] The anomaly detection system (10) of the 17th aspect, in any one of the 9th to 16th aspects, further includes an introduction unit (60) that downloads and installs a program that realizes the function of the second determination unit (58) from an external device in response to an operation of the operation unit by the resident (P1).

[0220] According to this embodiment, it is possible to add the function of the second determination section (58).

[0221] An eighteenth aspect of the anomaly detection system (10) is any one of the ninth to seventeenth aspects, in which a plurality of residents (P1) reside in the dwelling unit (H1). The plurality of residents (P1) are assigned to a plurality of rooms in the dwelling unit (H1). The anomaly detection system (10) further includes a setting unit (59) that sets a room among the plurality of rooms in which the function of the second determination unit (58) is to be enabled.

[0222] According to this aspect, it is possible to select and change the resident (P1) whose lifestyle-related risk is to be assessed from among a plurality of residents (P1).

[0223] A nineteenth aspect of the anomaly detection method includes an acquisition step, a determination step, and a storage step. The acquisition step includes acquiring detection data detected by one or more sensors (91) from an emergency notification system (90). The emergency notification system (90) includes one or more sensors (91) that detect detection data related to the living situation of a resident (P1) living in a dwelling unit (H1), a monitoring device (92) that monitors the occurrence of an abnormality related to the living situation based on the detection data detected by the one or more sensors (91), and a monitoring server (94) that is notified of the occurrence of the abnormality from the monitoring device (92). The determination step includes determining whether or not there is a physical abnormality in the resident (P1) based on the detection data acquired in the acquisition step. The storage step includes storing, in a memory unit (6), the detection data detected by the one or more sensors (91) during a period after it is determined in the determination step that there is a physical abnormality in the resident (P1).

[0224] According to this embodiment, it is possible to detect the occurrence of any physical abnormality in the resident (P1).

[0225] A program according to a twentieth aspect is a program for causing one or more processors to execute the anomaly detection method according to the nineteenth aspect. [Explanation of symbols]

[0226] 10. Anomaly Detection System 1 Second sensor 15 Power Sensor 51 Acquisition Department 52 Judgment part (1st judgment part) 53 Accumulation processing section 55 Report Writing Department 561 Normal notification department 562 Emergency Notification Department 57 Alert section 58 Second judgment part 59 Setting section 60 Introduction 6 Memory section 90 Emergency Call System 91 Sensor (1st Sensor) 92 Monitoring equipment 94 Monitoring Server H1 dwelling unit P1 Resident

Claims

1. an acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of a resident living in a dwelling unit, a monitoring device that monitors the occurrence of an abnormality related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; the second determination unit determines whether the resident is physically inactive as the lifestyle habit based on a length of time that the resident is out of the dwelling unit, which is a length of time that the resident is out of the dwelling unit in a day, and an amount of movement of the resident within the dwelling unit, which are obtained from at least one of the first detection data and the second detection data; the second determination unit determines that the resident has a risk related to the lifestyle habit when a proportion of days during which the length of time spent outside is shorter than a threshold for the length of time spent outside and the amount of movement is smaller than a threshold for the amount of movement, among days in a determination period that is two or more days, is equal to or greater than a determination threshold; Anomaly detection system.

2. An acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of residents living in a dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; the second determination unit determines whether the lifestyle habit of the resident is a lack of exercise based on a sitting duration length that is a length of time that the resident is continuously sitting, the length of time being obtained from at least one of the first detection data and the second detection data; The second determination unit determines that the resident has a risk related to the lifestyle habit when a proportion of days during which the sedentary duration is longer than a sedentary duration threshold is equal to or greater than a determination threshold, among the number of days in a determination period that is two or more days. Anomaly detection system.

3. An acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of residents living in a dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; the second determination unit determines the eating habits of the resident as the lifestyle habits based on the number of meals and meal start times of the resident per day obtained from at least one of the first detection data and the second detection data; The second determination unit When the proportion of days in which the number of meals is less than the threshold number of times among the number of days in a determination period of two days or more is equal to or greater than the determination threshold, or When the variation in the meal start time within the judgment period is equal to or greater than a judgment threshold, determining that the resident is at risk for the lifestyle habit; Anomaly detection system.

4. An acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of residents living in a dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; the second determination unit determines the sleeping habits of the resident as the lifestyle habits based on a bedtime, which is a time when the resident goes to bed, and a sleeping duration, which is a length of time the resident is sleeping, obtained from at least one of the first detection data and the second detection data; The second determination unit determines that the resident has a risk related to the lifestyle habit when a variation in at least one of the bedtime and the sleep duration within a determination period of two days or more is equal to or greater than a determination threshold. Anomaly detection system.

5. An acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of residents living in a dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; the second determination unit makes a determination regarding the biological clock as the lifestyle habit of the resident based on the brightness of a room assigned to the resident in the dwelling unit at a wake-up time that is a time when the resident wakes up, the brightness being obtained from at least one of the first detection data and the second detection data; the second determination unit determines that the resident has a risk related to the lifestyle habit when the brightness of the room at the wake-up time is equal to or less than a brightness threshold. Anomaly detection system.

6. An acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of residents living in a dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; the second determination unit determines a living environment as the lifestyle of the resident based on a temperature of the room in an occupied state in which the resident is present in the room of the dwelling unit, the temperature being obtained from at least one of the first detection data and the second detection data; the second determination unit determines that the resident has a risk related to the lifestyle habit when a proportion of the number of days during which a low temperature time length, which is the length of time during which the room temperature is lower than a temperature threshold, is longer than a low temperature time length threshold, among the number of days in a determination period that is two or more days, is equal to or greater than a determination threshold; Anomaly detection system.

7. An acquisition unit that acquires the first detection data detected by the one or more first sensors from an emergency notification system that includes one or more first sensors that detect first detection data related to the living conditions of residents living in a dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination unit that determines whether or not there is a physical abnormality in the resident based on the first detection data acquired by the acquisition unit; an accumulation processing unit that accumulates in a storage unit the first detection data detected by the one or more first sensors during a period after the first determination unit determines that the physical abnormality has occurred in the resident; The acquisition unit further acquires the second detection data from a second sensor that is a sensor other than the first sensor and detects second detection data related to a living situation of the resident living in the dwelling unit, a second determination unit that determines a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; A plurality of residents live in the dwelling unit, The plurality of residents are assigned to the plurality of rooms of the dwelling unit, respectively; a setting unit for setting a room in which the function of the second determination unit is enabled among the plurality of rooms; Anomaly detection system.

8. The first determination unit determines that the physical abnormality of the resident is a decline in the resident's cognitive function. The anomaly detection system according to any one of claims 1 to 7.

9. A report creation unit that creates a report regarding the physical abnormality of the resident based on the first detection data stored in the memory unit; and an abnormality notification unit that notifies the notification destination of the report. The anomaly detection system according to any one of claims 1 to 7.

10. The acquisition unit further acquires the power data from a power sensor that detects power data related to electricity usage in the dwelling unit; the first determination unit determines whether or not there is a physical abnormality in the resident based further on the power data. The anomaly detection system according to any one of claims 1 to 7.

11. The acquisition unit further acquires operation data indicating the manner of operation performed on an operation unit for operating electrical equipment arranged in the dwelling unit, the first determination unit determines whether or not there is a physical abnormality in the resident based further on the operation data; The anomaly detection system according to any one of claims 1 to 7.

12. The mode of operation is: a ratio of the number of times the button as the operation unit is pressed for a period longer than a reference time to the number of times the button is pressed; A ratio of the number of times the button is pressed continuously at a time interval equal to or shorter than a reference time interval to the number of times the button is pressed; and at least one of The anomaly detection system according to claim 11 .

13. The system further comprises a normal time notification unit that notifies a notification recipient of a report indicating that the resident has no physical abnormality during a period in which the first determination unit has determined that the resident has no physical abnormality. The anomaly detection system according to any one of claims 1 to 7.

14. The system further comprises an alert unit that notifies the emergency reporting system that the physical abnormality has occurred in the resident during a period after the first determination unit determines that the physical abnormality has occurred in the resident. The anomaly detection system according to any one of claims 1 to 7.

15. The device further includes a risk notification unit that notifies the resident of a risk related to the lifestyle habit when the second determination unit determines that the resident has a risk related to the lifestyle habit. The anomaly detection system according to any one of claims 1 to 7.

16. The system further comprises an introduction unit that downloads and installs a program from an external device that realizes the function of the second determination unit in response to an operation of the operation unit by the resident. The anomaly detection system according to any one of claims 1 to 7.

17. An acquisition step of acquiring the first detection data detected by the one or more first sensors from an emergency notification system comprising one or more first sensors that detect first detection data related to the living conditions of residents living in the dwelling unit, a monitoring device that monitors the occurrence of abnormalities related to the living conditions based on the first detection data detected by the one or more first sensors, and a monitoring server that is notified of the occurrence of the abnormality from the monitoring device; a first determination step of determining whether or not there is a physical abnormality in the resident based on the first detection data acquired in the acquisition step; a storage processing step of storing the first detection data detected by the one or more first sensors in a storage unit during a period after it is determined in the first determination step that the physical abnormality has occurred in the resident; The acquiring step further includes acquiring the second detection data from a second sensor other than the first sensor, the second detection data being related to a living situation of the resident living in the dwelling unit; a second determination step of determining a lifestyle habit of the resident based on at least one of the first detection data and the second detection data; The second determination step includes determining whether the resident is physically inactive as a lifestyle habit based on a length of time outside the dwelling, which is the length of time that the resident spends outside the dwelling, and an amount of movement of the resident within the dwelling, which are obtained from at least one of the first detection data and the second detection data, The second determination step includes determining that the resident has a risk related to the lifestyle habit when a ratio of days during which the length of time spent outside is shorter than a threshold for the length of time spent outside and the amount of movement is smaller than a threshold for the amount of movement, among days in a determination period that is two or more days, is equal to or greater than a determination threshold. Anomaly detection methods.

18. A method for causing one or more processors to execute the anomaly detection method according to claim 17, program.

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