Indoor anomaly detection method, system and program

Abstract

This invention provides an indoor anomaly detection method that allows for the remote determination of a resident's physical condition while protecting the privacy of the resident. [Solution] The method includes a first step of receiving the carbon dioxide concentration detected by a concentration sensor in the room, a second step of detecting a change in the carbon dioxide concentration in the room received in the first step, a third step of receiving the sensor detection result of a human presence sensor placed at a predetermined location in the room, and a fourth step of determining the state of a person in the room based on the concentration change detected in the second step and the sensor detection result received in the third step.

Description

Technical Field

[0001] The present invention relates to an indoor abnormality detection method, its system, and a program.

Background Art

[0002] There is a system that installs a camera or the like in the living space of the elderly to confirm the survival of residents such as the elderly.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, when using a camera as described above, there is a concern about the invasion of the privacy of residents. Residents have the right to live an independent life, and being constantly monitored may violate that right. [[ID=36]] In addition, if the camera malfunctions or is hacked, there is a risk that personal information and living conditions may be leaked to a third party. Furthermore, since the elderly should have a space to move around freely, the installation of cameras may also restrict the actions of residents. From such points, there is a need for a method to ensure the safety of the elderly while protecting individual privacy rights and dignity.

[0005] The present invention has been made in view of such circumstances, and its object is to provide an indoor abnormality detection method, its system, and a program that can remotely determine the physical condition of a resident while protecting the privacy of the resident and the like.

Means for Solving the Problems

[0006] The present invention is an indoor abnormality detection method in which a computer performs the following steps: a first step of receiving the carbon dioxide concentration detected by an indoor concentration sensor; a second step of detecting a change in the indoor carbon dioxide concentration received in the first step; a third step of receiving the sensor detection result of a human presence sensor placed at a predetermined location in the room; and a fourth step of determining the state of a person in the room based on the concentration change detected in the second step and the sensor detection result received in the third step.

[0007] Preferably, the fourth step determines that an abnormality has occurred in the person if, after the detected carbon dioxide concentration has fallen to a certain standard, the sensor detection result satisfies the first condition that no person in the room is detected for a certain period of time.

[0008] Preferably, the computer performs a fifth step of generating behavioral pattern information indicating the entry and exit of a person into the room and the movement patterns within the room, based on the concentration change over a predetermined period and the sensor detection results over a predetermined period. The fourth step determines that an abnormality has occurred in the person if the first condition is met and the second condition is met, which is that it is an estimated time of day when a person is estimated to be in the room based on the behavioral pattern information.

[0009] Preferably, the fourth step determines that the first condition is met when the detected carbon dioxide concentration remains at a certain level for a predetermined period of time and the sensor detection result does not detect any people in the room for a certain period of time.

[0010] Preferably, the fifth step generates the behavioral pattern information based on the concentration change, the timing of the concentration change, the sensor detection result, and the timing of the change in the sensor detection result.

[0011] Preferably, the fifth step generates the behavioral pattern information based on the change in carbon dioxide concentration detected by a plurality of concentration sensors provided in multiple rooms within the same living space or company, the timing of the change in concentration, the change in the detection result of the sensor detection detected by a plurality of motion sensors provided in multiple rooms within the same living space or company, and the timing of the change in the detection result.

[0012] Preferably, the fourth step determines whether there is one person or multiple people in the room based on the behavior pattern, the carbon dioxide concentration detected by the concentration sensor, and the behavior pattern information, and determines that the abnormality has occurred on the condition that there is only one person in the room.

[0013] Preferably, the process includes a sixth step of receiving the carbon monoxide concentration detected by a concentration sensor in the room, and a determination of whether a fire has occurred in the room based on the carbon monoxide concentration received in the sixth step.

[0014] The present invention is an indoor abnormality detection system comprising: a first means for receiving the carbon dioxide concentration detected by an indoor concentration sensor; a second means for detecting a change in the indoor carbon dioxide concentration received by the first means; a third means for receiving the sensor detection result of a human presence sensor placed at a predetermined location in the room; and a fourth means for determining the state of a person in the room based on the concentration change detected by the second means and the sensor detection result received by the third means.

[0015] The present invention is a program that causes a computer to perform the following steps: a first step of receiving the carbon dioxide concentration detected by a concentration sensor in a room; a second step of detecting a change in the carbon dioxide concentration in the room received in the first step; a third step of receiving the sensor detection result of a human presence sensor placed at a predetermined location in the room; and a fourth step of determining the state of a person in the room based on the concentration change detected in the second step and the sensor detection result received in the third step. [Effects of the Invention]

[0016] According to the present invention, it is possible to provide an indoor abnormality detection method, a system and a program thereof that can determine the physical state of a resident remotely while protecting the privacy of the resident and the like.

Brief Description of the Drawings

[0017] [Figure 1] FIG. 1 is a system configuration diagram for explaining indoor abnormality detection according to the first embodiment of the present invention. [Figure 2] FIG. 2 is a diagram for explaining a concentration sensor 13 and a human presence sensor 15 arranged in the interior 12 of a house to be monitored. [Figure 3] FIG. 3 is a functional block diagram of the indoor abnormality detection device 11 shown in FIG. 1. [Figure 4] FIG. 4 is a graph showing the difference in carbon dioxide and the like when a person is moving. [Figure 5] FIG. 5 is a graph showing the difference in carbon dioxide and the like when a person is moving. [Figure 6] FIG. 6 is a graph showing the time change of the indoor carbon dioxide concentration and the sensor detection results. [Figure 7] FIG. 7 is a flowchart for explaining an operation example of the indoor abnormality detection device 11 according to the first embodiment of the present invention. [Figure 8] FIG. 8 is a flowchart for explaining the generation of behavior pattern data according to the second embodiment of the present invention. [Figure 9] FIG. 9 is a flowchart for explaining an operation example of the indoor abnormality detection device 11 according to the second embodiment of the present invention.

Embodiments for Carrying Out the Invention

[0018] Hereinafter, an indoor abnormality detection method according to an embodiment of the present invention will be described. FIG. 1 is a system configuration diagram for explaining indoor abnormality detection according to an embodiment of the present invention. As shown in Figure 1, in this embodiment, concentration sensors 13 (13_1 to 13_4, etc.) are placed in living spaces or indoor spaces 12 (12_1 to 12_4, etc.) of a company. Human motion sensors 15 (15_1 to 15_3, etc.) are installed in the room 12. The motion sensor 15 has, for example, a detection angle of 110 degrees and a detection distance of approximately 5 meters. The motion sensor 15 is placed along the paths in which people move within a room.

[0019] The indoor abnormality detection device 11 receives the carbon dioxide concentration detected by the concentration sensor 13, receives the sensor detection result from the human presence sensor 15, processes and determines the abnormal state of a person in the room (described later), and sends a message to the relevant personnel terminal device 21 as necessary.

[0020] Figure 2 is a diagram illustrating a concentration sensor 13 placed inside the house 12 that is being monitored. The concentration sensor 13 and the motion sensor 15 are installed in a predetermined room 12 out of several rooms 12 in a house or the like.

[0021] Figure 3 is a functional block diagram of the indoor abnormality detection device 11 shown in Figure 1. As shown in Figure 2, the indoor abnormality detection device 11 includes, for example, an operation unit 53, a communication unit 55, a memory 59, and a processing unit 61.

[0022] The operation unit 53 is an operating means such as a touch panel, keyboard, or mouse. The communication unit 55 communicates with the concentration sensor 13 and the personnel terminal device 21. The input section 57 is a terminal or similar device for inputting data from an external source. Memory 59 stores the program that the processing unit 61 will execute. The processing unit 61 executes the program PRG stored in the memory 59 to perform the processing of the indoor abnormality detection device 11 as defined in this embodiment.

[0023] The indoor abnormality detection device 11 receives carbon dioxide concentration data from the concentration sensor 13 in the living space, which indicates the carbon dioxide concentration detected by the concentration sensor 13. The indoor anomaly detection device 11 detects the amount of change in carbon dioxide concentration per unit time, as indicated by the received carbon dioxide concentration data. For example, the indoor anomaly detection device 11 detects the amount of change as shown in Figures 4 and 5. The amount of change may also be expressed as a percentage change. By using the amount of change in this way, changes in the condition of residents can be identified with high accuracy.

[0024] The indoor anomaly detection device 11 receives the human presence detection result detected by the human presence sensor 15 in the living space. Figure 6 is a diagram illustrating the waveform of the human presence detection result.

[0025] The indoor anomaly detection device 11 determines whether or not there is a person inside the living space based on the detected change and the human presence detection result.

[0026] The indoor anomaly detection device 11 determines whether, in any of the indoors 12_1 to 12_4, the first condition is met, which is that after the carbon dioxide concentration of any of the concentration sensors 13_1 to 13_4 changes from a survival concentration to a non-survival concentration, the sensor detection results of the human presence sensors 15_1 to 15_3 do not detect a person for a certain period of time. The indoor abnormality detection device 11 determines that an abnormality has occurred to a person in the room when the first condition is met. Here, the survival concentration is defined based on the results of pre-detecting the carbon dioxide concentration in indoor environments 12_1 to 12_4 when a person is alive, over a predetermined period. Furthermore, the non-survival concentration is a concentration determined based on the results of pre-detecting the carbon dioxide concentration in the indoor areas 12_1 to 12_4 when no people are present for a predetermined period.

[0027] The indoor anomaly detection device 11 determines whether there is one person or multiple people in the living area based on the identified behavioral patterns and carbon dioxide concentration, and determines that an anomaly has occurred if there is only one person in the living space.

[0028] Figures 4 and 5 show the difference (change only) in carbon dioxide levels when a person is moving. When the line on the graph is moving rapidly, it indicates that a person is moving. This condition can also be assessed by monitoring carbon dioxide concentration. Based on carbon dioxide concentration and its changes, it is possible to understand the behavior of residents and the indoor air quality.

[0029] In Figure 6, (A) shows the carbon dioxide concentration, and (B) shows the time course of the sensor detection results. The horizontal axis represents time, and the vertical axis represents the level. As shown in Figure 6(B), the sensor detection result fluctuates significantly depending on the amount of time a person is within the detection range of the motion sensor 15.

[0030] Figure 7 is a flowchart illustrating an example of operation of the indoor abnormality detection device 11 according to the first embodiment of the present invention. Let's explain each step.

[0031] Step ST11: The indoor abnormality detection device 11 receives carbon dioxide concentration data from concentration sensors 13_1 to 13_4 in the living space, indicating the carbon dioxide concentration detected by the concentration sensors 13_1 to 13_4, and stores it in the memory 59.

[0032] Step ST12: The indoor anomaly detection device 11 detects the amount of change per unit time in the carbon dioxide concentration data received in step ST11 and stores it in the memory 59. For example, the indoor anomaly detection device 11 detects the amount of change as shown in Figures 4 and 5.

[0033] Step ST13: The indoor abnormality detection device 11 receives the sensor detection result detected by the human motion sensor 15 in the living space.

[0034] Step ST14: The indoor anomaly detection device 11 determines whether or not there are people in the living space based on at least one of the carbon dioxide concentration or its change and the sensor detection results. This determination may be performed for each of the rooms 12_1 to 12_4. This determination may also be performed using a learning function. If the indoor anomaly detection device 11 determines that a person is present, it proceeds to step ST15.

[0035] Step ST15: The indoor abnormality detection device 11 determines whether the first condition, which indicates an abnormality in a person in the room, is met, based on the concentration or change in carbon dioxide concentration received from concentration sensors 13_1 to 13_4, and the sensor detection results received from human presence sensors 15_1 to 15_3. Specifically, the indoor anomaly detection device 11 determines that the first condition is met when the detected carbon dioxide concentration falls to a certain standard and the sensor detection result does not detect a person in the room for a certain period of time. The above "detected carbon dioxide concentration falls to a certain standard" is determined based on the fact that the carbon dioxide concentration changes from a predetermined survival concentration to a non-survival concentration for a person within a certain period of time.

[0036] In this case, when an abnormal situation occurs involving a person, the determination is made based on how the indoor carbon dioxide concentration changes over time and whether it has changed at a predetermined rate. The indoor anomaly detection device 11 may determine that the first condition is met if it detects that the detected carbon dioxide concentration has fallen to a certain standard for a predetermined period of time and the sensor detection result does not detect any people in the room for a predetermined period of time. The predetermined period and the predetermined period are set in advance based on past measured values. Alternatively, they may be updated based on measured values ​​for a certain period of time. Such updates may be performed using a learning function.

[0037] Step ST16: The indoor abnormality detection device 11 notifies the resident's related party's terminal device 21 that an abnormality has occurred.

[0038] As explained above, the indoor abnormality detection device 11 allows for the installation of a concentration sensor 13 and a human presence sensor 15 in the room 12 without installing a camera. The concentration of carbon dioxide detected by the concentration sensor 13 and the sensor detection results detected by the human presence sensor 15 are used to determine the condition of the occupants in the room 12. Therefore, it is possible to protect the privacy of residents.

[0039] <Second Embodiment>

[0040] In this embodiment, in addition to the first condition in the first embodiment described above, an abnormality is determined to have occurred when a second condition is met, which is the estimated time of day when it is estimated that there are people inside the room based on the residents' behavioral pattern information. This improves the accuracy of the judgment.

[0041] Figure 8 is a flowchart illustrating the generation of behavioral pattern data. Let's explain each step. Step ST21: The indoor anomaly detection device 11 reads out the amount of change in carbon dioxide over a certain period (for example, 1 week to 1 month) stored in the memory 59 in step ST12 shown in Figure 7.

[0042] Step ST22: In step ST13, the indoor abnormality detection device 11 reads the sensor detection results for the above-mentioned period stored in the memory 59.

[0043] Step ST23: The communication terminal device 11 generates information on the resident's behavioral pattern based on the concentration changes read in steps ST21 and ST22, the timing of those concentration changes, the sensor detection results, and the timing of the changes in the sensor detection results. This generation may be performed using a learning function. If concentration sensors 13 and motion sensors 15 are placed in multiple rooms, a pattern is identified for each room, and overall behavioral pattern information is generated based on that. This behavioral pattern information identifies the time periods when the resident (person) is in rooms 12_1 to 12_4, the time periods when they are not in those rooms, and their movement patterns between rooms. This allows for the identification of estimated time periods when the resident is presumed to be in the living space. These estimated time periods are, for example, the time periods when the resident is in the living space or specific rooms 12_1 to 12_4 with a predetermined probability (e.g., 90%).

[0044] Figure 9 is a flowchart illustrating an example of operation of the indoor abnormality detection device 11 according to the second embodiment of the present invention. Let's explain each step.

[0045] Steps ST11, ST12, ST15, and ST16 are the same as the steps of the first embodiment described with reference to Figure 7.

[0046] Step ST33 will be explained below. Step ST33 is as follows: The indoor anomaly detection device 11 proceeds to step ST15 if it satisfies the second condition, which is that it is an estimated time of day when a person is estimated to be in the room based on the behavioral pattern information generated in step ST23 described above.

[0047] According to the second embodiment, by pre-generating information on residents' behavioral patterns and using it to notify abnormality messages, notifications can be made based on more accurate situational judgments.

[0048] The present invention is not limited to the embodiments described above. In other words, those skilled in the art may make various modifications, combinations, subcombinations, and substitutions with respect to the components of the embodiments described above, within the technical scope of the present invention or its equivalents.

[0049] In addition to the functions of the first and second embodiments described above, if, based on the carbon dioxide concentration, a person is detected in the room, but the sensor does not detect a person during the time when the person should have started their activity based on their behavioral pattern information, a low-priority warning may be sent to the relevant parties.

[0050] Although the above-described embodiment illustrates a living space, the present invention may also be applied to other corporate workspaces, hospital wards, facilities, etc.

[0051] Furthermore, the temperature and humidity of room 12 are affected by whether or not there are people inside. It can also determine whether or not the occupant intentionally turned on the air conditioning, thus serving as a life monitoring tool. Furthermore, humidity increases as the number of people increases, so there are seasonal changes, and by detecting these, we can understand the conditions of the room. The indoor anomaly detection device 11 can ultimately utilize the above information comprehensively, digitize it individually, and detect whether someone is home or absent, and read behavioral patterns.

[0052] For example, the typical behavioral patterns of an elderly person living alone in an apartment are limited to the bedroom, living room, or going out (excluding the toilet and bath). By installing concentration sensors 13 in the living room and bedroom, their well-being and lifestyle patterns can be monitored without their privacy being exposed by cameras.

[0053] Furthermore, the indoor abnormality detection device 11 may receive the carbon monoxide concentration detected by the indoor concentration sensor and determine whether a fire has occurred in the room based on the carbon monoxide concentration. Furthermore, it provides safety features against carbon monoxide poisoning caused by forgetting to turn off the stove or by stoves in cold regions. In the event of a fire, significant changes in CO, CO2, and temperature occur very quickly. [Industrial applicability]

[0054] The present invention is applicable to indoor anomaly detection systems. [Explanation of Symbols]

[0055] 11…Specification Verification System 12…Indoor 13…Carbon dioxide concentration sensor 15…Motion sensor 21…Related personnel terminal device

Claims

1. The first step is to receive the carbon dioxide concentration detected by the indoor concentration sensor, A second step involves detecting the change in the carbon dioxide concentration in the room received in the first step, A third step involves receiving the sensor detection result of a human presence sensor placed at a predetermined location within the room, A fourth step in which the state of the person in the room is determined based on the concentration change detected in the second step and the sensor detection result received in the third step. A computer-based method for detecting anomalies in an indoor environment.

2. The fourth step is to determine that an abnormality has occurred in the person if, after the detected carbon dioxide concentration has fallen to a certain standard, the sensor detection result satisfies the first condition that no person is detected in the room for a certain period of time. The indoor abnormality detection method according to claim 1.

3. A fifth step in which behavioral pattern information indicating the entry and exit of people into the room and their movement patterns within the room is generated based on the concentration change over a predetermined period and the sensor detection results over a predetermined period. The computer executes the following: The fourth step determines that an abnormality has occurred in the person if the first condition is met and the second condition is met, which is that it is an estimated time of day when a person is estimated to be in the room based on the behavioral pattern information. The indoor abnormality detection method according to claim 2.

4. The fourth step involves detecting that the detected carbon dioxide concentration has fallen to a certain standard for a predetermined period of time, and determining that the first condition has been met if the sensor detection result does not detect any people in the room for a predetermined period of time. The indoor abnormality detection method according to claim 3.

5. The fifth step generates the behavioral pattern information based on the concentration change, the timing of the concentration change, the sensor detection result, and the timing of the change in the sensor detection result. The indoor abnormality detection method according to claim 4.

6. The fifth step is, The carbon dioxide concentration change detected by multiple concentration sensors installed in multiple rooms within the same living space or company, and the timing of the concentration change. The changes in the detection results of the multiple motion sensors, each installed in the same living space or multiple rooms within a company, and the timing of such changes in the detection results, Based on this, the aforementioned behavioral pattern information is generated. The indoor abnormality detection method according to claim 5.

7. The 11th step is, Based on the aforementioned behavioral pattern, the carbon dioxide concentration detected by the concentration sensor, and the behavioral pattern information, it is determined whether there is one person or multiple people in the room, and if there is only one person in the room, it is determined that the abnormality has occurred. The indoor abnormality detection method according to claim 6.

8. A sixth step involves receiving the carbon monoxide concentration detected by the indoor concentration sensor, Based on the carbon monoxide concentration received in the sixth step, it is determined whether a fire has occurred in the room. The indoor abnormality detection method according to claim 7.

9. A first means for receiving the carbon dioxide concentration detected by an indoor concentration sensor, A second means for detecting changes in the concentration of carbon dioxide in the room received by the first means, A third means for receiving the sensor detection result of a human presence sensor placed at a predetermined location in the room, A fourth means for determining the state of a person in the room based on the concentration change detected by the second means and the sensor detection result received by the third means. An indoor anomaly detection system having the following features.

10. The first step is to receive the carbon dioxide concentration detected by the indoor concentration sensor, A second step involves detecting the change in the carbon dioxide concentration in the room received in the first step, A third step involves receiving the sensor detection result of a human presence sensor placed at a predetermined location within the room, A fourth step in which the state of the person in the room is determined based on the concentration change detected in the second step and the sensor detection result received in the third step. A program that causes a computer to execute something.

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