JP2017016185A - Method, program and determination system for determining presence or absence of room - Google Patents

Abstract

An object of the present invention is to provide a novel method that makes it possible to determine the presence / absence of a room without using an optical sensor or a surveillance camera. According to the present invention, there is provided a method for determining the presence or absence of an animal including a human being in a room, the step of measuring the carbon dioxide concentration in the room over time, and each time the carbon dioxide concentration is measured, Calculating the time variation of the carbon dioxide concentration based on the latest measured value and the immediately previous measured value, and comparing the time variation with a predetermined threshold to determine the presence or absence of a room, and The predetermined threshold values are a positive threshold value and a negative threshold value, and the step of determining the presence or absence of the room determines that the animal is in the room when the time variation exceeds the positive threshold value. And determining that the animal is not occupying when the time fluctuation falls below the negative threshold. [Selection] Figure 1

Description

  The present invention relates to a method for determining the presence / absence of a room, and more particularly to a method for determining the presence / absence of a room based on the concentration of carbon dioxide in a room.

  Conventionally, in order to determine whether or not a person is present in a room, a method using an optical sensor such as an infrared sensor or a method using a surveillance camera has been exclusively employed (for example, Patent Document 1).

  However, in the case of a method using an optical sensor or a surveillance camera, the presence of a blind spot becomes a problem. In addition, the method using a surveillance camera has a problem that many people feel psychological resistance when introducing it.

JP 2002-99974 A

  The present invention has been made in view of the above problems in the prior art, and the present invention provides a novel method that makes it possible to determine the presence or absence of a room without using an optical sensor or a surveillance camera. With the goal.

  As a result of intensive studies on a method for determining the presence or absence of an occupant without using an optical sensor or a monitoring camera, the present inventor has conceived the following configuration and has reached the present invention.

  That is, according to the present invention, there is provided a method for determining the presence or absence of an animal including a person, the step of measuring the carbon dioxide concentration in the room over time, and the latest measurement each time the carbon dioxide concentration is measured. Calculating a time variation of the carbon dioxide concentration based on the measurement value and the immediately preceding measurement value, and comparing the time variation with a predetermined threshold value to determine whether there is an occupancy, The threshold value is a positive threshold value and a negative threshold value, and the step of determining the presence or absence of the room determines that the animal is present when the time variation exceeds the positive threshold value, A determination method is provided that includes determining that the animal is not occupying when the time variation falls below the negative threshold.

  As described above, according to the present invention, a novel method is provided that makes it possible to determine the presence or absence of an occupancy without using an optical sensor or a surveillance camera.

The flowchart which shows the determination method of this embodiment. The figure which shows typically the structure of the determination system of this embodiment. The figure which shows the experimental apparatus of a present Example. Graph showing the change over time in the CO ₂ concentration. Graph showing the change over time in the time variation of the CO ₂ concentration.

  Hereinafter, the present invention will be described with reference to embodiments shown in the drawings, but the present invention is not limited to the embodiments shown in the drawings. In the drawings referred to below, the same reference numerals are used for common elements, and the description thereof is omitted as appropriate.

  The present invention provides a method for determining whether an animal including a person is present in a room. In the present invention, a room is a generally enclosed space and is a concept including all spaces in which animals including humans can stay, and is not limited to its shape or use. Moreover, the animal in this invention means the animal which breathes a lung, and contains the carbon dioxide in expiration.

When an animal performs lung respiration in a sealed space, the indoor CO ₂ concentration increases due to carbon dioxide (CO ₂ ) contained in exhaled breath. At this time, the amount of increase in the CO ₂ concentration per minute in the sealed space is given by the following formula (1). In Formula (1), V _exhaled represents the volume of exhaled, C _CO2 represents a CO ₂ concentration of the breath, n _breath represents the number per minute breathing, V _SPACE indicates the volume of the closed space.

Here, in the case of a typical adult, (V _exhaled ) = 0.5 L, (C _CO2 ) = 4%, (n _breath ) = 15, _{humans breathed in} an enclosed space The amount of increase in CO ₂ concentration per minute in this case is given by the following formula (2).

However, in an actual room, ventilation is always performed through a minute gap (or by air conditioning equipment), so that even if a person continues to breathe in the room, the CO ₂ concentration in the room continues to increase. Rather, it saturates at a certain value. On the other hand, when the CO ₂ concentration is leaving a person out of the room saturated, CO ₂ concentration in the room by the action of ventilation described above, including reduced, settles at a constant value after reduced to near baseline.

The present invention has been made paying attention to the above-described points, and is based on the temporal variation of the CO ₂ concentration that occurs when an animal including a person (hereinafter simply referred to as a person) enters or leaves the room. The presence or absence of is determined. Hereinafter, specific contents of the determination method of the present embodiment will be described based on the flowchart shown in FIG.

First, in step 101, the latest CO ₂ concentration of the room is acquired based on the sensor output of the CO ₂ concentration sensor installed in the room to be determined.

In the subsequent step 102, the time variation DC _CO2 (t ₀ ) of the CO ₂ concentration is calculated based on the following equation (3). In the following formula (3), C _CO2 (t ₀ ) and t ₀ indicate the latest CO ₂ concentration and its acquisition time, respectively, and C _CO2 (t _-1 ) and t-1 respectively Shows the acquired CO ₂ concentration and its acquisition time. In other words, (t ₀ -t ₋₁ ) in the following formula (3) corresponds to a CO ₂ concentration sampling interval (period).

In the subsequent step 103, processing for leveling the time-varying DC _CO2 (t ₀ ) calculated in step 102 is executed. In the present embodiment, the most recent of N, including a time-varying DC _CO2 (t ₀₎ (N is an integer of 2 or more) of the time variation _{(DC CO2 (t 0),} DC CO2 (t -1), DC CO2 (t _-2 )… DC _CO2 (t- _(n-1) )) is output as a time-varying DC _CO2 (t ₀ ) 'after leveling. However, in other embodiments, the leveling process may be executed by other appropriate methods.

In the next step 104, it is determined whether or not the time-varying DC _CO2 (t ₀ ) ′ after leveling exceeds a positive threshold value. The positive threshold here is a threshold for determining the presence of a person and has a positive value. In the present embodiment, an appropriate value is set in advance as the positive threshold based on the result of a simulation or preliminary experiment taking into account the space volume of the target room, the degree of ventilation, and the like.

As a result of the determination in step 104, if the time variation DC _CO2 (t ₀ ) ′ exceeds the positive threshold value (S104, Yes), the process proceeds to step 106, and at that time (CO ₂ concentration sampling time). It is determined that a person is present in the room. On the other hand, when the time variation DC _CO2 (t ₀ ) ′ does not exceed the positive threshold value (S104, No), the process proceeds to Step 105.

In step 105, it is determined whether or not the time-varying DC _CO2 (t ₀ ) ′ after leveling is below a negative threshold. The negative threshold here is a threshold for determining the absence of a person and has a negative value. In the present embodiment, similarly for the negative threshold value, an appropriate value is set in advance based on the results of simulations and preliminary experiments taking into account the space volume of the target room and the degree of ventilation.

As a result of the determination in step 105, when the time variation DC _CO2 (t ₀ ) ′ is below the negative threshold (S105, Yes), the process proceeds to step 108, and at that time (CO ₂ concentration sampling time). It is determined that no person is present in the room (ie, the absence is determined). On the other hand, when the time variation DC _CO2 (t ₀ ) ′ is not less than the negative threshold value (S105, No), the process proceeds to Step 107.

In step 107, the result of the determination made in the previous process is maintained, and the process ends. As described above, if a person continues to stay in the room, the CO ₂ concentration time fluctuation DC _CO2 (t ₀ ) ′ falls below the positive threshold as the indoor CO ₂ concentration saturates. May approach zero. Under such circumstances, the previous determination result (in-room) is maintained in step 107. Similarly, after a person leaves the room, if the indoor CO ₂ concentration decreases to near the baseline and settles to a certain value, the time variation DC _CO2 (t ₀ ) ′ of the indoor CO ₂ concentration becomes negative. May exceed zero threshold and approach zero. Under such circumstances, the previous determination (absence) is maintained at step 107.

In the present embodiment, the series of processes (steps 101 to 107) described above are repeatedly executed in synchronization with the CO ₂ concentration sampling timing. The functional means for executing each step shown in FIG. 1 can be realized by a device executable program described in C, C ++, C #, Java (registered trademark), etc. It can be stored and distributed on a device-readable recording medium such as a device, CD-ROM, MO, DVD, flexible disk, EEPROM, EPROM, or transmitted via a network.

  The determination method of the present embodiment has been described above. Subsequently, a determination system that employs the determination method of the present embodiment will be described.

FIG. 2 shows a network configuration of an “elderly person watching system” that can be referred to as one example of application development of the determination system of the present embodiment. In this system, a CO ₂ concentration sensor 14 is installed in each room of the house 10 for the elderly living alone, and each sensor 14 is configured to detect the CO ₂ concentration in the room at a predetermined sampling period. The CO ₂ concentration is transmitted to the occupancy monitoring server 20 in real time via a WAN (Wide Area Network) 40 referred to as the Internet or VPN.

  On the other hand, the occupancy status monitoring server 20 is provided with functional means for executing the steps of the determination method shown in FIG. 1 and determines in real time whether or not the elderly person 12 is in each room of the house 10. Is configured to do. Further, the occupancy status monitoring server 20 is configured to record in which room the elderly person 12 is located, the occupancy status of how the elderly person 12 moved, and the like as time series data based on the determination result. According to this system, the family 32 of the elderly person 12 who lives far away can check the occupancy status of the elderly person 12 in real time by accessing the occupancy status monitoring server 20 from the PC 30. It is possible to grasp the living state.

The “elderly person monitoring system” shown in FIG. 2 can be easily constructed simply by installing one CO ₂ concentration sensor in each room, and thus has an advantage that the introduction cost can be kept low. In principle, there is no problem of blind spots as in the conventional method using a camera or an optical sensor, so that there is an advantage that the occupancy status of the elderly person 12 can be reliably grasped. Furthermore, since privacy of elderly people is protected to some extent by not using a camera, there is an advantage that a psychological barrier at the time of introduction is low.

The system configuration shown in FIG. 2 is applied as a “pet monitoring system” that directly monitors the occupancy status of pets such as dogs and cats by resetting the threshold value related to temporal fluctuations in CO ₂ concentration. It is also possible to do. 2 illustrates the case where the functional means for executing each step of the determination method shown in FIG. 1 is mounted on one server, the functional means includes two or more information processing apparatuses on the network. Needless to say, they may be distributed in appropriate units.

  As described above, the present invention has been described with the embodiments. However, the present invention is not limited to the above-described embodiments, and other functions and effects of the present invention are within the scope of embodiments that can be considered by those skilled in the art. As long as it plays, it is included in the scope of the present invention.

  Hereinafter, the determination method of the present invention will be described more specifically using examples, but the present invention is not limited to the examples described later.

In this experiment, as shown in FIG. 3, a greenhouse 50 (width 123.5 × depth 190.5 × height 193 cm) provided with a roll-up door 52 is installed in a room, and then an adult male subject examines the greenhouse 50. The act of staying for 15 minutes and then leaving the room was repeated three times. Meanwhile, PC 56 (Lenovo G580, OS: Win8, CPU: Celeron1000M-1.8) that receives the sensor output of the CO ₂ sensor module 54 (S8: Sense Air) installed inside the greenhouse 50
The CO ₂ concentration inside the greenhouse 50 was measured over time (GHz, memory: 4 GB) (sampling period: 10 seconds). As a result of measuring the CO ₂ concentration inside the unmanned greenhouse 50 in advance, the baseline was about 500 ppm.

(Measurement result)
FIG. 4 is a graph showing the change over time of the CO ₂ concentration inside the greenhouse 10. The rectangular wave shown at the bottom of the graph indicates the actual absence / occupancy period of the subject (same in FIG. 5). As shown in FIG. 4, the subject began to increase CO ₂ concentration when the delay of about one to two minutes entering the greenhouses 50, increasing the amount of CO ₂ concentration by the subject stay for about 15 minutes was about 1000ppm . On the other hand, when the subject to discharge from vinyl house 50, but the CO ₂ concentration immediately after began to decrease rapidly, the CO ₂ concentration was never lowered again to the baseline (500 ppm).

(Evaluation of occupancy judgment method)
In this experiment, ex post occupancy determination was performed based on the data shown in FIG. 4 (change in CO ₂ concentration with time). Specifically, first, the time variation of the CO ₂ concentration was calculated based on the data shown in FIG. 4, and then the moving average (n = 8) was obtained for each value. FIG. 5A shows time-series data of time variation of CO ₂ concentration, and FIG. 5B shows the result of leveling time-series data of CO ₂ concentration time variation.

  Finally, the presence / absence of the subject in the greenhouse 50 at each sampling time was determined by comparing each value of the time-series data shown in FIG. 5B with a predetermined threshold. Table 1 below summarizes the correct answer rate / incorrect answer rate for each of the period in which the subject is absent and the period in which the subject is in the room. Note that the fractional denominator shown in the judgment result column of Table 1 below corresponds to the total number of sampling points in each period, and the numerator is the total number of sampling points indicating the relevant judgment result (absence / occupancy) in each period. Corresponding to

As shown in Table 1 above, the rate at which the subject is determined to be resident during the absence period (incorrect answer rate) is only 1%, while the rate at which the subject is determined to be resident during the period in which the subject is present (correct rate) ) Remained at 63%. However, this is considered to be due to a delay of about 1 to 2 minutes from when the subject enters the room until the CO ₂ concentration starts to increase. Therefore, it can be considered that the determination method of the present invention has sufficient practical applicability in applications in which a delay of about 1 to 2 minutes is allowed for determination of entry.

10 ... house 12 ... the elderly 14 ... CO ₂ concentration sensor 20 ... occupancy status monitoring server 30 ... PC
40 ... WAN
32 ... Family 50 ... greenhouses 52 ... door 54 ... CO ₂ concentration sensor 56 ... PC

Claims (7)

A method for determining the presence or absence of an animal including a human being,
Measuring the carbon dioxide concentration in the room over time;
Each time the carbon dioxide concentration is measured, calculating the time variation of the carbon dioxide concentration based on the latest measurement value and the previous measurement value;
Comparing the time variation with a predetermined threshold to determine the presence or absence of a room;
Including
The predetermined threshold values are a positive threshold value and a negative threshold value,
The step of determining the presence / absence of the room is:
It is determined that the animal is present when the time variation exceeds the positive threshold, and is determined not to be present when the time variation is less than the negative threshold. Including steps,
Judgment method. And leveling the calculated time variation,
The step of determining the presence / absence of an occupancy is a step of determining the presence / absence of an occupancy by comparing the leveled time fluctuation with the predetermined threshold.
The determination method according to claim 1. The leveling step includes:
The determination method according to claim 2, which is a step of obtaining a moving average of the N most recent time fluctuations (N is an integer of 2 or more) including the calculated time fluctuations.   The program for making a computer perform each step of the method as described in any one of Claims 1-3. A system for determining the presence or absence of an animal, including a human,
Means for measuring the carbon dioxide concentration in the room over time;
Means for calculating the time variation of the carbon dioxide concentration based on the latest measurement value and the previous measurement value each time the carbon dioxide concentration is measured;
Means for comparing the time variation with a predetermined threshold to determine the presence or absence of a room;
Including
The predetermined threshold values are a positive threshold value and a negative threshold value,
The means for determining the presence / absence of the room is:
It is determined that the animal is present when the time variation exceeds the positive threshold, and is determined not to be present when the time variation is less than the negative threshold. Including means,
Judgment system. And further comprising means for leveling the calculated time variation,
The means for determining the presence / absence of the occupancy includes means for determining the presence / absence of an occupancy by comparing the leveled time fluctuation with the predetermined threshold.
The determination system according to claim 5. The leveling means is:
The determination system according to claim 6, further comprising means for obtaining a moving average of the N most recent time fluctuations (N is an integer of 2 or more) including the calculated time fluctuations.