Measurement system, measurement method, and program

Abstract

To provide a measurement system capable of easily detecting people entering and exiting a space.SOLUTION: A measurement system 1 includes a temperature acquisition unit 10, a storage unit 20, a difference calculation unit 30, a number-of-people estimation unit 40, a movement estimation unit 50, and a movement detection unit 60. The temperature acquisition unit 10 repeatedly acquires temperature distribution data 21 representing the temperature corresponding to multiple detection points arranged in a matrix in areas where people enter and exit the space. The storage unit 20 stores multiple pieces of temperature distribution data 21. The difference calculation unit 30 repeats an operation to generate temperature differential data 22 from the multiple pieces of temperature distribution data 21. The number of people estimation unit 40 repeats an operation to estimate the position and the number of people from the temperature differential data 22. The movement estimation unit 50 estimates the movement of people based on time series changes in position and the number of people. The movement detection unit 60 detects the number of people entering and exiting the space based on the location and number of people and their movements.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a measurement system, a measurement method, and a program, and more particularly to a measurement system, a measurement method, and a program for measuring people entering and exiting a space. [Background technology]

[0002] Patent Document 1 discloses a technology for detecting people in a space using temperature. The technology disclosed in Patent Document 1 detects people in a space based on the detected temperatures of each of a plurality of matrix-shaped detection grids. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-124833 Summary of the Invention [Problem to be solved by the invention]

[0004] However, with the technology disclosed in Patent Document 1, depending on the shape of the space, the number of infrared sensors for detecting the number of people in the space may become large.

[0005] The present disclosure aims to provide a measurement system, a measurement method, and a program that can easily detect people entering and exiting a space. [Means for solving the problem]

[0006] A measurement system according to one aspect of the present disclosure measures people entering and exiting a space. The measurement system includes a temperature acquisition unit, a memory unit, a difference calculation unit, a number of people estimation unit, a movement estimation unit, and a movement detection unit. The temperature acquisition unit repeatedly acquires temperature distribution data indicating temperatures corresponding to a plurality of detection points arranged in a matrix in an area where people enter and exit the space. The memory unit stores a plurality of the temperature distribution data. The difference calculation unit repeatedly generates temperature difference data from the plurality of temperature distribution data. The number of people estimation unit repeatedly estimates the positions and number of people from the temperature difference data. The movement estimation unit estimates the movement of people based on time-series changes in the positions and number of people. The movement detection unit detects the number of people entering and exiting the space based on the positions and number of people and the movement of people.

[0007] A measurement method according to one aspect of the present disclosure measures people entering and exiting a space. The measurement method includes a temperature acquisition step, a storage step, a difference calculation step, a number of people estimation step, a movement estimation step, and a movement detection step. The temperature acquisition step repeatedly acquires temperature distribution data indicating temperatures corresponding to a plurality of detection points arranged in a matrix in an area where people enter and exit the space. The storage step stores a plurality of pieces of the temperature distribution data. The difference calculation step repeatedly generates temperature difference data from the plurality of temperature distribution data. The number of people estimation step repeatedly estimates the positions and number of people from the temperature difference data. The movement estimation step estimates the movement of people based on time-series changes in the positions and number of people. The movement detection step detects the number of people entering and exiting the space based on the positions and number of people and the movement of people.

[0008] A program according to one aspect of the present disclosure causes one or more processors to execute the measurement method. [Effects of the Invention]

[0009] According to a measurement system, a measurement method, and a program according to one aspect of the present disclosure, it is possible to easily detect people entering and exiting a space. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing the configuration of a measurement system according to the first embodiment. [Figure 2] FIG. 2 is a schematic diagram showing a space to be measured by the measurement system. [Figure 3] FIG. 3 is a schematic diagram showing an outline of temperature distribution measurement in the measurement system. [Figure 4] FIG. 4 is a flowchart showing the operation of the measurement system. [Figure 5] Fig. 5A is a schematic diagram showing the position of a person as they pass through a doorway of a space. Fig. 5B is a schematic diagram showing the position of the person at a later time than Fig. 5A. Fig. 5C is a schematic diagram showing the position of the person at a later time than Fig. 5B. Fig. 5D is a schematic diagram showing the position of the person at a later time than Fig. 5C. [Figure 6] Fig. 6A is a schematic diagram showing the positions of two people as they pass through a doorway of a space. Fig. 6B is a schematic diagram showing the positions of the people at a later time than Fig. 6A. Fig. 6C is a schematic diagram showing the positions of the people at a later time than Fig. 6B. Fig. 6D is a schematic diagram showing the positions of the people at a later time than Fig. 6C. [Figure 7] Fig. 7A is a schematic diagram showing the position of a person as they pass through a doorway of a space. Fig. 7B is a schematic diagram showing the position of the person at a later time than Fig. 7A. Fig. 7C is a schematic diagram showing the position of the person at a later time than Fig. 7B. Fig. 7D is a schematic diagram showing the position of the person at a later time than Fig. 7C. [Figure 8] Fig. 8A is a schematic diagram showing the positions of two people as they pass through a doorway of a space. Fig. 8B is a schematic diagram showing the positions of the people at a later time than Fig. 8A. Fig. 8C is a schematic diagram showing the positions of the people at a later time than Fig. 8B. Fig. 8D is a schematic diagram showing the positions of the people at a later time than Fig. 8C. [Figure 9]Fig. 9A is a schematic diagram showing the position of a person as they pass through a doorway of a space, and Fig. 9B is a schematic diagram showing the position of the person at a later time than in Fig. 9A. [Figure 10] Fig. 10A is a schematic diagram showing the positions of two people as they pass through a doorway of a space, and Fig. 10B is a schematic diagram showing the positions of the people at a later time than in Fig. 10A. [Figure 11] FIG. 11 is a perspective view showing the relationship between a temperature sensor installed in a space and a plurality of detection points. [Figure 12] 12A and 12B are schematic diagrams showing time-series changes in the position of a person when passing through a doorway of a space. [Figure 13] 13A and 13B are schematic diagrams showing time-series changes in the position of a person when passing through a doorway of a space. DETAILED DESCRIPTION OF THE INVENTION

[0011] Measurement systems, measurement methods, and programs according to embodiments will be described in detail below with reference to the drawings. However, the figures described in the following embodiments are schematic diagrams, and the ratios of the sizes and thicknesses of the components do not necessarily reflect the actual dimensional ratios. Note that the configurations described in the following embodiments are merely examples of the present disclosure. The present disclosure is not limited to the following embodiments, and various modifications are possible depending on the design, etc., as long as the effects of the present disclosure can be achieved.

[0012] (Embodiment 1) (1) Overall structure The measurement system 1 according to the first embodiment measures people entering and exiting a space AR1 (see FIG. 2) by detecting the movement of people in an area AR2 (see FIG. 2) where people enter and exit the space AR1. The space AR1 is a space for which people entering and exiting are to be measured, and may be, for example, a part of a building. The space AR1 may be, for example, a single room in a building, multiple consecutive rooms in a building, a floor in a building, an open-air space, a rooftop, or an entire building. The space AR1 may also be part of an open space, such as a park or an outdoor stage.

[0013] The measurement system 1 is connected to one or more temperature sensors 2 (one in FIG. 2). As shown in FIG. 2, the one or more temperature sensors 2 are installed in a one-to-one correspondence in an area AR2 where people enter and exit the space AR1. The area AR2 is a space through which people pass to enter and exit the space AR1. The area AR2 includes a boundary B1. The boundary B1 separates the space AR1 from the space AR3. The boundary B1 is, for example, a door, but it may also be a gate that is always open without a door, or a virtual boundary surface that has no physical entity. More specifically, the area AR2 includes the boundary B1, a part of the space AR1 adjacent to the boundary B1, and a part of the space AR3.

[0014] It should be noted that there may be multiple areas AR2 for one space AR1. When multiple areas AR2 exist in one space AR1, at least one of the multiple areas AR2 may be one-way. Specifically, at least one of the multiple areas AR2 may be a one-way entrance through which people can enter the space AR1 but cannot exit, or a one-way exit through which people can exit the space AR1 but cannot enter.

[0015] Each of the one or more temperature sensors 2 measures the temperature distribution in the corresponding area AR2. The temperature sensors 2 are installed, for example, on the ceiling surface above the area AR2. As shown in FIG. 3, the temperature sensors 2 detect the temperature of each of a plurality of detection points G1 arranged in a matrix (64 points in FIG. 3, 8 rows and 8 columns). Each of the plurality of detection points G1 corresponds to an area within the area AR2. For each of the plurality of detection points G1, the temperature sensor 2 outputs, for example, the average temperature of the area within the corresponding area AR2 as the temperature of the detection point G1.

[0016] (2) Measurement system configuration As shown in FIG. 1, the measurement system 1 according to the first embodiment includes a temperature acquisition unit 10, a memory unit 20, a difference calculation unit 30, a number of people estimation unit 40, a movement estimation unit 50, and a movement detection unit 60.

[0017] The temperature acquisition unit 10 acquires temperature distribution data 21 of the area AR2 from each of the one or more temperature sensors 2. More specifically, the temperature acquisition unit 10 periodically acquires the temperature distribution data 21 of the area AR2 from each of the one or more temperature sensors 2. The temperature acquisition unit 10 stores the acquired temperature distribution data 21 in the storage unit 20 and outputs it to the difference calculation unit 30. Note that the temperature acquisition unit 10 may calculate a moving average of the temperature for each of the multiple detection points G1 from the multiple temperature distribution data acquired from the temperature sensors 2, and map the moving average of the temperature to the multiple detection points G1 to create the temperature distribution data 21. This makes it possible to remove noise from the measurement values of the temperature sensors 2.

[0018] The storage unit 20 is a recording medium that stores a plurality of pieces of temperature distribution data 21. The storage unit 20 also stores a plurality of pieces of temperature difference data 22 and person position data 23, which will be described later.

[0019] The difference calculation unit 30 generates temperature difference data 22 from the plurality of temperature distribution data 21 corresponding to one area AR2. More specifically, when the temperature acquisition unit 10 outputs the temperature distribution data 21, the difference calculation unit 30 reads the temperature distribution data 21 immediately before the received temperature distribution data 21 from the storage unit 20. For each of the plurality of detection points G1 in each area AR2, the difference calculation unit 30 calculates the temperature difference between the latest temperature distribution data 21 output by the temperature acquisition unit 10 and the immediately previous temperature distribution data 21 read from the storage unit 20, maps the temperature difference data 22 to the plurality of detection points G1, and generates temperature difference data 22. The difference calculation unit 30 stores the generated temperature difference data 22 in the storage unit 20 and also outputs it to the number of people estimation unit 40 and the movement estimation unit 50. For example, the difference calculation unit 30 periodically generates the temperature difference data 22 in synchronization with the operation of the temperature acquisition unit 10 outputting the temperature distribution data 21.

[0020] The number of people estimation unit 40 estimates the positions and number of people in the area AR2 based on the temperature difference data 22 corresponding to one area AR2. For example, the number of people estimation unit 40 estimates that a heat source indicated in the temperature difference data 22 as an area with a larger temperature difference than the surrounding area corresponds to one or more people. Furthermore, the number of people estimation unit 40 estimates the number of people based on the temperature difference between the heat source area and the surrounding area and its area in the temperature difference data 22. If the temperature difference data 22 does not include a heat source, the number of people estimation unit 40 stores person position data 23 indicating that no people are present in the area AR2 in the memory unit 20. Furthermore, if the temperature difference data 22 includes one or more heat sources, the number of people estimation unit 40 stores the positions and number of people corresponding to each heat source as person position data 23 in the memory unit 20. Here, the person positions are information identifying the detection points G1, such as coordinates when the temperature distribution data 21 is treated as a two-dimensional image. Furthermore, the number-of-people estimation unit 40 outputs the person position data 23 stored in the storage unit 20 to the movement estimation unit 50.

[0021] The movement estimation unit 50 estimates the direction of movement of people based on time-series changes in the positions and number of people in one area AR2. When the number of people estimation unit 40 outputs person position data 23, the movement estimation unit 50 reads from the memory unit 20 the person position data 23 immediately before the person position data 23 output by the number of people estimation unit 40. The movement estimation unit 50 compares the latest person position data 23 output by the number of people estimation unit 40 with the immediately previous person position data 23 read from the memory unit 20 to detect the movement of people. If the position of a person included in the latest person position data 23 and the position of a person included in the immediately previous person position data 23 are the same or close to each other, the movement estimation unit 50 estimates that they are the same person and that the movement is that of that person. If the movement of a person whose movement has been detected is present, the movement estimation unit 50 adds a person correspondence to the person position data 23.

[0022] The movement detection unit 60 detects the number of people entering and exiting the space AR1 based on the person position data 23 and calculates the number of people in the space AR1. The movement detection unit 60 detects whether people are coming and going between the space AR1 and the space AR3 based on the person position data 23. For example, the movement detection unit 60 sets a detection area D1 between one or more detection points G1 corresponding to the space AR1 and one or more detection points G1 corresponding to the space AR3 among the multiple detection points G1. Then, for example, when a person's position moves from the detection point G1 corresponding to the space AR3 across the detection area D1 to the detection point G1 corresponding to the space AR1, the movement detection unit 60 detects that the person has entered the space AR1. Here, the detection area D1 does not necessarily need to coincide with the boundary B1. As shown in FIG. 3, the boundary B1 and the detection area D1 do not necessarily need to correspond to each other. Furthermore, for example, when a person's position moves from detection point G1 corresponding to space AR1 to detection point G1 corresponding to space AR3 across detection area D1, the movement detection unit 60 detects that the person has left space AR1. The movement detection unit 60 adds or subtracts the number of people who have entered and exited space AR1 from the number of people in space AR1.

[0023] Each of the temperature acquisition unit 10, difference calculation unit 30, number of people estimation unit 40, movement estimation unit 50, and movement detection unit 60 is, for example, a computer having a processor. More specifically, the difference calculation unit 30 is configured, for example, by a computer system having a CPU (Central Processing Unit) and memory. The computer system realizes the functions of the difference calculation unit 30 by having the CPU execute a program stored in the memory. The program may be pre-recorded in the memory of the computer system, may be provided by being recorded on a recording medium such as a memory card, or may be provided via a telecommunications line such as the Internet. Furthermore, two or more of the temperature acquisition unit 10, difference calculation unit 30, number of people estimation unit 40, movement estimation unit 50, and movement detection unit 60 may be configured by a single computer system.

[0024] (3) Operation (3.1) Overview of operation FIG. 4 is a flowchart showing the operation of the measurement system 1 according to the first embodiment.

[0025] The temperature acquisition unit 10 of the measurement system 1 acquires temperature distribution data 21 (step S1). The temperature acquisition unit 10 acquires the temperature distribution data 21 from each of the one or more temperature sensors 2, and outputs the temperature distribution data 21 to the storage unit 20 and the difference calculation unit 30.

[0026] Next, the difference calculation unit 30 of the measurement system 1 calculates the temperature difference and generates temperature difference data 22 (step S2). The difference calculation unit 30 reads out the temperature distribution data 21 immediately before the latest one from the storage unit 20. The difference calculation unit 30 calculates the temperature difference for each of the multiple detection points G1 using the temperature distribution data 21 output by the temperature acquisition unit 10 in step S1 and the temperature distribution data 21 read out from the storage unit 20, and generates matrix-like temperature difference data 22. The difference calculation unit 30 stores the temperature difference data 22 in the storage unit 20 and outputs it to the number of people estimation unit 40.

[0027] Next, the number of people estimation unit 40 of the measurement system 1 detects the positions and number of people based on the temperature difference data 22 (step S3). The number of people estimation unit 40 identifies detection points G1 corresponding to people based on the temperature difference data 22 and detects the positions and number of people. The number of people estimation unit 40, for example, extracts detection points G1 where the temperature difference value is equal to or greater than a threshold, and detects each of the extracted detection points G1 or each cluster of multiple detection points G1 as a heat source corresponding to one or more people. The threshold is, for example, 1 K. Here, multiple heat sources do not contact each other in the temperature difference data 22. The number of people estimation unit 40 detects the position and number of people for each heat source. The number of people estimation unit 40 stores the positions and number of people as person position data 23 in the memory unit 20 and outputs it to the movement estimation unit 50.

[0028] Next, the movement estimation unit 50 of the measurement system 1 estimates the movement of people based on the multiple person position data 23 (step S4). The movement estimation unit 50 reads out the person position data 23 immediately before the latest one from the memory unit 20. The movement estimation unit 50 determines whether the person positions are close to each other between the person position data 23 generated by the number of people estimation unit 40 in step S3 and the person position data 23 read out from the memory unit 20, and estimates whether the people are the same person. If there is a person who can be estimated to be the same person, the movement estimation unit 50 adds the movement direction to the person position data 23. The movement estimation unit 50 stores the person position data 23 in the memory unit 20 and outputs it to the movement detection unit 60.

[0029] Next, the movement detection unit 60 of the measurement system 1 counts the number of people in the space AR1 based on the person position data 23 (step S5). Based on the multiple detection points G1, the movement detection unit 60 sets an area A1 (see FIG. 5A) corresponding to the space AR1, an area A3 (see FIG. 5A) corresponding to the space AR3, and a detection area D1 that separates the areas A1 and A3. If a person's position after moving is in the area A1 and their position before moving is in the area A3, the movement detection unit 60 detects that the person has entered the space AR1. Furthermore, if a person's position after moving is in the area A3 and their position before moving is in the area A1, the movement detection unit 60 detects that the person has left the space AR1. The movement detection unit 60 counts the number of people entering and leaving the space AR1.

[0030] (3.2) Specific examples 5A to 5D are schematic diagrams showing the time series of positions of a person as he or she enters space AR1. In FIGS. 5A to 5D, position P1 indicates the position of the person, and the direction of the arrow indicates the direction of the person's movement. In temperature distribution data 21, position P1 is the center of an area with a higher temperature than the surrounding area. The measurement system 1 detects whether a person moves between area A1, which corresponds to space AR1 and includes 6 × 3 detection points G1, and area A3, which corresponds to space AR3 and includes 6 × 3 detection points G1. Detection area D1 is the boundary between area A1 and area A3. In other words, when the measurement system 1 detects that person's position P1 has moved across the linear detection area D1, which is the boundary between area A1 and area A3, it measures that a person has entered or exited space AR1.

[0031] When a person passes through area AR2 from space AR3 to space AR1, position P1 of the person approaches area A3 as shown in Fig. 5A, and then moves into area A3 as shown in Fig. 5B. Then, position P1 of the person moves into area A1 across detection area D1 as shown in Fig. 5C, and then moves out of area A1 as shown in Fig. 5D. In this case, the measurement system 1 determines that the person corresponding to position P1 has entered space AR1 in the state shown in Fig. 5C.

[0032] 6A to 6D are schematic diagrams showing the positions of two people over time as they enter space AR1. In FIGS. 6A to 6D, positions P2 and P3 indicate the positions of the people, and the arrows indicate the direction of movement of the people. In temperature distribution data 21, positions P2 and P3 of the people are each in an area with a higher temperature than the surrounding area. In this case, position P3 of one of the two people approaches area A1 as shown in FIG. 6A, and position P3 of the person enters area A3 as shown in FIG. 6B. Furthermore, position P3 of the person moves into area A1 across detection area D1 as shown in FIG. 6C, and position P3 of the person moves out of area A1 as shown in FIG. 6D. Meanwhile, position P2 of the other of the two people approaches area A1 as shown in FIG. 6A, and position P2 of the person enters area A3 as shown in FIG. 6B. Thereafter, the position P2 of the person remains in the area A3 as shown in FIG. 6C, and then the position P2 of the person moves across the detection area D1 to the area A1 as shown in FIG. 6D.

[0033] In this case, the measurement system 1 compares the positions P2 and P3 of the two people in Figure 6B with the positions P2 and P3 of the two people in Figure 6A and infers that the position P2 of the two people corresponds to one person and the position P3 of the two people corresponds to another person. Similarly, the measurement system 1 compares the positions P2 and P3 of the two people between Figures 6B and 6C and between Figures 6C and 6D and infers that the position P2 of the two people corresponds to one person and the position P3 of the two people corresponds to another person. Then, the measurement system 1 determines that the person corresponding to the position P3 of the person has entered the space AR1 in the state shown in Figure 6C. Furthermore, the measurement system 1 determines that the person corresponding to the position P2 of the person has entered the space AR1 in the state shown in Figure 6D.

[0034] (4) Effects A measurement system 1 according to the first embodiment measures people entering and exiting a space AR1. The measurement system 1 includes a temperature acquisition unit 10, a memory unit 20, a difference calculation unit 30, a number of people estimation unit 40, a movement estimation unit 50, and a movement detection unit 60. The temperature acquisition unit 10 repeatedly acquires temperature distribution data 21 indicating a temperature distribution corresponding to a plurality of detection points G1 arranged in a matrix in an area AR2 where people enter and exit the space AR1. The memory unit 20 stores the plurality of temperature distribution data 21. The difference calculation unit 30 repeatedly generates temperature difference data 22 from the plurality of temperature distribution data 21. The number of people estimation unit 40 repeatedly estimates the positions and number of people from the temperature difference data 22. The movement estimation unit 50 estimates the movements of people based on time-series changes in the positions and number of people. The movement detection unit 60 detects the number of people entering and exiting the space AR1 based on the positions and number of people and their movements. This allows the measurement system 1 to measure the number of people entering and exiting the space AR1 by detecting the number of people passing through the area AR2 where people enter and exit the space AR1, without having to detect the number of people in the entire space AR1. Therefore, it becomes possible to easily measure the number of people entering and exiting the space AR1.

[0035] In the measurement system 1 according to the first embodiment, the temperature distribution data 21 is temperature data corresponding to each of a plurality of detection points G1 arranged in a matrix. The movement detection unit 60 determines that a person has entered or exited the space AR1 when the person passes through a detection area D1 based on the plurality of detection points G1. As a result, the measurement system 1 detects the position of the person based on the coordinates of the temperature distribution data 21, and therefore, it becomes possible to detect the entry or exit of a person into or exit from the space AR1 by simple processing.

[0036] The measurement method according to the first embodiment may also measure people entering and exiting a space. The measurement method according to the first embodiment includes a temperature acquisition step, a storage step, a difference calculation step, a number of people estimation step, a movement estimation step, and a movement detection step. In the temperature acquisition step, temperature distribution data 21 indicating temperatures corresponding to a plurality of detection points G1 arranged in a matrix in an area AR2 where people enter and exit the space AR1 is repeatedly acquired. In the storage step, the plurality of temperature distribution data 21 is stored. In the difference calculation step, an operation of generating temperature difference data 22 from the plurality of temperature distribution data 21 is repeatedly performed. In the number of people estimation step, an operation of estimating the positions and number of people from the temperature difference data 22 is repeatedly performed. In the movement estimation step, the movement of people is estimated based on time-series changes in the positions and number of people. In the movement detection step, the number of people entering and exiting the space AR1 is detected based on the positions and number of people and their movement.

[0037] The program according to the first embodiment may cause one or more processors to execute the measurement method according to the first embodiment.

[0038] (Embodiment 2) (1) Composition In the measurement system 1 according to the second embodiment, the number-of-people estimation unit 40 detects the number of people based on the temperature difference data 22 as follows.

[0039] The number of people estimation unit 40 determines whether one heat source corresponds to multiple people based on the time-series changes in the temperature difference data 22. More specifically, the number of people estimation unit 40 detects how many people actually exist at positions shown as high-temperature areas in the temperature distribution data 21, depending on whether the temperature difference from the surrounding area is large.

[0040] 7A to 7D are schematic diagrams showing the position P4 of a person over time as the person enters the space AR1. In Fig. 7A to 7D, position P4 indicates the position of the person, and the direction of the arrow indicates the direction of movement. In the temperature distribution data 21, the position P4 of the person is shown as an area with a higher temperature than the surrounding area.

[0041] The following table shows the temperatures at multiple detection points G1 in the fourth column from the left in the temperature distribution data 21 corresponding to Figure 7A. Note that in the table below, the nth row (n is a natural number) refers to the first row at the top and the eighth row at the bottom in Figure 7A. That is, the temperature of detection point G1 in the eighth row, which is person position P4, is 25°C.

[0042] [Table 1]

[0043] 7B, the temperatures at the multiple detection points G1 in the fourth column from the left are shown in the table below. That is, the temperature at detection point G1 in the fifth row, which is person position P4, has changed to 25°C, and the temperature at detection point G1 in the eighth row, which was person position P4 in FIG. 7A, has changed to 22°C.

[0044] [Table 2]

[0045] 7C, the temperatures at the multiple detection points G1 in the fourth column from the left are shown in the table below. That is, the temperature at detection point G1 in the third row, which is person position P4, has changed to 25°C, and the temperature at detection point G1 in the fifth row, which was person position P4 in FIG. 7B, has changed to 22°C.

[0046] [Table 3]

[0047] 7D, the temperatures at the multiple detection points G1 in the fourth column from the left are shown in the table below. That is, the temperature at detection point G1 in the first row, which is person position P4, has changed to 25°C, and the temperature at detection point G1 in the third row, which was person position P4 in FIG. 7C, has changed to 23°C.

[0048] [Table 4]

[0049] 8A to 8D are schematic diagrams showing positions P5 and P6 of two people in a time series when they enter space AR1 in a nearly close contact state. In Fig. 8A to 8D, positions P5 and P6 indicate the positions of the people, and the direction of the arrows indicates the direction of movement of the people. In temperature distribution data 21, positions P5 and P6 of the people are shown as areas with a higher temperature than the surrounding area, and because they are in close contact with each other, they cannot be distinguished, as will be described later.

[0050] The following table shows the temperatures at multiple detection points G1 in the fourth column from the left in the temperature distribution data 21 corresponding to FIG. 8A. The temperature of detection point G1 in the eighth row, which corresponds to person positions P5 and P6, is 26°C. Here, person positions P5 and P6 cannot be distinguished in the temperature distribution data 21 and the temperature difference data 22, but in the area corresponding to detection point G1 at person positions P5 and P6, the proportion of people is greater than when there is only one person. Therefore, the temperature of detection point G1 at person positions P5 and P6 is higher than when there is only one person.

[0051] [Table 5]

[0052] Similarly, the temperatures at multiple detection points G1 in the fourth column from the left in the temperature distribution data 21 corresponding to Figure 8B are shown in the table below. The temperature at detection point G1 in the fifth row, which corresponds to positions P5 and P6 of people, has changed to 26°C, and the temperature at detection point G1 in the eighth row, which corresponds to positions P5 and P6 of people in Figure 8A, has changed to 25°C.

[0053] [Table 6]

[0054] Similarly, in the temperature distribution data 21 corresponding to Figure 8C, the temperatures at the multiple detection points G1 in the fourth column from the left are shown in the table below. The temperature at detection point G1 in the third row, which corresponds to positions P5 and P6 of people, has changed to 26°C, and the temperature at detection point G1 in the fifth row, which corresponds to positions P5 and P6 of people in Figure 8B, has changed to 24°C.

[0055] [Table 7]

[0056] Similarly, the temperatures at multiple detection points G1 in the fourth column from the left in the temperature distribution data 21 corresponding to Figure 8D are shown in the table below. The temperature at detection point G1 in the first row, which corresponds to positions P5 and P6 of people, has changed to 27°C, and the temperature at detection point G1 in the third row, which corresponds to positions P5 and P6 of people in Figure 8C, has changed to 23°C.

[0057] [Table 8]

[0058] As described above, when multiple people pass through area AR2, if the distance between people is small compared to the size of the area corresponding to each of the multiple detection points G1, they may become a single heat source that is inseparable in the temperature distribution data 21 and the temperature difference data 22. On the other hand, the more people there are corresponding to a single heat source, the higher the temperature detected in the temperature distribution data 21, and the temperature of detection point G1 where the heat source was most recently located may remain high. Therefore, if the maximum value of the temperature difference in the temperature difference data 22 is large for a heat source, the number of people estimation unit 40 estimates that the number of people is large according to the maximum value of the temperature difference.

[0059] (2) Effects In the measurement system 1 according to the second embodiment, the number-of-people estimation unit 40 determines whether one heat source corresponds to multiple people based on the time-series changes in the temperature difference data 22. This enables the measurement system 1 to accurately estimate the number of people even if multiple people enter and exit the space AR1 while being close to each other.

[0060] (Embodiment 3) In the measurement system 1 according to the third embodiment, the number-of-people estimation unit 40 detects the number of people based on the temperature difference data 22 as follows.

[0061] The number of people estimation unit 40 determines whether one heat source corresponds to multiple people based on the temperature difference data 22. More specifically, the number of people estimation unit 40 determines whether an image of a person shown as a high-temperature area in the temperature distribution data 21 is an image of one person or an image of multiple people based on the temperature difference.

[0062] 9A and 9B are schematic diagrams showing the time series of a person's position P7 as they enter space AR1. In Fig. 9A and Fig. 9B, position P7 indicates the person's position, and the direction of the arrow indicates the direction of movement. In temperature distribution data 21, person's position P7 is shown as the center of an area with a higher temperature than the surrounding area.

[0063] The temperatures in the third to fifth columns from the left in the temperature distribution data 21 corresponding to FIG. 9A are shown in the table below. Note that in the table below, the leftmost column of the table corresponds to the third column from the left in FIG. 9A, the center column corresponds to the fourth column from the left in FIG. 9A, and the rightmost column of the table corresponds to the fifth column from the left in FIG. 9A. That is, the bottom row of the center column of the table corresponds to person position P7, and the temperature is 25°C. Here, the only detection point G1 whose temperature is higher than the surrounding area is person position P7.

[0064] [Table 9]

[0065] In addition, the temperatures in the third to fifth columns from the left in the temperature distribution data 21 corresponding to Figure 9B are shown in the table below. That is, the fifth row from the top in the center column of the table corresponds to the person's position P7, and the temperature is 25°C. Here, the only detection point G1 whose temperature is higher than the surrounding area is the detection point G1 corresponding to the person's position P7.

[0066] [Table 10]

[0067] 10A and 10B are schematic diagrams showing the positions P8 and P9 of two people over time as they enter space AR1. In Fig. 10A and Fig. 10B, positions P8 and P9 indicate the positions of the people, and the direction of the arrows indicates the direction of movement. In temperature distribution data 21, positions P8 and P9 of the people are shown as a single area with a higher temperature than the surrounding area.

[0068] In the temperature distribution data 21 shown in FIG. 10A, the temperatures in the third to fifth columns from the left are shown in the table below. Note that in the table below, the leftmost column of the table corresponds to the third column from the left in FIG. 10A, the center column corresponds to the fourth column from the left in FIG. 10A, and the rightmost column of the table corresponds to the fifth column from the left in FIG. 10A. That is, the bottom row of the center column of the table corresponds to person positions P8 and P9, and the temperature is 26°C. Here, the only detection point G1 whose temperature is higher than the surrounding area is the detection point G1 corresponding to person positions P8 and P9.

[0069] [Table 11]

[0070] 10B, the temperatures in the third to fifth columns from the left are shown in the table below. That is, the fifth row from the top in the center column of the table corresponds to the positions P8 and P9 of people, and the temperature is 26°C. Here, the detection point G1 that has a higher temperature than the surrounding area is not only the detection point G1 that corresponds to the positions P8 and P9 of people, but also the detection points G1 adjacent to it in the left and right directions.

[0071] [Table 12]

[0072] Here, when a heat source, which is a high-temperature region in the temperature difference data 22, includes multiple detection points G1, the number of people estimation unit 40 calculates the number of detection points corresponding to the heat source as follows: For the detection point G1 (hereinafter referred to as the "central detection point") with the largest temperature difference from the surroundings, the number of people estimation unit 40 determines that the number of detection points G1 corresponding to the central detection point is 1. The central detection point corresponds to the position of a person. Furthermore, the number of people estimation unit 40 detects the maximum temperature difference from the surroundings for eight detection points G1 adjacent to the central detection point (hereinafter referred to as the "peripheral detection point group"), and determines the number of detection points G1 corresponding to the peripheral detection point group by dividing the maximum temperature difference by the temperature difference of the central detection point. That is, in the temperature distribution data 21 corresponding to FIG. 10B, the detection point G1 in the fourth column from the left and the fifth row from the top, which corresponds to the positions P8 and P9 of people, is the central detection point, and its temperature difference is 3 K. The number of people estimation unit 40 determines that the number of detection points G1 corresponding to the central detection point is 1. 10B, the maximum temperature value for the eight detection points G1 corresponding to the peripheral detection point group is 24°C, and therefore the maximum temperature difference is 1K. Therefore, the number of detection points G1 corresponding to the peripheral detection point group is 1 / 3, which is the value obtained by dividing 1K, the maximum temperature difference, by 3K, the temperature difference of the central detection point. In other words, the number of people estimation unit 40 determines that the number of detection points G1 corresponding to person positions P8 and P9 is 4 / 3.

[0073] As described above, when multiple people pass through area AR2, if the distance between people is small compared to the size of the space corresponding to each of the multiple detection points G1, they may form a single heat source that is inseparable in the temperature distribution data 21 and the temperature difference data 22. On the other hand, the greater the number of people corresponding to one heat source, the more spatially the area where the detected temperature is high expands in the temperature difference data 22. Therefore, when the number of detection points G1 corresponding to heat sources is large in the temperature difference data 22, the number of people estimation unit 40 estimates that the number of people is large according to that value.

[0074] (2) Effects In the measurement system 1 according to the third embodiment, the number of people estimation unit 40 determines the number of people corresponding to the heat source based on the temperature distribution of the multiple detection points G1, using the temperature difference data 22. This allows the measurement system 1 to accurately estimate the number of people even when multiple people enter and exit the space AR1 while in close proximity to each other. In other words, the measurement system 1 can estimate the number of people even when the resolution of the temperature sensor 2 is so low that it is impossible to distinguish whether there is one person or multiple people. Therefore, the measurement system 1 can estimate the number of people even when the resolution of the temperature sensor 2 cannot be improved, for example, when the temperature sensor 2 cannot be placed close enough to identify people's gender or body shape due to privacy protection reasons.

[0075] (Embodiment 4) (1) Composition In the measurement system 1 according to the fourth embodiment, the number-of-people estimation unit 40 changes the threshold when detecting the number of people based on the temperature difference data 22.

[0076] As shown in FIG. 11, each of the multiple detection points G1 corresponds to a quadrangular pyramid-shaped region with the sensor position of the temperature sensor 2 as its vertex. Therefore, when the same temperature sensor 2 is used, the volume of the region corresponding to the detection point G1 increases as the height H1 of the temperature sensor 2 from the floor or ground increases. Furthermore, the temperature corresponding to each of the multiple detection points G1 is a representative value of the temperatures of multiple objects present in the region corresponding to the detection point G1. Therefore, even if the size, body temperature, and clothing of a person PS1 passing through the region AR2 are the same, the lower the height H1 of the temperature sensor 2, the greater the temperature difference due to the greater influence of the person PS1's body temperature. Conversely, the higher the height H1 of the temperature sensor 2, the smaller the temperature difference due to the less influence of the person PS1's body temperature.

[0077] Therefore, in the measurement system 1 according to the fourth embodiment, the number of people estimation unit 40 changes the threshold for detecting the presence or absence of a person based on the temperature difference data 22. The number of people estimation unit 40 changes the threshold for the temperature difference for estimating the presence of one person, for example, based on the value of the temperature difference of the heat source corresponding to the person. For example, if the minimum value of the temperature difference of the heat source corresponding to a person is 2 K, the number of people estimation unit 40 changes the threshold for the temperature difference for detecting the heat source corresponding to a person to 2 K. This makes it possible in the measurement system 1 according to the fourth embodiment to reduce the occurrence of overcounting the number of people due to a threshold that is too small, or of failing to detect the movement of a person due to a threshold that is too large.

[0078] Furthermore, in the measurement system 1 according to the fourth embodiment, the threshold value may be changed depending on the season, for example. Depending on the installation location of the temperature sensor 2, the temperature in the area AR2 may fluctuate depending on the season. In contrast, the body temperatures of people passing through the area AR2 do not fluctuate as much as the air temperature, so the temperature difference between the detection point G1 where people are present and the detection point G1 where no people are present changes depending on the season. Specifically, even if the number of people is the same, if the temperature in the area AR2 is high, the temperature difference between the heat sources corresponding to people will be small, and if the temperature in the area AR2 is low, the temperature difference between the heat sources corresponding to people will be large. Therefore, the number of people estimation unit 40 changes the threshold value for the temperature difference used to estimate the number of people as one person, for example, based on the average temperature in the area AR2. Here, the number of people estimation unit 40 may change the threshold value for the temperature difference used to estimate the number of people as one person, for example, based on the value of the temperature difference between the heat sources corresponding to people. This is because the lower the temperature in the area AR2, the larger the temperature difference between the heat sources corresponding to people.

[0079] (2) Effects In the measurement system 1 according to the fourth embodiment, the number-of-people estimation unit 40 changes the threshold for detecting the presence or absence of a person based on the temperature difference data 22. This makes it possible to reduce the influence of the distance between the person and the temperature sensor or the average temperature of the area AR2 on the person detection accuracy.

[0080] (Embodiment 5) (1) Composition In the measurement system 1 according to the fifth embodiment, the movement detection unit 60 detects movement using detection points G1 in at least four rows and four columns.

[0081] FIG. 12A is a schematic diagram showing the movement of a person's position when one person moves through area AR2 at high speed, with position P10 indicating the person's position. More specifically, this corresponds to two consecutive acquisitions of temperature distribution data 21, with person position P10a corresponding to the first acquisition and person position P10b corresponding to the second acquisition. On the other hand, FIG. 12B is a schematic diagram showing the movement of a person's position when one person moves through area AR2 at low speed, with position P11 indicating the person's position. More specifically, this corresponds to the consecutive acquisitions of temperature distribution data 21 on the fourth floor, with person position P11a corresponding to the first acquisition, person position P11b corresponding to the second acquisition, person position P11c corresponding to the third acquisition, and person position P11d corresponding to the fourth acquisition.

[0082] 12B, when the change in person's position P11 is small compared to the interval between detection points G1, it is possible to detect the person's movement using only the detection points G1 around the detection area D1. On the other hand, when the change in person's position P10 is large compared to the interval between detection points G1 as shown in FIG. 12A, when an attempt is made to detect the person's movement using only the detection points G1 around the detection area D1, the person's position may cross the detection area D1 without being detected near the detection area D1. That is, for example, when the areas of area A1 and area A3 are each reduced, it may not be possible to detect the state in which the person has entered area A1 or area A3, and it may not be possible to detect that the person has crossed the detection area D1.

[0083] In contrast, in the measurement system 1 according to the fifth embodiment, the movement detection unit 60 detects human movement using areas A1 and A3 where at least detection point G1 is arranged in 4 rows and 4 columns. This makes it possible to improve the accuracy of detecting human movement even when a person passes through area AR2 at high speed or when the temperature sensor is close to the person.

[0084] (2) Effects In the measurement system 1 according to the fifth embodiment, the movement detection unit 60 detects the movement of a person using areas A1 and A3 where at least the detection point G1 among the multiple detection points G1 is arranged in 4 rows and 4 columns. This enables the measurement system 1 to improve the accuracy of detecting the movement of a person even when the person passes through the area AR2 at high speed or when the temperature sensor is close to the person.

[0085] (Embodiment 6) (1) Composition In the measurement system 1 according to the sixth embodiment, the movement detection unit 60 uses an area DA1 including one or more rows of detection points G1 as the detection area D1.

[0086] FIG. 13A is a schematic diagram showing the movement of a person's position when one person moves through area AR2 at high speed, with position P12 indicating the person's position. More specifically, this corresponds to two consecutive acquisitions of temperature distribution data 21, with person position P12a corresponding to the first acquisition and person position P12b corresponding to the second acquisition. Meanwhile, FIG. 13B is a schematic diagram showing the movement of a person's position when one person moves through area AR2 at low speed, with position P13 indicating the person's position. More specifically, this corresponds to the consecutive acquisitions of temperature distribution data 21 on the fourth floor, with person position P13a corresponding to the first acquisition, person position P13b corresponding to the second acquisition, person position P13c corresponding to the third acquisition, and person position P13d corresponding to the fourth acquisition.

[0087] 13B, if the change in person position P13 is small compared to the interval between detection points G1, it is highly likely that person position P13 is adjacent to detection area D1, and it is therefore possible to detect that the person has crossed over detection area D1. On the other hand, if the change in person position P12 is large compared to the interval between detection points G1, as shown in FIG. 13A, it may be difficult to determine whether the person has crossed over detection area D1, as person position P12 may not be adjacent to detection area D1.

[0088] In contrast, in the measurement system 1 according to the sixth embodiment, the detection area DA1 includes multiple detection points arranged in one or more rows. This makes it easier to detect whether a person has crossed the detection area DA1, even when the person passes through the area AR2 at high speed or when the temperature sensor is close to the person, thereby improving the accuracy of detecting the movement of the person.

[0089] (2) Effects In the measurement system 1 according to the sixth embodiment, the detection area DA1 includes multiple detection points arranged in one or more rows. This makes it easy to detect whether a person has crossed the detection area DA1, even when the person passes through the area AR2 at high speed or when the temperature sensor is close to the person, thereby improving the accuracy of detecting the movement of the person.

[0090] (Aspect) A measurement system (1) according to a first aspect measures people entering and exiting a space (AR1). The measurement system (1) includes a temperature acquisition unit (10), a memory unit (20), a difference calculation unit (30), a number of people estimation unit (40), a movement estimation unit (50), and a movement detection unit (60). The temperature acquisition unit (10) repeatedly acquires temperature distribution data (21) indicating temperatures corresponding to a plurality of detection points (G1) arranged in a matrix in an area (AR2) where people enter and exit the space (AR1). The memory unit (20) stores the plurality of temperature distribution data (21). The difference calculation unit (30) repeatedly generates temperature difference data (22) from the plurality of temperature distribution data (21). The number of people estimation unit (40) repeatedly estimates the positions and number of people from the temperature difference data (22). The movement estimation unit (50) estimates the movement of people based on time-series changes in the positions and number of people. The movement detection unit (60) detects the number of people entering and leaving the space (AR1) based on the positions and number of people and the movement of people.

[0091] According to the measurement system (1) of the above aspect, the measurement system (1) can measure the number of people entering and exiting the space (AR1) by detecting the number of people passing through the area (AR2) where people enter and exit the space (AR1), so it is not necessary to detect the number of people in the entire space (AR1). Therefore, it is possible to easily measure the number of people entering and exiting the space (AR1).

[0092] In the measurement system (1) according to the second aspect, in the first aspect, the movement detection unit (60) determines that a person has entered or exited a space (AR1) when the person passes through a detection area (D1; DA1) based on a plurality of detection points (G1).

[0093] According to the measurement system (1) of the above aspect, the position of a person is detected based on the coordinates of the temperature distribution data (21), so that it is possible to detect the entrance and exit of a person into the space (AR1) by simple processing.

[0094] In the measurement system (1) according to the third aspect, in the second aspect, the detection area (DA1) includes a plurality of detection points (G1) arranged in one or more rows.

[0095] According to the measurement system (1) relating to the above aspect, even when a person passes through the area (AR2) at high speed or when the temperature sensor is close to the person, it becomes easy to detect whether the person has crossed the detection area (DA1), thereby improving the accuracy of detecting the movement of the person.

[0096] In the measurement system (1) according to the fourth aspect, in any of the first to third aspects, the number-of-people estimation unit (40) determines whether one heat source corresponds to multiple people based on a time-series change in the temperature difference data (22).

[0097] According to the measurement system (1) of the above aspect, it is possible to accurately estimate the number of people even if multiple people enter and exit the space (AR1) while being close to each other.

[0098] In the measurement system (1) according to the fifth aspect, in any of the first to fourth aspects, the number of people estimation unit (40) determines the number of people corresponding to the heat source based on the temperature distribution of the plurality of detection points (G1) based on the temperature difference data (22).

[0099] According to the measurement system (1) of the above aspect, it is possible to accurately estimate the number of people even if multiple people enter and exit the space (AR1) while being close to each other.

[0100] In the measurement system (1) according to a sixth aspect, in any of the first to fifth aspects, the number-of-people estimation unit (40) changes a threshold value for detecting the presence or absence of a person based on the temperature difference data (22).

[0101] According to the measurement system (1) of the above aspect, it is possible to reduce the influence of the distance between a person and the temperature sensor or the average temperature of the area (AR2) on the accuracy of human detection.

[0102] In the measurement system (1) according to the seventh aspect, in any of the first to sixth aspects, the movement detection unit (60) detects the movement of a person using an area in which at least the detection points (G1) out of the multiple detection points (G1) are arranged in four rows and four columns.

[0103] According to the measurement system (1) relating to the above aspect, it is possible to improve the accuracy of detecting human movement even when a person passes through the area (AR2) at high speed or when the temperature sensor is close to the person.

[0104] A measurement method according to an eighth aspect measures people entering and exiting a space (AR1). The measurement method includes a temperature acquisition step, a storage step, a difference calculation step, a number of people estimation step, a movement estimation step, and a movement detection step. In the temperature acquisition step, temperature distribution data (21) indicating temperatures corresponding to a plurality of detection points (G1) arranged in a matrix in an area (AR2) where people enter and exit the space (AR1). In the storage step, the plurality of temperature distribution data (21) is stored. In the difference calculation step, an operation of generating temperature difference data (22) from the plurality of temperature distribution data (21) is repeated. In the number of people estimation step, an operation of estimating the positions and number of people from the temperature difference data (22) is repeated. In the movement estimation step, the movement of people is estimated based on time-series changes in the positions and number of people. In the movement detection step, the number of people entering and exiting the space (AR1) is detected based on the positions and number of people and the movement of people.

[0105] According to the measurement method of the above aspect, it is possible to measure the number of people entering and exiting the space (AR1) by detecting the number of people passing through the area (AR2) where people enter and exit the space (AR1), so it is not necessary to detect the number of people in the entire space (AR1). Therefore, it is possible to easily measure the number of people entering and exiting the space (AR1).

[0106] A program according to a ninth aspect causes one or more processors to execute the measurement method according to the eighth aspect.

[0107] According to the above program, it is possible to measure the number of people entering and exiting the space (AR1) by detecting the number of people passing through the area (AR2) where people enter and exit the space (AR1), so it is not necessary to detect the number of people in the entire space (AR1). Therefore, it is possible to easily measure the number of people entering and exiting the space (AR1). [Explanation of symbols]

[0108] 1. Measurement system 10 Temperature acquisition section 20 Memory section 30 Difference calculation part 40 Number of people estimation part 50 Movement estimation part 60 Movement detection unit 21 Temperature distribution data 22 Temperature differential data AR1 space AR2 area G1 detection point D1, DA1 detection area

Claims

1. A measurement system for measuring people entering and exiting a space, comprising: a temperature acquisition unit that repeatedly acquires temperature distribution data indicating temperatures corresponding to a plurality of detection points arranged in a matrix in an area where people enter and exit the space; a storage unit that stores a plurality of pieces of temperature distribution data; a difference calculation unit that repeats an operation of generating temperature difference data from the plurality of temperature distribution data; a number-of-people estimation unit that repeats an operation of estimating the position and number of people from the temperature difference data; a movement estimation unit that estimates the movement of people based on time-series changes in the positions and number of people; a movement detection unit that detects the number of people entering and exiting the space based on the positions and number of people and the movements of the people, Measurement system.

2. the movement detection unit determines that a person has entered or exited the space when the person passes through a detection area based on the plurality of detection points; The measurement system of claim 1 .

3. The detection area includes a plurality of detection points arranged in one or more rows. The measurement system of claim 2 .

4. the number-of-people estimation unit determines whether one heat source corresponds to multiple people based on a time-series change in the temperature difference data. The measurement system of claim 1 .

5. the number-of-people estimation unit determines the number of people based on the temperature distribution at a plurality of detection points, based on the temperature difference data. The measurement system of claim 1 .

6. the number-of-people estimation unit changes a threshold for detecting the presence or absence of a person based on the temperature difference data. The measurement system of claim 1 .

7. the movement detection unit detects movement of a person using at least an area in which the detection points are arranged in four rows and four columns among the plurality of detection points; The measurement system of claim 1 .

8. A measurement method for measuring people entering and exiting a space, comprising: a temperature acquisition step of repeatedly acquiring temperature distribution data indicating temperatures corresponding to a plurality of detection points arranged in a matrix in an area where people enter and exit the space; a storage step of storing a plurality of pieces of the temperature distribution data; a difference calculation step of repeating an operation of generating temperature difference data from the plurality of temperature distribution data; a number-of-people estimation step of repeating an operation of estimating the positions and number of people from the temperature difference data; a movement estimation step of estimating the movement of people based on time-series changes in the positions and number of people; and a movement detection step of detecting the number of people entering and exiting the space based on the positions and number of people and the movements of the people. Measurement method.

9. 9. The method of claim 8, wherein one or more processors are configured to execute the measurement method. program.

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