JP2024087437A - Human detection device, lighting control system, air conditioning control system, integrated management system, thermal human detection device, and monitoring system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a human detection device that can improve the accuracy of detecting the positions of people, and a lighting control system that can improve the accuracy of detecting the positions of people and realize an appropriate lighting environment according to information on the detected positions.

SOLUTION: A human detection device disclosed herein is configured to perform a process of capturing an image of a space at a regular interval, a process of extracting a structure with the linear feature captured in the image as an inactive area, a process of detecting people captured in the image as frames, an exclusion process of excluding the influence of the inactive area from the frames, and a process of determining the positions of the people from the frames after the exclusion process in accordance with a specified rule.

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2024,JPO&INPIT

Description

This disclosure relates to a human detection device, a lighting control system, an air conditioning control system, an integrated management system, a thermal human detection device, and a monitoring system.

There is a technology that places a human detection device equipped with an image sensor or the like on the ceiling, removes the influence of non-target areas from the imaging range of image data obtained by imaging the target space, and senses people walking/staying, presence/absence, number of people, activity level, and spatial illuminance, etc., from image processing limited to the target area (see, for example, Patent Document 1).

Patent No. 7005285

In human detection devices such as image sensors, a wide-angle lens is often attached to the CMOS camera, which is installed on the ceiling and captures a wide area centered on directly below. Since the image of a wide-angle lens is distorted at the edges, people occupy a wide area, and if the target range for image processing is further limited to a symmetrical area, there is an issue that the accuracy of detecting the position of people decreases.

In addition, if the accuracy of detecting a person's position decreases, even if lighting control or air conditioning control is performed based on the position information detected by the human detection device, it may not be possible to achieve a suitable lighting environment or air conditioning environment for the detected person.

In order to solve the above-mentioned problems, the first objective of this disclosure is to provide a human detection device that can improve the accuracy of detecting the position of a person.

A second objective of the present disclosure is to provide a lighting control system that can improve the accuracy of detecting a person's position and realize an optimal lighting environment according to the detected position information.

A third objective of the present disclosure is to provide an air conditioning control system that can improve the accuracy of detecting a person's position and realize an optimal air conditioning environment according to the detected position information.

Furthermore, a fourth objective of the present disclosure is to provide an integrated management system that can improve the accuracy of detecting a person's position and realize an optimal lighting environment according to the detected position information.

Furthermore, a fifth objective of this disclosure is to provide a thermal human detection device that can improve the accuracy of detecting the position of a person.

The sixth objective of this disclosure is to provide a surveillance system equipped with a human detection device that can improve the accuracy of detecting the position of a person.

A first aspect of the present disclosure relates to a process for capturing an image of a space at regular intervals;
A process of extracting structures having linear features captured in the image as inactive regions;
A process of detecting a person in the image as a frame;
an exclusion process for excluding the influence of the inactive region from the frame;
a position determination process for determining a position of a person from the frame after the exclusion process according to a predetermined rule;
Preferably, the human detection device is configured to perform the following:

A second aspect of the present disclosure includes a human detection device according to claim 1,
A lighting controller;
Lighting equipment and
Equipped with
The lighting controller includes:
a light source state selection process for selecting a light source state of the lighting device based on position information of a person notified from the human detection device;
A process of controlling the lighting device so as to realize the light source state;
Preferably, the lighting control system is configured to:

A third aspect of the present disclosure includes a human detection device according to claim 1,
An indoor unit,
The outdoor unit,
Air conditioning monitoring system;
Equipped with
The air conditioning monitoring system includes:
an air conditioning state selection process for selecting an operating state of the indoor unit and the outdoor unit based on position information of a person notified from the human detection device;
A process of controlling the indoor unit and the outdoor unit so as to realize the operating state;
Preferably, the air conditioning control system is configured to execute the following:

A fourth aspect of the present disclosure is an integrated management system for managing the lighting control system according to claim 2, comprising:
A process of receiving position information of a person detected by the person detection device in a server;
a learned light source state selection process for selecting a light source state of a lighting device included in the lighting control system from learning data based on the position information;
A process of changing a light source state of the lighting device provided in the lighting control system based on a result of the learned light source state selection process;
a learning process for learning a light source state of the lighting device suitable for the location information into the learning data;
Preferably, the system is configured to execute:

A fifth aspect of the present disclosure is a thermal human detection device that detects a temperature distribution in a space and displays the temperature distribution as a thermal image,
The thermal type human detection device is
A process of generating the thermal image at regular intervals;
A process of extracting a near body temperature region showing a temperature distribution of 30 degrees to 40 degrees from the thermal image;
A process of determining whether the near-body temperature region is a human;
is configured to run
If it is determined that the near body temperature region is a human,
A process of detecting a maximum temperature indicated by the near body temperature region as a human body temperature;
determining the location of the person from the near-body temperature region according to a predefined rule;
It is preferable that the method is further configured to execute the following steps.

A sixth aspect of the present disclosure provides a method for detecting a human presence comprising the steps of:
A process of receiving information on absolute coordinates of an installation position from an identified human detection device, the absolute coordinates of which are known, the human detection device being included in the human detection device;
A process of receiving first position information of a person detected by the identified person detection device;
a process of identifying a device that detects a person present at a position indicated by the first position information as an unidentified person detection device among the person detection devices whose absolute coordinates of an installation position are unknown;
receiving second location information of the person detected by the unidentified person detection device when the person is present at the location indicated by the first location information;
A process of identifying absolute coordinates of an installation location of the unidentified person detection device from the first position information and the second position information, and setting the unidentified person detection device as an identified person detection device;
is configured to run
It is preferable that the monitoring system is such that an icon indicating the position of the identified person detection device is placed on a monitoring screen.

According to the first aspect of the present disclosure, it is possible to provide a human detection device that can improve the accuracy of detecting the position of a person.

In addition, according to a second aspect of the present disclosure, it is possible to provide a lighting control system that can improve the accuracy of detecting a person's position and realize a suitable lighting environment according to the detected position information.

Furthermore, according to a third aspect of the present disclosure, it is possible to provide an air conditioning control system that can improve the accuracy of detecting a person's position and realize an optimal air conditioning environment according to the detected position information.

Furthermore, according to the fourth aspect of the present disclosure, it is possible to provide an integrated management system that can improve the accuracy of detecting a person's position and realize an optimal lighting environment according to the detected position information.

Furthermore, according to the fifth aspect of the present disclosure, it is possible to provide a thermal human detection device that can improve the accuracy of detecting the position of a person.

Furthermore, according to a sixth aspect of the present disclosure, it is possible to provide a surveillance system equipped with a human detection device that can improve the accuracy of detecting the position of a person.

2 is a block diagram showing an example of functions of the human detection device according to the first embodiment of the present disclosure. FIG. 11 is a diagram showing an inactive region extracted by a position determination unit of an image processing unit from an image captured by a human detection device. FIG. 11A and 11B are diagrams illustrating an example of a result of a position determination unit of an image processing unit determining a position of a person in an image captured by a human detection device. 11 is a diagram showing how a position determination unit of an image processing unit identifies the position of a person based on an image captured by a human detection device. FIG. 4 is an example of camera information provided in the human detection device according to the first embodiment of the present disclosure. A block diagram showing an example of functions of a heat-type human detection device according to embodiment 2 of the present disclosure. A diagram summarizing information detected by a human detection device, a human presence sensor, and a thermal human detection device in accordance with embodiments 1 and 2 of the present disclosure. FIG. 13 is a diagram illustrating a configuration example of a lighting control system according to a third embodiment of the present disclosure. FIG. 13 is a configuration diagram of an integrated management system according to a fourth embodiment of the present disclosure. 13 is a flowchart showing communication specifications for linking human detection device detection information detected by a human detection device to the cloud in the integrated management system of the present disclosure. 1 is a diagram showing communication specifications for linking a lighting control system and an air conditioning control system to a server in an integrated management system of the present disclosure. FIG. FIG. 13 is a diagram illustrating a configuration example of a lighting control system according to a fifth embodiment of the present disclosure. A diagram showing how a lighting monitoring system identifies the position of a human detection device in a lighting control system according to embodiment 5 of the present disclosure.

First embodiment
1 is a block diagram showing an example of functions of a human detection device 3 according to a first embodiment of the present disclosure. A camera unit 31 of the human detection device 3 includes a CMOS (Complementary Metal-Oxide-Semiconductor) as an imaging element and a wide-angle lens. Image data captured by the camera unit 31 is input to an image processing unit 52 at a constant cycle. The cycle interval is, for example, 200 ms. This corresponds to a frame rate of 5 fps.

The image processing unit 52 is a unit that detects people from image data. The image input unit 32 receives image data input from the camera unit 31. The image input unit 32 transmits the received image data to the image generation unit 33. The image generation unit 33 converts the resolution of the transmitted image data and converts it from a color image to a monochrome image. This allows image processing based on the monochrome image to be performed in the subsequent processing of the image processing unit 52. Note that the resolution conversion in the image generation unit 33 includes, for example, conversion from SVGA (registered trademark) to VGA (registered trademark).

The image generating unit 33 stores the processed latest image data 36 in memory. It also stores the image data received one cycle before (hereinafter referred to as old image data) 35 in memory.

The disturbance determination unit 34 performs disturbance determination based on the image data output from the image generation unit 33. The disturbance determination unit 34 determines that a disturbance has occurred when a luminance change occurs in one direction, either brightening or darkening, in the image data and exceeds a specified value. If it is determined that a disturbance has occurred, the image processing unit 52 does not execute the next process on the image data. In this way, by excluding image data in which a luminance change has occurred due to a change in lighting conditions from the processing target, it is possible to suppress the occurrence of erroneous detection in subsequent human detection.

On the other hand, if the disturbance determination unit 34 determines that there is no disturbance, the same image determination unit 37 performs the subsequent processing. The same image determination unit 37 determines whether there is a change from the two images, the latest image data 36 and the old image data 35. If it is determined that there is no change, the image processing unit 52 does not execute the next process on the image data. On the other hand, if it is determined that there is a change, the illuminance estimation unit 38 and the motion detection unit 41 perform the subsequent processing.

The illuminance estimation unit 38 is a part that performs illuminance estimation. In illuminance estimation, a position determination range 97 of 7.2 m x 7.2 m, which is set in advance by the user, is divided into 64 blocks of 8 x 8. Furthermore, the divided blocks are grouped into a number of areas specified by the user, and the illuminance is estimated for each area. Note that the size of the position determination range 97 does not have to be limited to 7.2 m x 7.2 m. Also, the number of areas specified by the user is, for example, 1 to 4, but it does not have to be limited to this.

The illuminance estimation unit 38 uses the relationship information between the reference image and illuminance stored in advance to estimate the illuminance for each area based on the average luminance of each area. However, in this case, the illuminance estimation is performed after excluding pixels that are brighter than a specified value and pixels that are darker than a specified value.

In addition, in illuminance estimation, a portion of the 64 8x8 blocks can be masked to provide areas where illuminance estimation is not performed. The mask can be set using the infrared setting device 9 or the mobile terminal device 10, which will be described later. When using the mobile terminal device 10, operations are performed via an interface such as a smartphone app. In this way, by setting the mask, it is possible to perform illuminance estimation while excluding blocks that may become noise.

The motion detection unit 41 is a unit that detects people. The motion detection unit 41 includes a slight motion detection unit 39 and a still area determination unit 40. The slight motion detection unit 39 detects changes in brightness and histograms from the latest image data 36 and the old image data 35, and identifies areas in the latest image data 36 where it is recognized that a person has moved as slight motion areas. The still area determination unit 40 identifies parts in the latest image data 36 where it is not recognized that a person has moved as still areas.

In the motion detection unit 41, as in the illuminance estimation unit 38 described above, it is possible to mask a portion of the 64 8x8 blocks to create an area in which human detection is not performed.

The latest image data 36 in which the slight movement area and still area have been identified by the motion detection unit 41 is notified to the position determination unit 42. The position determination unit 42 extracts the inactive area 91 from the latest image data 36, and executes a process to determine the position of the person after removing its influence (hereinafter referred to as the position determination process).

In the position determination process, the position of the person is identified from the slight movement area and the still area based on information such as the installation position of the human detection device 3, the camera installation height, the position determination range 97, and the installation position correction value stored in the camera information 43.

In the position determination unit 42, the position of a person is expressed as a point on the XY coordinate system with the installation position of the person detection device 3 as the coordinate origin (0.0). The notation is, for example, in meters. For example, a point of (0.7, -1.2) m indicates a position 0.7 m in the X direction and 1.2 m in the Y direction relative to the installation position of the person detection device 3. Hereinafter, the point identified by the position determination unit 42 is referred to as a person-identified position 96. The number of people detection unit 44 counts the number of points indicating person-identified positions 96 and detects the number of people present in each area.

The tracking determination unit 45 compares the state of the slight movement area and still area in the latest image data 36 with the state of the old image data 35, and performs a tracking determination of human movement, such as presence/absence, movement, stillness, etc. In the tracking determination, it is determined that human movement has occurred, for example, when the slight movement area moves, when the still area moves, when a part that was a slight movement area becomes a still area, and when a part that was a still area becomes a slight movement area.

In this way, in the image processing unit 52, the illuminance estimation unit 38 detects the illuminance, the position determination unit 42 detects the position of the person, the number of people detection unit 44 detects the number of people, and the tracking determination unit 45 detects the presence/absence and movement of people. Note that hereinafter, the illuminance information detected by the illuminance estimation unit 38, the position information of people detected by the position determination unit 42, the number of people information detected by the number of people detection unit 44, and the information on the movement of people detected by the tracking determination unit 45 are collectively referred to as human detection device detection information.

The human detection device detection information is notified to the communication processing unit 47. The human detection device detection information is also notified to the beacon processing unit 48.

The beacon processing unit 48 transmits a beacon signal (described below) containing the human detection device detection information via the wireless module 49. The beacon signal is used to collect personal information of the person detected by the human detection device 3 from the mobile terminal device 10.

The communication processing unit 47 notifies the communication circuit/power supply circuit 30 of the human detection device detection information notified by the image processing unit 52. When the communication circuit/power supply circuit 30 receives human detection device detection information from the communication processing unit 47, it notifies the human detection device detection information to other devices, such as the lighting controller 1 described below. On the other hand, when a signal is input from another device, it transmits the signal to the communication processing unit 47.

The communication circuit/power supply circuit 30 also serves as a power supply generating unit that generates voltages of 24 V, 5 V, 2.8 V, and 1.8 V that serve as operating power supplies for the circuit. However, the voltage values do not have to be limited to these.

The non-volatile memory 46 is a non-volatile memory such as a ROM (Read Only Memory) or a flash memory that stores information used by the image processing unit 52. By using non-volatile memory, there is no risk of data being lost even in the event of a power outage, and processing in the image processing unit 52 can be resumed when the power is restored.

The light-emitting/receiving element 51 is a receiver that receives an infrared signal from the infrared setting device 9, which will be described later. The light-emitting/receiving element 51 converts the received infrared signal into an electrical signal of 0 V/5 V and transmits it to the infrared communication unit 50. The infrared communication unit 50 analyzes the data contained in the electrical signal.

For example, if the infrared signal contains setting information that the camera installation height of the human detection device 3 is set to 3.0 m, the infrared communication unit 50 stores the camera installation height information in the non-volatile memory 46.

In addition, if the infrared signal includes a notification requesting the number of people information, the infrared communication unit 50 outputs the number of people information counted by the number of people detection unit 44 to the light emitting/receiving element 51 as a 0V/5V electrical signal. The light emitting/receiving element 51 converts the electrical signal into an infrared signal and transmits it to the infrared setting device 9. This makes it possible for the infrared setting device 9 to check the number of people information detected by the human detection device 3.

As described above, the human detection device 3 of the present disclosure detects illuminance, human positions, the number of people, and human movements in the image processing unit 52 based on image data captured by the camera unit 31. Here, in the human detection device 3 of the present disclosure, as a result of the position determination process performed by the position determination unit 42, the position of the person is pinpointed on the coordinate plane as a person-identified position 96.

In addition, the human detection device detection information detected by the image processing unit 52 is notified to other devices from the communication circuit/power supply circuit 30. This makes it possible to utilize pinpointed human position information in the lighting control system 100, air conditioning control system 200, etc., described below.

<Modification>
It should be noted that the light emitting/receiving element 51 may be omitted. The same effect can be obtained by utilizing the cloud and setting and operating from an app on the mobile terminal 10, which will be described later. This point is the same in all of the following embodiments.

Note that in FIG. 1, the image processing unit 52 uses an image difference method for human detection, but the same effect can be obtained by using a machine learning method.

In FIG. 1, it has been described that the human detection device detection information is notified to the mobile terminal device 10. However, only a portion of the information contained in the human detection device detection information may be notified. This also applies to the following embodiments.

Similarly, in FIG. 1, it is described that the human detection device detection information is notified to other devices, but only a portion of the information contained in the human detection device detection information may be notified.

Figure 2 is a diagram showing an inactive region 91 extracted by the position determination unit 42 of the image processing unit 52 from an image captured by the human detection device 3. The position determination unit 42 of the image processing unit 52 performs processing to extract structures with linear features, such as desks and shelves, captured in the captured image 90 as inactive regions 91. In addition, at the edges of the captured image 90, linear features such as walls and windows are determined and set as inactive regions 91. By determining the inactive region 91 based on linear features in this way, it is possible to accurately distinguish the inactive region 91 even at the edges of image data where the image is distorted due to the use of a wide-angle lens. This makes it possible to prevent a decrease in detection accuracy, which was an issue with conventional technology.

It is advisable that the inactive area 91 be updated automatically at least once a year, or by an operator when the room layout is changed.

Figure 3 is a diagram showing an example of the result of determining the position of a person by the position determination unit 42 of the image processing unit 52 for an image 90 captured by the person detection device 3. The person identification position 96 is expressed in XY coordinates (±X, ±Y) with the installation position of the person detection device 3 as the origin. Note that the unit here is cm.

On the X-axis, a positive sign indicates the direction to the right of the paper relative to the installation position of the human detection device 3 in the center of Figure 3, and a negative sign indicates the direction to the left of the paper. On the other hand, on the Y-axis, a positive sign indicates the direction to the top of the paper relative to the installation position of the human detection device 3, and a negative sign indicates the direction to the bottom of the paper.

For example, point A indicates a position 100 cm to the right of the installation position of the human detection device 3 on the paper and 100 cm above the paper. Point B indicates a position 300 cm to the left of the installation position of the human detection device 3 on the paper and 200 cm above the paper. Point C indicates a position 200 cm to the left of the installation position of the human detection device 3 on the paper and 400 cm below the paper.

Figure 4 is a diagram showing how the position determination unit 42 of the image processing unit 52 identifies the position of a person based on the captured image 90 captured by the person detection device 3. In Figure 4, for ease of explanation, the desk in the center of the captured image 90 is marked as an inactive area 91, but the marks for the inactive areas 91 are omitted for the walls and windows on the periphery.

As explained in FIG. 2, the position determination unit 42 performs a process of extracting structures with linear features, such as desks or shelves, captured in the captured image 90 as inactive regions 91. The position determination unit 42 further performs a process of detecting people captured in the latest image data 36 as person detection frames 92. For example, in FIG. 4, the position determination unit 42 determines that person 98(1) is a person, and recognizes the area of the person as person detection frame 92(1). The position determination unit 42 further performs a process of identifying the positions of the head 93(1) and feet 94(1) from the person detection frame 92(1).

Here, person detection frame 92(1) partially overlaps with inactive region 91(1), and in this state, even if the positions of head 93(1) and feet 94(1) are identified from person detection frame 92(1), these positions will contain errors. For example, when person detection frame 92(1) partially overlaps with inactive region 91(1), etc., the position of head 93(1) will be determined to be (-20, 350), and the position of feet 94(1) will be determined to be (-20, 110), which will result in them being determined to be larger than the actual person.

The position determination unit 42 then performs an exclusion process to exclude the influence of the inactive region 91(1) from the person detection frame 92(1). It then performs a position determination process to determine the position of the person from the person detection frame 92(1) that has been subjected to the exclusion process, according to a prescribed rule. The prescribed rule is, for example, a rule that the point closest to the coordinate origin of the captured image 90 indicating the installation position of the person detection device 3 is determined to be the position of the person. In FIG. 4, the point in the person detection frame 92(1) that is closest to the installation position of the person detection device 3, i.e., the above-mentioned XY coordinate origin, is determined to be the person identification position 96(1). As a result, the person identification position 96(1) is the same as the feet 94(1) of the person 98(1) (-20, 110).

Similarly, the position determination unit 42 determines that person 98(2) is a human and extracts person detection frame 92(2). In person detection frame 92(2), the position of head 93(2) is determined to be (200, -170), and the position of feet 94(2) is determined to be (60, -80).

The position determination unit 42 again determines the point closest to the installation position of the human detection device 3 as the person identification position 96(2) after eliminating the influence of the overlapping inactive area 91(2). As a result, the person identification position 96(2) becomes the same as the feet area 94(2) (60, -80).

The same is true for person 98(3). That is, after removing the influence of the overlapping inactive area 91(3) from person detection frame 92(3) and performing position determination processing, person identification position 96(3) becomes (0, 20).

In this manner, in the present disclosure, even if the detected person detection frame 92 overlaps with an inactive area 91 such as a desk or a wall, the influence of the inactive area 91 is eliminated and the position of the person is identified. By determining the position of the person after eliminating the influence of the inactive area 91, the position detection accuracy can be improved.

As described above, according to this embodiment, it is possible to provide a human detection device 3 that can improve the accuracy of detecting the position of a person.

Figure 5 is an example of camera information 43 provided in the human detection device 3 according to the first embodiment of the present disclosure. In Figure 5, the camera installation height (number no. 1 in Figure 5) indicates the height at which the camera unit 31 is installed. By specifying the camera installation height, it is possible to match the image captured by the camera unit 31 with the position determination range 97 (number no. 2), and it is possible to ensure the specified position determination range 97.

The installation position correction value (number no. 3) is a correction value that corrects the deviation between the imaging range of the human detection device 3 and the user-desired position determination range 97. For example, assume that the user sets the position determination range 97 to a range of 7.2 m x 7.2 m centered on the center of the room. In this case, it is desirable to install the human detection device 3 on the ceiling in the center of the room. However, in the case of a grid-type ceiling, air conditioning equipment, sprinklers, disaster prevention sensors, etc. are installed in the center, and the installation location of the human detection device 3 is often not in the center of the room. In that case, the human detection device 3 will be installed in a location close to the center.

The human detection device 3 can capture an image of a wide area of 16 m x 16 m using a wide-angle lens, so if the installation position is close to the center, it can cover the user-desired position determination range 97. However, as described above, the human detection device 3 displays the position of a person using XY coordinates with its own installation position as the coordinate origin (0.0), which results in a deviation from the center point of the user-desired position determination range 97. The installation position correction value (number no. 3) represents the correction value for this deviation.

By applying correction using the installation position correction value, the problem of the imaging range of the human detection device 3 not matching the desired position determination range 97 can be solved. This allows the entire imaging range to be subject to image processing.

The camera image size (number no. 4) is the standard resolution of the image data captured by the camera unit 31, and is, for example, SXGA (registered trademark) or VGA (registered trademark). The installation height of the camera of the human detection device 3 varies widely from 2.5 m to 5 m, and the number of pixels equivalent to φ30 cm, which corresponds to the human head that the human detection device 3 must detect, varies greatly depending on whether the device is installed at a location of 2.5 m or 5 m. By knowing the camera image size as camera information 43, it is possible to correct it to the optimal resolution.

The number of area divisions (number no. 5) is the number of areas when the position determination range 97, which is divided into 64 blocks, is consolidated in the human detection device 3. The number of area divisions can be set to any value between 1 and 4 using the infrared setting device 9. Based on this number of area divisions, the illuminance estimation unit 38 of the image processing unit 52 estimates the illuminance for each area. The tracking determination unit 45 also detects human movement for each area.

The human detection mask (number no. 6) is a range of the 64 8x8 blocks in the position determination range 97 in which human detection is not performed.

The illuminance estimation mask (number no. 7) is an area of the 64 8x8 blocks in the position determination range 97 where illuminance estimation is not performed.

Embodiment 2
6 is a block diagram showing an example of functions of the thermal human detection device 5 according to the second embodiment of the present disclosure. The camera unit 61 of the thermal human detection device 5 includes a thermopile element, which is a heat-sensitive element. The thermopile element receives electromagnetic waves emitted by a person in a wavelength range of 0.78 μm to 1 mm and converts the electromagnetic waves into temperature information.

Image data captured by the camera unit 61 is input to the image input unit 62 of the image processing unit 68 at a constant interval. The interval is, for example, 200 ms. This corresponds to a frame rate of 5 fps.

The image processing unit 68 is a part that detects people and body temperature from image data. The image input unit 62 receives image data input from the camera unit 61. The image input unit 62 transmits the received image data to the image generation unit 63. The image generation unit 63 converts the image data transmitted from the image input unit 62 into a thermal image showing a temperature distribution from about 0 degrees to about 100 degrees. The image generation unit 63 also manages reference image data 65 and latest image data 64. The reference image data 65 is updated when the environment is changed, such as when the layout of the room in which the thermal human detection device 5 is installed is changed.

The disturbance determination unit 66 performs disturbance determination based on the image data output from the image generation unit 63. The disturbance determination unit 66 considers the size and absolute temperature of the object depicted in the image data to determine whether or not the object is a disturbance. Furthermore, the disturbance determination unit 66 stores the image data after the disturbance determination has been completed in the non-volatile memory 76, together with a record of the characteristics of the object determined to be a disturbance, such as its position, size, and absolute temperature. By recording the characteristics of the object determined to be a disturbance in this way, it is possible to grasp in advance information about objects that generate heat during operation, such as personal computers. This makes it possible to prevent erroneous detections from occurring in the person detection performed later by the image processing unit 68.

The temperature estimation unit 67 reads from the non-volatile memory 76 data relating the reference image data 65 to absolute temperatures, and image data for which the disturbance determination unit 66 has completed disturbance determination, and corrects the temperature of the image data.

The human detection unit 69 is a part that detects humans and body temperature. The human detection unit 69 includes a human determination unit 70, a position determination unit 71, and an abnormal temperature determination unit 72. The human determination unit 70 extracts an area showing a temperature distribution of 30 to 40 degrees, close to human body temperature, from the image data (hereinafter referred to as the near-body temperature area), and determines whether or not it is a human, taking into account the size of the area. If it is determined to be a human, the human determination unit 70 detects the maximum temperature shown in the near-body temperature area as the body temperature. The position determination unit 71 determines the position of the person in the near-body temperature area according to a prescribed rule. The prescribed rule is, for example, a rule that the point closest to the point on the thermal image showing the installation position of the thermal human detection device 5 is determined to be the position of the person.

When an area showing a temperature distribution of 100°C or higher due to a fire or other cause is confirmed, the abnormal temperature determination unit 72 detects this as an abnormal temperature.

The number of people detection unit 75 counts points indicating the positions of people identified by the position determination unit 71, and calculates the number of people information in each area. The tracking determination unit 74 tracks changes in the positions of people identified by the position determination unit 71 for each sampling period, and determines the movement of people in each area, such as presence/absence, movement, stationary, etc.

In this way, in the image processing unit 68, the human detection unit 69 detects the position and body temperature of a person, the abnormal temperature judgment unit 72 detects abnormal temperatures, the number of people detection unit 75 detects the number of people, and the tracking judgment unit 74 detects human movement, including presence/absence and movement. Note that hereafter, the position information and body temperature information of people detected by the human detection unit 69, the abnormal temperature information detected by the abnormal temperature judgment unit 72, the number of people information detected by the number of people detection unit 75, and the information on human movement detected by the tracking judgment unit 74 are collectively referred to as heat-type human detection device detection information.

The communication circuit/power circuit 60, non-volatile memory 76, communication processing unit 77, beacon processing unit 78, wireless module 79, infrared communication unit 81, and light emitting/receiving element 80 of the thermal human detection device 5 have the same functions as those of the human detection device 3 in Figure 1, so their explanations are omitted.

As described above, the thermal human detection device 5 of the present disclosure detects human positions, body temperatures, abnormal temperatures, number of people, and human movements in the image processing unit 68 based on image data captured by the camera unit 61. In addition, the thermal human detection device detection information detected by the image processing unit 68 is notified to other devices. This makes it possible to utilize pinpointed human position information in the lighting control system 100, air conditioning control system 200, etc., described below.

As described above, according to this embodiment, it is possible to provide a thermal human detection device 5 that can improve the accuracy of detecting the position of a person.

<Example of use>
In the following, preferred use examples of the thermal human detection device 5 of the present disclosure will be described. As a first use example, by installing the thermal human detection device 5 of the present disclosure on a hospital bed, it is possible to monitor the patient's health information, such as body temperature and the state of turning over in bed. In addition, by notifying the health information to the cloud 24 described below, the cloud 24 can select a lighting environment suitable for the patient and perform lighting control to reflect this. In addition to the health information, the time, weather information, etc. may be taken into account when selecting the lighting environment.

In addition to the thermal human detection device 5, a vital sensor such as a 24 GHz band IQ demodulation Doppler radar can be installed to monitor the patient's vital information such as breathing and heart rate. In addition to the health information described above, the patient's vital information can also be managed in the cloud 24, and by matching it with information from the hospital's medical records, it is possible to provide services that are beneficial to the patient's treatment.

It is desirable for the vital sensor to be capable of detecting a person's biometric information, such as breathing and heart rate, and their location without contact. Furthermore, it is desirable for the sensor to be capable of simultaneously acquiring biometric information and location information of multiple people within an azimuth angle of ±45 degrees from the sensor, and within a range of 4 to 5 m from the sensor.

As a second use example, a fire can be detected by installing the thermal human detection device 5 of the present disclosure in a place where open flames are handled, such as a water heater room. By notifying the cloud 24 of abnormal temperature information, it becomes possible to link with disaster prevention equipment and guidance equipment, and it becomes possible to identify the location of the fire and grasp the evacuation situation. Furthermore, by notifying the cloud 24 of the human detection device detection information from the human detection device 3 in addition to the thermal human detection device 5, it is possible to grasp the situation during a fire even more efficiently.

Furthermore, as a third use example, by installing the thermal human detection device 5 of the present disclosure in a machine room, it is possible to simultaneously manage the health of workers and abnormal heat generation in equipment.

Figure 7 is a diagram summarizing the information detected by the human detection device 3, human sensor 4, and thermal human detection device 5 according to the first and second embodiments of the present disclosure. First, the human detection device 3 provides the above-mentioned human detection device detection information. That is, information on the position and movement of people (number no. 1 in Figure 7), the number of people in each set area (number no. 2), and the illuminance of each area (number no. 3) is provided.

Next, the above-mentioned heat-type human detection device detection information is obtained from the heat-type human detection device 5. That is, information on human position and movement (number no. 4), number of people in each set area (number no. 5), body temperature (number no. 6), and abnormal temperature (number no. 7) is obtained.

Note that since the human presence sensor 4 is a general sensor, an explanation of the human detection (number no. 8) information will be omitted.

Embodiment 3
8 is a diagram showing a configuration example of a lighting control system 100 according to a third embodiment of the present disclosure. The lighting control system 100 according to the present disclosure is installed in each building, such as a building, each room, etc. The lighting control system 100 includes two human detection devices 3. The lighting control system 100 further includes a human sensor 4 that detects a human using a pyroelectric element, a thermal human detection device 5, and a wall switch 8 for inputting a desired light source state to a lighting fixture 7. Information from these multiple devices is output to a lighting controller 1 via a communication line 2.

The human detection device 3, human sensor 4, thermal human detection device 5, and wall switch 8 input information to the lighting controller 1, so hereafter they will be collectively referred to as input devices.

The lighting controller 1 executes a process for selecting the light source state of the lighting fixture 7 based on information from the input device (hereinafter referred to as the light source state selection process). Furthermore, it transmits a control command to the terminal device 6 via the communication line 2 so that the light source state is realized. The lighting controller 1 also performs a process for transmitting information of the system device 12 (described later) to the lighting monitoring system 11. The control command is a command for controlling the light source state such as ON/OFF, dimming rate, and color temperature of the lighting fixture 7.

The terminal device 6 changes the light source state of the lighting fixture 7 based on the control command. The lighting fixture 7 is equipped with a light source such as an LED or a white light source. The terminal device 6 and the lighting fixture 7 are connected by either a dimming signal line or digital communication.

Here, the terminal device 6 and the lighting fixture 7 change the light source state based on the control command output from the lighting controller 1, so these will be referred to as output devices hereafter. Furthermore, the configuration combining the above-mentioned input devices and output devices will be referred to as system device 12.

The system device 12 further includes an infrared setting device 9 and a portable terminal device 10. The infrared setting device 9 is, for example, a remote control. The portable terminal device 10 is, for example, a smartphone. The infrared setting device 9 and the portable terminal device 10 are remote control devices that monitor and operate the status of the human detection device 3, the human sensor 4, the thermal human detection device 5, and other system devices 12 based on operating information, error information, etc.

The infrared setting device 9 and the mobile terminal device 10 also remotely operate the wall switch 8, and change the light source state of the lighting fixture 7 via the wall switch 8. Furthermore, by remotely operating the wall switch 8, it is possible to operate the lighting controller 1 connected to the wall switch 8 via the communication line 2 and monitor the operation information. The operation information is, for example, the group information, pattern information, demand information, linkage information, etc. of the lighting controller 1.

The lighting monitoring system 11 centrally manages the operational information of the system equipment 12 input from the lighting controller 1 via the LAN.

As described above, in the lighting control system 100 disclosed herein, the lighting controller 1 selects the light source state of the lighting fixture 7 based on information from input devices including the human detection device 3. In this case, by utilizing pinpoint information on the position of a person contained in the human detection device detection information, it becomes possible to select a more suitable light source state.

For example, based on a person's location information, energy-saving control can be implemented, such as turning on the lights at that location at a dimming rate of 70% if the person is present, turning them off if the person is absent, and turning them on at a dimming rate of 5% if the person is moving.

As described above, according to this embodiment, it is possible to provide a lighting control system 100 that can improve the accuracy of detecting a person's position and realize a suitable lighting environment according to the detected position information.

<Modification>
8 has been described as a case in which the lighting control system 100 includes two human detection devices 3. However, the number of human detection devices 3 may be determined depending on the usage environment of the lighting control system 100. The same applies to other input devices.

Fourth embodiment
9 is a configuration diagram of an integrated management system 300 according to the fourth embodiment of the present disclosure. The integrated management system 300 includes a cloud computing system (hereinafter, cloud) 24, a server 25, and a group management system 26.

The cloud 24 is a server in an Internet environment that stores data notified from the lighting control systems 100(1), 100(2), ... that are installed in multiple buildings or rooms, and is also called a cloud server. The data in each lighting control system 100 is notified to the cloud 24 from each lighting monitoring system 11 via a VPN (Virtual Private Network) 27.

Furthermore, if an air conditioning control system 200 is also installed in addition to the above-mentioned lighting control system 100, the cloud 24 also stores data notified from the air conditioning control system 200. For example, in FIG. 9, a lighting control system 100(1) and an air conditioning control system 200 are installed in the same building. Data from the air conditioning control system 200 is input to the cloud 24 from the air conditioning monitoring system 20 via the VPN 27.

The data notified to the cloud 24 from the lighting control system 100 and the air conditioning control system 200 includes the human detection device detection information described above.

Based on the human detection device detection information notified to the cloud 24, the server 25 selects suitable lighting conditions or air conditioning conditions for the lighting control system 100 or air conditioning control system 200 that notified the human detection device detection information.

If the person detection device detection information has been notified by the lighting control system 100, the server 25 executes a process of selecting a suitable light source state for the lighting device 7 from the learning data (hereinafter referred to as the learned light source state selection process).

On the other hand, if the human detection device detection information has been notified by the air conditioning control system 200, the server 25 executes a process of selecting suitable operating states for the indoor unit 22 and the outdoor unit 21 from the learning data (hereinafter referred to as the learned operating state selection process).

Here, the learning data is data obtained by a learning process in which the server 25 performs data analysis or machine learning to learn lighting conditions or air conditioning conditions suitable for the human detection device detection information.

The group management system 26 is a system that centrally manages information on multiple lighting control systems 100 and information on air conditioning control systems 200 stored in the cloud 24.

Here, the air conditioning control system 200 includes a human detection device 3 and a thermal human detection device 5. It also includes an air conditioning monitoring system 20, an outdoor unit 21, an indoor unit 22, and a remote control 23 for inputting the desired air conditioning operation state to the indoor unit 22.

The air conditioning monitoring system 20 executes a process (hereinafter referred to as an air conditioning state selection process) for selecting the operating state of the indoor unit 22 and the outdoor unit 21 based on the information notified from the input device. Furthermore, the air conditioning monitoring system 20 controls the indoor unit 22 and the outdoor unit 21 based on the result of the air conditioning state selection process.

As described above, the integrated management system 300 of the present disclosure stores data of multiple lighting control systems 100 and data of air conditioning control systems 200 in the cloud 24. The data stored in the cloud 24 is centrally managed by the group management system 26 and used for energy conservation and environmental improvement.

<Modification>
9, it has been described that data in each lighting control system 100 is notified to the cloud 24 via the lighting monitoring system 11 and the lighting controller 1. However, each device included in the system device 12 may be directly connected to the cloud 24 via a VPN 27, without going through the lighting monitoring system 11 and the lighting controller 1. For example, information from the human detection device 3 may be notified directly to the cloud 24. This also applies to the following embodiments.

The connection to the cloud 24 via the VPN 27 may be wired or wireless. This also applies to the following embodiments.

In addition to the lighting control system 100 and air conditioning control system 200 described above, the cloud 24 and server 25 may also be connected to the security system, disaster prevention system, and power monitoring system in each building. By connecting to various systems and sharing information, the group management system 26 can achieve further energy savings and environmental improvement.

In addition, in FIG. 9, it has been described that the server 25 and the group management system 26 are installed outside the cloud 24. However, the functions of the server 25 and the group management system 26 may be executed within the cloud 24. This will further improve safety and convenience. Conversely, the server 25 may receive and store data of the lighting control system 100 and the air conditioning control system 200 without using the cloud 24.

In the above, it has been described that the server 25 performs the learning process, the learned light source state selection process, and the air conditioning state selection process based on the human detection device detection information from the human detection device 3. However, the same effect can be obtained by using the thermal human detection device detection information detected by the thermal human detection device 5. This also applies to all of the following embodiments.

Figure 10 is a flowchart showing communication specifications for linking human detection device detection information detected by the human detection device 3 to the cloud in the integrated management system 300 of the present disclosure. Here, it is assumed that multiple human detection devices 3 are provided. When the first human detection device, human detection device 3 (1), detects a person, it transmits a human detection notification including the human detection device detection information to the lighting controller 1 (step S01). Note that in step S01, the MAC address is added to the human detection notification signal as identification information of the human detection device 3 (1). Furthermore, the human detection device detection information here is information indicating the presence of a person, as well as information on the position, number, and illuminance of the people.

Next, the lighting controller 1 transmits the received human detection notification to the lighting monitoring system 11 (step S02). Next, the lighting monitoring system 11 transmits the received human detection notification to the server 25 connected to the cloud 24 (step S03). The human detection device detection information included in the human detection notification received by the server 25 is stored in the database 95 held by the cloud 24.

Meanwhile, the lighting controller 1 that received the human detection notification in step S01 transmits a control command to the terminal device 6 responsible for the relevant area based on the position information of the person detected by the human detection device 3 (1) (step S04). The control command here is to turn on the light source state of the lighting fixture 7 and specify the dimming rate and color temperature. In this way, the lighting controller 1 can implement control to change the lighting fixture 7 to the ON state based on the position information of the person from the human detection notification.

The lighting controller 1 further transmits a change notification to the lighting monitoring system 11, notifying it that the light source state of the lighting fixture 7 will be changed (step S05). Next, the lighting monitoring system 11 transmits the received change notification to the server 25 (step S06). The information contained in the change notification received by the server 25 is stored in the database 95.

When the human detection device 3(1) detects a human within the imaging range, it transmits the above-mentioned beacon signal (hereinafter referred to as the first wireless signal) to which its own MAC address and information indicating that this is the first notification are added to the mobile terminal device 10 and the human detection device 3(2), which is the second human detection device (step S07). The mobile terminal device 10 that receives the first wireless signal stores the MAC address of the human detection device 3(1), the human detection device detection information, and the reception level indicating the strength of the radio waves.

Meanwhile, the human detection device 3 (2) that received the first wireless signal transmits a beacon signal (hereinafter referred to as the second wireless signal) to the mobile terminal 10, which includes its own MAC address and information indicating that this is the second notification (step S08). In this manner, the present disclosure incorporates a mechanism in which devices other than the human detection device 3 that transmitted the first wireless signal transmit second wireless signals. The mobile terminal 10 that received the second wireless signal stores the MAC address of the human detection device 3 (2), the human detection device detection information, and the reception level.

The mobile terminal 10 executes a process (hereinafter referred to as the identification process) to identify the position of the person detected by the human detection device 3(1) and the human detection device 3(2) using a three-point positioning method based on the reception levels of the first wireless signal and the second wireless signal. If it is determined from the position of the person identified by the identification process that the person is the owner of the mobile terminal 10, the mobile terminal 10 notifies the server 25 of personal information related to the person (step S09). Note that when notifying the personal information in step S09, the MAC address information of the human detection device 3(1) and the human detection device 3(2) (hereinafter referred to as device identification information) is also notified at the same time.

The server 25 stores the personal information and device identification information notified from the mobile terminal 10 in the database 95 of the cloud 24. As a result, in the above-mentioned learning process performed by the server 25, lighting conditions suitable for the human detection device detection information can be linked to the personal information and learned into the learning data.

The server 25 then notifies the lighting monitoring system 11 of the personal information and device identification information notified from the mobile terminal 10, and the human detection device detection information acquired in step S03 (step S10). The lighting monitoring system 11 displays the received information on the monitoring screen.

Note that steps S11 to S20 are a flowchart for the case where human detection device 3(2) detects a person first. This is similar to the case where human detection device 3(1) detects a person first described above, so a detailed explanation is omitted.

As described above, in the integrated management system 300 disclosed herein, the mobile terminal device 10 transmits personal information of the detected person based on the first and second wireless signals transmitted from the human detection device 3. The server 25 that receives the personal information stores the personal information together with the human detection device detection information, and performs a learning process that utilizes the personal information.

<Modification>
10 has been described as a method for acquiring personal information from the mobile terminal 10 using the first wireless signal and the second wireless signal. However, the same effect can be obtained by linking the MAC address information of the human detection device 3 with the individual information in the cloud 24. Therefore, the wireless module 49 does not need to be used.

In FIG. 10, it has been described that the server 25 performs the learning process. Using the results of the learning process, after step S10 or step S20, a learned light source state selection process may be performed, and an instruction may be issued to the lighting monitoring system 11 or the lighting controller 1 to change the lighting state.

Figure 11 is a diagram showing communication specifications for linking the lighting control system 100 and the air conditioning control system 200 to the server 25 in the integrated management system 300 of the present disclosure. First, a security unlocking notification is sent to the lighting monitoring system 11 (step S50). Here, the security unlocking notification is, for example, a notification indicating that a person has unlocked the security system and entered the building, and is sent by the security system.

Next, the lighting monitoring system 11 transmits a control signal to the lighting controller 1 to realize scene 1 (step S51). Here, scene 1 is, for example, a state in which the dimming rate of the lighting fixture 7 is 5%.

The lighting controller 1 transmits a control command for a dimming rate of 5% and a color temperature of 6000K to the pre-specified terminal device 6 in accordance with the control signal for scene 1 (step S52). Furthermore, the lighting monitoring system 11 controls the air conditioning monitoring system 20 to start operation under pre-specified operating conditions (step S53). The operating conditions are, for example, a room temperature of 27°C, weak airflow, and weak ventilation.

The air conditioning monitoring system 20 controls the operation of the outdoor unit 21 and the indoor unit 22 based on the operating conditions notified by the lighting monitoring system 11 (step S54).

As explained in FIG. 10, when the human detection device 3(1) detects a person, it transmits a human detection notification including human detection device detection information to the lighting controller 1 (step S55). The MAC address of the human detection device 3(1) is added to the human detection notification signal. The human detection device detection information here is information indicating the presence of a person, their location, and the number of people.

Next, the lighting controller 1 transmits the received human detection notification to the lighting monitoring system 11 (step S56). Next, the lighting monitoring system 11 transmits the received human detection notification to the server 25 connected to the cloud 24 (step S57). The human detection device detection information included in the human detection notification received by the server 25 is stored in the database 95 held by the cloud 24.

Meanwhile, the lighting controller 1 that received the human detection notification in step S55 transmits a control command to the terminal device 6 responsible for the relevant area based on the position information of the person detected by the human detection device 3 (step S58). The control command here specifies that the light source state of the lighting fixture 7 is ON, the dimming rate is 100%, and the color temperature is 6000K. In this way, when a person is detected in a room in which the human detection device 3 is installed, the dimming rate of the lighting fixture 7 in that room can be controlled to increase from 5% to 100%.

The lighting controller 1 further transmits a change notification to the lighting monitoring system 11 to notify it that the light source state of the lighting fixture 7 will be changed (step S59). Next, the lighting monitoring system 11 transmits the received change notification to the server 25 (step S60). The information contained in the change notification received by the server 25 is stored in the database 95.

Next, the server 25 selects suitable operating states for the indoor unit 22 and the outdoor unit 21 from the learning data based on the human detection device detection information and weather information acquired in step S57. That is, it executes a learned operating state selection process. Furthermore, it transmits the selected operating state to the air conditioning monitoring system 20 (step S61). The selected operating state is, for example, a room temperature of 28°C, strong airflow, and strong ventilation.

The air conditioning monitoring system 20 controls the operation of the outdoor unit 21 and the indoor unit 22 based on the operating status notified by the server 25 (step S62).

As described above, in the integrated management system 300 disclosed herein, the lighting monitoring system 11 and the air conditioning monitoring system 20 are connected to the server 25. This allows the server 25 to select an operating state suitable for the human detection device detection information and perform air conditioning control.

As described above, this embodiment makes it possible to provide an air conditioning control system that can improve the accuracy of detecting a person's position and realize an optimal air conditioning environment according to the detected position information.

Furthermore, according to this embodiment, it is possible to provide an integrated management system that can improve the accuracy of detecting a person's position and realize an optimal lighting environment according to the detected position information.

Fifth embodiment
12 is a diagram showing an example of the configuration of a lighting control system 400 according to a fifth embodiment of the present disclosure. The lighting control system 400 is similar to the lighting control system 100, but the human detection device 3 and the thermal type human detection device 5 are connected to the lighting monitoring system 11 via a POE (Power Over Ethernet, registered trademark)-HUB 13 that can supply power, rather than via a communication line 2. This allows the human detection device 3 and the thermal type human detection device 5 to communicate with the lighting monitoring system 11 via LAN.

By transmitting the image data acquired by the human detection device 3 and the thermal human detection device 5 to the lighting monitoring system 11 via LAN communication, it becomes possible to monitor the image data in the lighting monitoring system 11, and a security function can be added to the lighting monitoring system 11.

Note that the communication sequence for the human detection notification from the human detection device 3 to the lighting monitoring system 11 is different from that in FIG. 11, but the function is the same, so it will not be described here. The same applies to the thermal human detection device 5.

Figure 13 is a diagram showing how the lighting monitoring system 11 identifies the position of the human detection device 3 in the lighting control system 400 according to embodiment 5 of the present disclosure. The monitoring screen of the lighting monitoring system 11 displays a floor layout diagram as shown in Figure 13. Icons of various devices included in the system device 12 are also displayed there, and their operating status can be monitored and operated.

The following describes a method in which the lighting monitoring system 11 identifies the installation positions of multiple human detection devices 3 and arranges icons of the human detection devices 3 on the layout diagram described above. However, in this example, it is assumed that eight human detection devices 3(1), 3(2), ... 3(8) are installed on the ceiling of a room to capture an image of a position determination range 97 of 7.2 m x 7.2 m. It is preferable that these eight human detection devices 3 are installed so that their position determination ranges 97 do not overlap. In addition, it is assumed that the captured image 90 of each human detection device 3 is 16 m x 16 m, and the position determination range 97 is a range of 7.2 m x 7.2 m within the captured image 90.

First, the lighting monitoring system 11 switches all human detection devices 3 to placement mode. Next, information on the absolute coordinates of the installation position is received from the human detection device 3(1) (hereinafter referred to as the identified human detection device) whose absolute coordinates of the installation position are known. The absolute coordinates of the installation position are displayed in two-dimensional coordinates with a specified starting point as the origin. For example, if the absolute coordinates of the human detection device 3(1) with respect to the starting point of the entrance to a room are (0,380), this means that the human detection device 3(1) is installed at a position 380 cm directly below the entrance.

Furthermore, a person 98 who has entered the room moves through the entrance and is detected by the identified person detection device 3(1). The lighting monitoring system 11 collects the person specific position 96(1) of the person detected by the identified person detection device 3(1). At this time, it is assumed that the person specific position 96(1) is (-680, -80). Note that hereafter, the person specific position 96(1) of the person detected by the identified person detection device 3(1) will be referred to as the first position information.

Furthermore, when the person is present at the position indicated by the first position information, the lighting monitoring system 11 searches for the person detection device 3 that detected the person among the person detection devices 3(2), ... person detection devices 3(8) whose absolute coordinates of the installation positions are unknown, and identifies it as an unidentified person detection device. In FIG. 13, person 98 passes between identified person detection device 3(1) and person detection device 3(3). Therefore, as a result of the search, unidentified person detection device 3(3) is identified.

Next, when the person is present at the position indicated by the first position information, the person-specific position 96(3) of the person detected by the unidentified person detection device 3(3) is accepted. Here, it is assumed that the person-specific position 96(3) in the person detection device 3(3) is (740, -80). Hereinafter, the person-specific position 96(3) of the person detected by the unidentified person detection device 3(3) is referred to as the second position information.

Furthermore, the lighting monitoring system 11 determines the absolute coordinates of the installation location of the unidentified person detection device 3(3) from the first position information and the second position information. As a result, the location of the unidentified person detection device 3(3) is determined to be 420 cm to the left of the identified person detection device 3(1). Accordingly, the lighting monitoring system 11 changes the unidentified person detection device 3(3) to the identified person detection device 3(1).

As for the other person detection device 3, the absolute coordinates of the installation position are sequentially identified based on the information of the person specific position 96 when the person 98 moves along the movement route 99.

The lighting monitoring system 11 automatically places an icon of the human detection device 3 on the layout drawing based on the information on the absolute coordinates of the identified installation position of the human detection device 3, and then ends the placement mode.

In this way, the lighting monitoring system 11 of the present disclosure has a function for automatically identifying the placement of each human detection device 3. This allows the lighting monitoring system 11 to collectively manage the information of multiple human detection devices 3 and check the captured images 90. In addition, when the user sets the position determination range 97, the user can set it without gaps or overlaps while checking the layout diagram.

<Modification>
13, the lighting monitoring system 11 automatically identifies the location of each human detection device 3 and places icons of the human detection devices 3 on the monitoring screen. However, this is not limited to the lighting monitoring system 11, and may be performed in any monitoring system. This allows any monitoring system to be provided with a security function.

In the above explanation, the position determination range 97 is 7.2 m x 7.2 m, but the lighting monitoring system 11 may be operated so that the range can be arbitrarily switched to 6.4 m x 6.4 m or 9 m x 9 m, etc.

As described above, according to this embodiment, it is possible to provide a surveillance system equipped with a human detection device that can improve the accuracy of detecting the position of a person.

1 Lighting controller, 2 Communication line, 3 Human detection device, 4 Human sensor, 5 Thermal human detection device, 6 Terminal device, 7 Lighting fixture, 8 Wall switch, 9 Infrared setting device, 10 Portable terminal device, 11 Lighting monitoring system, 12 System equipment, 13 POE-HUB, 20 Air conditioning monitoring system, 21 Outdoor unit, 22 Indoor unit, 23 Remote control, 24 Cloud, 25 Server, 26 Group management system, 27 VPN, 30 Communication circuit/power circuit, 31 Camera unit, 32 Image input unit, 33 Image generation unit, 34 Disturbance determination unit, 35 Old image data, 36 Latest image data, 37 Same image determination unit, 38 Illuminance estimation unit, 39 Slight movement detection unit, 40 Still area determination unit, 41 Movement detection unit, 42 Position determination unit, 43 Camera information, 44 Number of people detection unit, 45 Tracking determination unit, 46 non-volatile memory, 47 communication processing unit, 48 beacon processing unit, 49 wireless module, 50 infrared communication unit, 51 light emitting/receiving element, 52 image processing unit, 60 communication circuit/power supply circuit, 61 camera unit, 62 image input unit, 63 image generation unit, 64 latest image data, 65 reference image data, 66 disturbance determination unit, 67 temperature estimation unit, 68 image processing unit, 69 person detection unit, 70 person determination unit, 71 position determination unit, 72 abnormal temperature determination unit, 73 camera information, 74 tracking determination unit, 75 number of people detection unit, 76 non-volatile memory, 77 communication processing unit, 78 beacon processing unit, 79 wireless module, 80 light emitting/receiving element, 81 infrared communication unit, 90 captured image, 91 inactive area, 92 person detection frame, 93 head, 94 foot area, 95 database, 96 Person identification position, 97 Position determination range, 98 Person, 99 Movement route, 100 Lighting control system, 200 Air conditioning control system, 300 Integrated management system, 400 Lighting control system

Claims (12)

A process of capturing an image of the space at regular intervals;
A process of extracting structures having linear features captured in the image as inactive regions;
A process of detecting a person in the image as a frame;
an exclusion process for excluding the influence of the inactive region from the frame;
a position determination process for determining a position of a person from the frame after the exclusion process according to a predetermined rule;
A human detection device configured to perform the following: The human detection device according to claim 1 ;
A lighting controller;
Lighting equipment and
Equipped with
The lighting controller includes:
a light source state selection process for selecting a light source state of the lighting device based on position information of a person notified from the human detection device;
A process of controlling the lighting device so as to realize the light source state;
A lighting control system configured to: The human detection device according to claim 1 ;
An indoor unit,
The outdoor unit,
Air conditioning monitoring system;
Equipped with
The air conditioning monitoring system includes:
an air conditioning state selection process for selecting an operating state of the indoor unit and the outdoor unit based on position information of a person notified from the human detection device;
A process of controlling the indoor unit and the outdoor unit so as to realize the operating state;
An air conditioning control system configured to: An integrated management system for managing the lighting control system according to claim 2,
A process of receiving position information of a person detected by the person detection device in a server;
a learned light source state selection process for selecting a light source state of a lighting device included in the lighting control system from learning data based on the position information;
A process of changing a light source state of the lighting device provided in the lighting control system based on a result of the learned light source state selection process;
a learning process for learning a light source state of the lighting device suitable for the location information into the learning data;
23. An integrated management system configured to: The integrated management system according to claim 4, wherein the server is a cloud server. The integrated management system further manages the air conditioning control system according to claim 3,
a learned operating state selection process for selecting operating states of an indoor unit and an outdoor unit included in the air conditioning control system from the learning data according to the position information;
A process of changing the operating states of the indoor units and the outdoor units included in the air conditioning control system based on a result of the learned operating state selection process;
Further execute
The integrated management system according to claim 4 , wherein the learning process further includes a process of causing the learning data to learn operating conditions of the indoor unit and the outdoor unit suitable for the position information. A plurality of the human detection devices are provided,
The system further comprises a mobile terminal device in which personal information of the owner is stored,
a first human detection device included in the human detection devices further performs a process of transmitting a first wireless signal including position information of the detected human and identification information indicating the first human detection device;
A second human detection device included in the human detection device other than the first human detection device,
receiving the first wireless signal;
a process of transmitting a second wireless signal, when the first wireless signal is received, the second wireless signal including position information of the detected person and identification information indicating the second human detection device;
Further execute
The mobile terminal device includes:
receiving the first wireless signal and the second wireless signal;
an identification process for identifying a position of the person detected by the first human detection device from the first wireless signal and the second wireless signal;
A process of determining whether or not a person identified by the identification process is the owner based on the position of the person;
If it is determined that the person is the owner, transmitting the personal information to the server;
Run
The integrated management system according to claim 4 , wherein in the learning process, the server causes a light source state of the lighting device suitable for the location information to be learned as the learning data by linking the light source state to the personal information. A thermal human detection device that detects a temperature distribution in a space and displays the temperature distribution as a thermal image,
The thermal type human detection device is
A process of generating the thermal image at regular intervals;
A process of extracting a near body temperature region showing a temperature distribution of 30 degrees to 40 degrees from the thermal image;
A process of determining whether the near-body temperature region is a human;
is configured to run
If it is determined that the near body temperature region is a human,
A process of detecting a maximum temperature indicated by the near body temperature region as a human body temperature;
determining the location of the person from said near-body temperature region according to a predefined rule;
The thermal-based human detection device is further configured to perform the following: In the light source state selection process, the lighting controller
The lighting control system according to claim 2 , further comprising a process for selecting a light source state of the lighting fixture based on position information of a person notified from the thermal type human detection device according to claim 8 . The method further comprises the steps of: receiving, in the server, location information of a person detected by the thermal type human detection device according to claim 8;
The learning process further includes a process of learning a light source state of the lighting device suitable for position information of a person detected by the thermal type human detection device into the learning data,
The learned light source state selection process further includes a process of selecting a light source state of the lighting device provided in the lighting control system from the learned data based on position information of a person detected by the thermal human detection device.
The integrated management system according to claim 4. A plurality of the human detection devices according to claim 1 are provided,
A process of receiving information on absolute coordinates of an installation position from an identified human detection device, the absolute coordinates of which are known, the human detection device being included in the human detection device;
A process of receiving first position information of a person detected by the identified person detection device;
a process of identifying, among the person detection devices whose absolute coordinates of installation positions are unknown, a device that detects a person present at the position indicated by the first position information as an unidentified person detection device;
receiving second location information of the person detected by the unidentified person detection device when the person is present at the location indicated by the first location information;
A process of identifying absolute coordinates of an installation location of the unidentified person detection device from the first position information and the second position information, and setting the unidentified person detection device as an identified person detection device;
is configured to run
A monitoring system that places an icon indicating the position of the identified person detection device on a monitoring screen. In the position determination process, the predetermined rule is:
The human detection device according to claim 1 , wherein the rule is that a point in the frame after the exclusion process that is closest to a point on the image that indicates an installation position of the human detection device is set as the position of the human.

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