Control device, program, and toilet monitoring system

Abstract

The present invention provides a control device, program, and toilet monitoring system that can detect falls in toilets while protecting privacy and suppressing false positives. [Solution] A control device 20 receives a lock signal from a lock detection device 35 that detects the locking of toilet stall 2, a seating signal from a seating detection device 45 that detects someone sitting on the toilet seat 41 inside stall 2, and point cloud data output from a LiDAR device 10 that detects the state inside stall 2. The control device outputs a predetermined signal when a lock signal is input, a seating signal is not input, and a person has fallen from the point cloud data.

Description

Technical Field

[0001] The present invention relates to a control device, a program, and a toilet monitoring system.

Background Art

[0002] During the use of a toilet, a user may collapse due to a sudden illness or the like. In such a case, since the toilet cubicle is locked, there is a concern that the notification may be delayed. Therefore, there is a need for a toilet monitoring system that monitors the user's fall in the toilet.

[0003] The following Patent Document 1 describes a monitoring system that detects the fall of a user in such a toilet. In the monitoring system of Patent Document 1, based on the detection result of a floor sensor arranged on the floor for detecting the presence or absence of a load, the state of the user in the toilet is monitored, and when pressure is detected over a wide range of the floor sensor, it is determined as an abnormal state where a person has fallen.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In the monitoring system of Patent Document 1, as described above, based on the load on the floor, the fall of a person or the like is detected. Therefore, when an object is placed on the floor, there is a possibility of false detection that a person has fallen. In addition, a toilet cubicle is often a space where privacy should be protected, and it is necessary to consider the protection of privacy.

[0006] Therefore, an object of the present invention is to provide a control device, a program, and a toilet monitoring system that can detect the fall of a person in a toilet while protecting privacy and suppressing false detection. [Means for solving the problem]

[0007] To achieve the above objective, the present invention provides a control device that receives a lock signal from a lock detection device that detects the locking of a toilet stall, a seating signal from a seating detection device that detects someone sitting on the toilet seat inside the stall, and point cloud data output from a LiDAR (Light Detection And Ranging) device that detects the state inside the stall, and is characterized in that it outputs a predetermined signal when the lock signal is input, the seating signal is not input, and a person has fallen from the point cloud data.

[0008] Furthermore, the present invention relates to a program executed by a control device that receives a locking signal from a lock detection device for detecting the locking of a toilet stall, a seating signal from a seating detection device for detecting someone sitting on a toilet seat inside the stall, and point cloud data output from a LiDAR device for detecting the state inside the stall, the program comprising the steps of: determining whether or not the locking signal is input to the control device; determining whether or not the seating signal is input to the control device; detecting a person falling using the point cloud data; and outputting a predetermined signal when the locking signal is input, the seating signal is not input, and a person falling is detected from the point cloud data.

[0009] Furthermore, the present invention relates to a toilet monitoring system comprising: a lock detection device for detecting the locking of a toilet stall; a seat detection device for detecting someone sitting on the toilet seat inside the stall; a LiDAR device for detecting the state of the stall; and a control device that receives a lock signal from the lock detection device, a seat signal from the seat detection device, and point cloud data from the LiDAR device, wherein the control device outputs a predetermined signal when it receives the lock signal, does not receive the seat signal, and detects a person falling from the point cloud data.

[0010] Point cloud data output from a LiDAR device can identify human movement and objects, but it cannot identify individuals. Therefore, detecting the state of a private room using a LiDAR device can protect the privacy of those inside the room. Furthermore, detecting falls from the point cloud data input from the LiDAR device can suppress false detections of a person falling when luggage is placed on the floor, as described above. Also, even if a person inside a private room performs an action that is falsely detected as a fall by the control device, it is not a fall if they remain seated. Therefore, detecting a fall from the point cloud data when there is no seating signal can suppress false detections. In this way, when a person falls is detected, the control device can output a predetermined signal, causing other devices to take action indicating that a person has fallen.

[0011] Furthermore, it is preferable that the control device assumes a person has fallen if it does not detect any dynamic objects located in a region higher than the toilet seat from the point cloud data.

[0012] When a person falls, they generally fall to a position lower than the toilet seat. Unlike cameras, LiDAR devices can measure the distance to an object, and therefore can accurately measure the height of an object. By using point cloud data from a LiDAR device, if no dynamic objects located in the area higher than the toilet seat are detected, it is possible to appropriately detect a person falling.

[0013] Furthermore, it is preferable that the control device does not detect objects located above the toilet seat in the point cloud data and in the region that overlaps with the toilet seat in the vertical direction.

[0014] In this case, the upper body of a seated person may not be detected from the point cloud data, thus better protecting the privacy of the seated person.

[0015] Preferably, the point cloud data does not include information about objects located above the toilet seat and overlapping with the toilet seat in the vertical direction.

[0016] In this case, the point cloud data may largely not contain information indicating the seated individuals, thus better protecting their privacy. [Effects of the Invention]

[0017] As described above, the present invention provides a control device, a program, and a toilet monitoring system that can detect a person falling in a toilet while protecting privacy and suppressing false detections. [Brief explanation of the drawing]

[0018] [Figure 1] Figure 1 is a schematic diagram showing a toilet monitoring system according to an embodiment of the present invention. [Figure 2] Figure 2 is a conceptual diagram showing a LiDAR device, etc. [Figure 3] Figure 3 is a flowchart showing the operation of the control device in the embodiment. [Modes for carrying out the invention]

[0019] Preferred embodiments of the control device, program, and toilet monitoring system according to the present invention will be described in detail below with reference to the drawings. The embodiments illustrated below are for the purpose of facilitating understanding of the present invention and are not intended to limit the interpretation of the present invention. The present invention can be modified and improved within the scope of the claims without departing from its spirit. Furthermore, the components of the embodiments illustrated below may be combined as appropriate. Note that in the drawings referenced below, the dimensions of each component may be shown differently for the purpose of facilitating understanding. Also, in the drawings, for the sake of readability, reference numerals may be assigned to only some of the similar components, and some reference numerals may be omitted.

[0020] Fig. 1 is a schematic diagram showing a toilet monitoring system according to the present embodiment. The private room 2 is a toilet private room. Therefore, the private room 2 mainly includes a door 30 and a toilet 40. Further, the toilet monitoring system 1 of the present embodiment mainly includes a LiDAR device 10, a control device 20, a memory 25, a locking detection device 35, a sitting detection device 45, and a voice output device 50. In Fig. 1, the state where the person M has fallen is shown by a solid line, and the state where the person is sitting is shown by a broken line.

[0021] A key 31 is provided on the door 30, and the locking detection device 35 detects that the door is locked by the key 31. The locking detection device 35 is, for example, mechanically connected to a lever or the like of the key 31, and detects the locking by the key 31 based on the position of the lever or the like. Alternatively, the locking detection device 35 is non-contact with the key 31, and may detect the state of the key 31 optically or magnetically to detect the locking by the key 31. The configuration for the locking detection device 35 to detect that the door is locked is not limited to these examples. When the locking detection device 35 detects that the door is locked, it outputs a locking signal indicating the locked state. The locking signal may be, for example, any signal that can distinguish between a state where the door is not locked by the key 31 and a state where the door is locked by the key 31. Therefore, for example, the locking detection device 35 outputs a Lo signal when the door is not locked, and outputs a Hi signal when the door is locked. In this case, the Hi signal is the locking signal. Also, for example, the locking detection device 35 does not output a signal when the door is not locked, and outputs a predetermined signal when the door is locked. In this case, the predetermined signal is the locking signal.

[0022] The locking detection device 35 is connected to the control device 20 so that a signal can be input thereto, and the locking signal is input to the control device 20. In this specification, when it is said that a device is connected so that a signal can be input, it includes cases where the device that outputs the signal and the device that receives the signal are electrically connected or wirelessly connected.

[0023] The toilet 40 is provided with a toilet seat 41, a toilet lid 42, and a seating detection device 45. With the toilet lid 42 open and the toilet seat 41 positioned on the toilet 40, person M sits on the toilet seat 41. The seating detection device 45 detects that person M is sitting on the toilet seat 41. The seating detection device 45 may be a load detection type that detects the load applied to the toilet seat 41 to detect the seating of person M, or an infrared detection type that detects the seating of person M by infrared rays. The configuration in which the seating detection device 45 detects seating is not limited to these examples.

[0024] When the seating detection device 45 detects that person M is sitting on the toilet seat 41, it outputs a seating signal indicating the seated state. The seating signal may be, for example, any signal that can distinguish between the state where person M is not sitting and the state where person M is sitting. Therefore, for example, the seating detection device 45 outputs a Lo signal when person M is not sitting and a Hi signal when person M is sitting. In this case, the Hi signal is the seating signal. Also, for example, the seating detection device 45 does not output a signal when person M is not sitting and outputs a predetermined signal when person M is sitting. In this case, the predetermined signal is the seating signal. The seating detection device 45 is connected to the control device 20 so that a signal can be input thereto, and the seating signal is input to the control device 20.

[0025] The voice output device 50 is connected to the control device so that a signal can be input thereto. The voice output device 50 outputs voice according to the signal input from the control device 20.

[0026] Next, the LiDAR device 10 will be described.

[0027] The LiDAR device 10 detects the state inside the private room 2, and detects objects within the monitoring area MA inside the private room 2 of the LiDAR device 10, and outputs point cloud data showing the state of the monitoring area MA. Through this detection, the LiDAR device 10 can detect objects related to the facility, such as walls and toilets 40, as well as people M. In this embodiment, the monitoring area MA is an area higher than the toilet seat 41 and includes a first area MA1 that does not overlap with the toilet seat 41 in the vertical direction, a second area MA2 that is located above the toilet seat 41 and overlaps with the toilet seat 41 in the vertical direction, and a third area MA3 that is lower than the toilet seat 41.

[0028] The first region MA1 is where the upper body of person M is located when person M is not seated. Therefore, when person M is not seated, a dynamic object is located in the first region MA1. The second region MA2 is where the upper body of person M is located when person M is seated. Therefore, when person M is seated, a dynamic object is located in the second region MA2. Note that when person M is seated, a person's hands may be located in the first region MA1, so there may or may not be a dynamic object in the first region MA1. The third region MA3 is where person M is located when person M is lying down. Therefore, when person M is lying down, there is no dynamic object in the first region MA1 or the second region MA2, but there is an object in the third region MA3. When person M is lying down, the object in the third region MA3 may be dynamic or static.

[0029] Figure 2 shows a LiDAR device 10, etc. In this embodiment, for example, a raster scan type LiDAR device is used as the LiDAR device 10. The LiDAR device 10 in this embodiment includes a cover 19, a control unit 11, a laser light source 12, a drive mirror 13 for H-direction scanning, a drive mirror 14 for V-direction scanning, a light receiving element 15, and a point cloud data generation unit 16. In the example in Figure 2, the LiDAR device 10 is a mechanical type LiDAR device, but it may also be a phased array type LiDAR device that does not include a drive unit.

[0030] The cover 19 has a housing space for the control unit 11, laser light source 12, drive mirror 13 for H-direction scanning, drive mirror 14 for V-direction scanning, light receiving element 15, and point cloud data generation unit 16, and transmits the laser light Lb emitted from the laser light source 12 and the reflected light Lr that is reflected by objects in the monitoring area MA.

[0031] The control unit 11 is composed of, for example, multiple logic circuits and is electrically connected to the laser light source 12, the H-direction scanning drive mirror 13, and the V-direction scanning drive mirror 14, and controls them. In this embodiment, the control unit 11 is also connected to the control device 20 so that signals can be input and output, and the control signals from the control device 20 control each part of the LiDAR device 10.

[0032] The laser light source 12 emits laser light Lb of a predetermined wavelength. This laser light Lb is, for example, near-infrared light with wavelengths of 905 nm or 1550 nm. The timing of the laser light source 12's emission of laser light Lb is controlled by the control unit 11, which emits the laser light Lb based on a signal from the control unit 11. The control unit 11 is electrically connected to the point cloud data generation unit 16 and outputs data including the timing of the laser light emitted from the laser light source 12 to the point cloud data generation unit 16.

[0033] The H-direction scanning drive mirror 13 includes a mirror that reflects the laser light Lb emitted from the laser light source 12 and a drive unit (not shown) controlled by the control unit 11. When the H-direction scanning drive mirror 13 reflects the laser light Lb, the drive unit changes the reflection angle in the horizontal direction while reflecting the laser light Lb. This change in the reflection angle of the H-direction scanning drive mirror 13 allows the LiDAR device 10 to perform horizontal scanning.

[0034] The V-direction scanning drive mirror 14 includes a mirror that reflects the laser light Lb reflected by the H-direction scanning drive mirror 13, and a drive unit (not shown) controlled by the control unit 11. When the V-direction scanning drive mirror 14 reflects the laser light Lb, the drive unit changes the reflection angle in the vertical direction while reflecting the laser light Lb. This change in the reflection angle of the V-direction scanning drive mirror 14 changes the position of the horizontal scanning performed by the LiDAR device 10 in the vertical direction. The laser light reflected by the V-direction scanning drive mirror 14 passes through the cover 19 and is irradiated into the private room 2.

[0035] The H-direction scanning drive mirror 13 and the V-direction scanning drive mirror 14 are composed of, for example, polygon mirrors or galvanometer mirrors. Alternatively, the H-direction scanning drive mirror 13 and the V-direction scanning drive mirror 14 may each be composed of MEMS mirrors. Furthermore, the H-direction scanning drive mirror 13 and the V-direction scanning drive mirror 14 may be combined into one by a two-axis scanning type mirror, and the order in which the laser beam Lb is reflected by the H-direction scanning drive mirror 13 and the V-direction scanning drive mirror 14 may be reversed.

[0036] The light-receiving element 15 is an element that receives reflected light Lr that is reflected by an object within the monitoring area MA from the laser beam Lb. The reflected light Lr received by the light-receiving element 15 contains information about the object located within the monitoring area MA. The light-receiving element 15 is electrically connected to the point cloud data generation unit 16, and this information is input to the point cloud data generation unit 16 as an electrical signal.

[0037] The point cloud data generation unit 16 generates point data for each reflection position based on the direction of the reflection position where the laser beam Lb is reflected and the distance to the reflection position, using data related to the laser beam emission timing input from the control unit 11, information input from the photodetector 15, and timing data input from the photodetector 15. The point data includes the coordinates of the point. Therefore, the point cloud data generation unit 16 generates point cloud data, which is a collection of point data. The point cloud data generation unit 16 is connected to the control device 20 so that it can receive signals, and the point cloud data is input to the control device 20.

[0038] Furthermore, it is preferable that the point cloud data generation unit 16 does not generate information about objects in the second region MA2, which is located above the toilet seat 41 and overlaps with the toilet seat 41 in the vertical direction, within the monitoring region MA of Figure 1. In other words, it is preferable that the point cloud data output from the point cloud data generation unit 16 does not include information about objects in the second region MA2. Since the upper body of a person M sitting on the toilet seat 41 is usually located in the second region MA2, by not generating information about objects in the second region MA2, the point cloud data output from the point cloud data generation unit 16 will generally not include information indicating the upper body of the person M sitting on the seat. Therefore, the privacy of the person M sitting on the seat can be better protected. The LiDAR device 10 may also be configured so that the monitoring region MA does not include the second region MA2. Even in this case, the point cloud data output from the point cloud data generation unit 16 will not include information about objects in the second region MA2.

[0039] Next, the control device 20 and its operation will be described.

[0040] The control device 20 consists of, for example, an integrated circuit such as a microcontroller, IC (Integrated Circuit), LSI (Large-scale Integrated Circuit), or ASIC (Application Specific Integrated Circuit), or an NC (Numerical Control) device. Furthermore, the control device 20 may or may not use a machine learning machine.

[0041] The control device 20 controls the LiDAR device 10 and identifies the shape of objects in the monitoring region MA from the point cloud data input from the LiDAR device 10. The control device 20 also processes the point cloud data to extract people M, toilet seats 41, etc., and defines the position of the toilet seat 41, the first region MA1, the second region MA2, and the third region MA3. The control device 20 may not detect objects in the second region MA2 if the point cloud data of the monitoring region MA includes the second region MA2. In this case, the control device 20 generally does not process the point cloud data showing the upper body of the seated person M, which can better protect the privacy of the seated person M.

[0042] Furthermore, the control device 20 detects the input of a locking signal from the locking detection device 35, the input of a seating signal from the seating detection device 45, and so on.

[0043] Furthermore, in this embodiment, the control device 20 is connected to the control room CR, where a toilet manager or the like is stationed, enabling signal input and output.

[0044] The control device 20 is electrically connected to the memory 25. The memory 25 is configured to store information and to be readable. The memory 25 is, for example, a non-transitory recording medium, preferably a semiconductor recording medium such as RAM (Random Access Memory) or ROM (Read Only Memory), but it can include any type of recording medium such as an optical recording medium or a magnetic recording medium. Note that a "non-transitory" recording medium includes all computer-readable recording media except transient propagation signals, and does not exclude volatile recording media. The memory 25 and the control device 20 may be provided in a single package. The memory 25 stores various programs for controlling some of the configurations of the control device 20 and generating information, as well as data necessary for generating information. The control device 20 reads the programs and information stored in the memory 25. The memory 25 also stores information, etc., based on instructions from the control device 20.

[0045] Figure 3 is a flowchart showing the operation of the control device 20. The program that executes the operations in the flowchart is stored in memory 25. Therefore, the control device 20 executes the flowchart in Figure 3 by reading the program from memory 25. As shown in Figure 3, the operation of the control device 20 in this embodiment comprises steps S1 to S13.

[0046] In the flowchart in Figure 3, the start is when the toilet monitoring system 1 is powered on and operating normally.

[0047] <Step S1> This step is for the control device 20 to determine whether or not a locking signal has been input from the lock detection device 35. When the lock detection device 35 detects that the lock has been opened with the key 31, a locking signal is input from the lock detection device 35 to the control device 20 as described above. If a locking signal is input, the control device 20 proceeds to step S2, and if no locking signal is input, this step is repeated.

[0048] <Step S2> This step is in which the control device 20 initiates the detection of the state inside the private room 2 by the LiDAR device 10. In this step, the control device 20 transmits a predetermined control signal to the control unit 11 of the LiDAR device 10. Upon receiving the control signal, the control unit 11 controls each part of the LiDAR device 10. Through this control, the LiDAR device 10 emits laser light Lb, scans inside the private room 2, and detects the state inside the private room 2. The LiDAR device 10 outputs point cloud data relating to the detected state inside the private room 2, and inputs this point cloud data to the control device 20. The LiDAR device 10 continues the detection and continues to output point cloud data to the control device 20 until the control device 20 terminates the detection in step S13. After this step, the control device 20 proceeds to step S3.

[0049] <Step S3> This step is for the control device 20 to determine whether or not a seating signal is input from the seating detection device 45. When the seating detection device 45 detects that a person M is seated on the toilet seat 41, a seating signal is input from the seating detection device 45 to the control device 20 as described above. If no seating signal is input, the control device 20 proceeds to step S4, and if a seating signal is input, this step is repeated.

[0050] <Step S4> This step, similar to step S1, is a step in which the control device 20 determines whether or not a locking signal is input from the lock detection device 35. If no locking signal is input, the control device 20 proceeds to step S13; if a locking signal is input, it proceeds to step S5.

[0051] <Step S5> This step is for the control device 20 to determine whether or not a person has fallen. The control device 20 detects a person falling from the point cloud data as follows. Note that in this step, person M is not seated on the toilet seat 41. If the control device 20 detects a person falling, it proceeds to step S6; otherwise, it returns to step S3. Note that the case in which the control device 20 detects a person falling includes not only when the control device 20 recognizes a person falling from the point cloud data, but also when the control device 20 extracts from the point cloud data conditions that satisfy predetermined conditions corresponding to a person falling. The following shows an example of how the control device 20 detects a person falling.

[0052] (First detection method) This method detects a person M falling over by having the control device 20 determine whether or not a dynamic object is located in the first region MA1. If person M is seated on the toilet seat 41 inside the private room 2, then person M has not fallen over. Therefore, if person M is not seated on the toilet seat 41 and has not fallen over, the control device 20 can detect a portion of person M as a dynamic object in the first region MA1 from the point cloud data. Thus, in this step, the control device 20 determines whether or not a dynamic object is located in the first region MA1. If a dynamic object is located in the first region MA1, the control device 20 does not detect a person M falling over; if no dynamic object is located in the first region MA1, it detects a person M falling over. According to this method, it is only necessary to detect the presence or absence of a dynamic object in the first region MA1, and recognition of person M using machine learning or the like may be unnecessary. Therefore, the load on the control device 20 can be reduced. In addition, in this method, detection of objects in the third region MA3 may also be performed.

[0053] (Second detection method) This method detects a person M falling over by having the control device 20 determine whether the movement of the top of a dynamic object is moving downward at a predetermined speed or higher. When a person M falls, their head moves downward at a relatively fast speed. Therefore, in this step, the control device 20 determines whether the movement of the top of the dynamic object is moving downward at a predetermined speed or higher. The predetermined speed is, for example, 0.3 m / s. The control device 20 detects a person M falling over if the movement of the top of the dynamic object is moving downward at a predetermined speed or higher, and does not detect a person M falling over if the movement of the top of the dynamic object is not moving downward at a predetermined speed or higher. In this case, a position for measuring the speed may be set. For example, the movement of the top of the dynamic object may be measured at any position from the toilet seat 41 up to 30 cm above, and it may be determined whether the top moved downward at a predetermined speed or higher in that section. People rarely lower their heads close to the toilet seat 41, and if the speed of the head moving downward is fast, it is generally a fall. Therefore, by setting the position for measuring speed in this way, it becomes possible to detect a person M falling more accurately.

[0054] Furthermore, in the second detection method, a person M may also be detected by determining whether the movement of the top of the dynamic object is at a predetermined speed or greater as described above, and whether the movement continues for a predetermined distance or longer. By detecting movement at a predetermined speed or greater for a predetermined distance or longer, it is possible to detect that the head of person M moves downward over a long distance, and a fall of person M can be detected more accurately. The control device 20 detects a fall of person M if the movement of the top of the dynamic object is at a predetermined speed or greater for a predetermined distance or longer, and does not detect a fall of person M if the movement of the top of the dynamic object is not at a predetermined speed or greater for a predetermined distance or longer. As described above, there are few opportunities for a person to lower their head to the vicinity of the toilet seat 41, and the possibility of a fall increases when the head moves at a predetermined speed or greater for a predetermined distance. Therefore, it is preferable that the section in which the movement of the top of the dynamic object is at a predetermined speed or greater as described above is, for example, a section that includes the height position of the toilet seat 41. It is also preferable that the distance over which the movement of the top of the dynamic object is at a predetermined speed or greater as described above is 30 cm or more in the vertical direction.

[0055] Regardless of the method described above, it is not necessary to detect the movement of the dynamic object in the second region MA2. This is because, if a dynamic object is located in the second region MA2, it can generally be understood as being seated.

[0056] Furthermore, the detection method is not limited to the first and second detection methods described above, as long as the control device 20 can detect when a person M falls. For example, the control device 20 may detect when a person M falls by using image recognition technology, machine learning technology, etc.

[0057] <Step S6> This step is in which the control device 20 starts measuring the period since the fall of person M was detected in step S5. In this step, the control device 20 advances the count using an internal counter to measure the period since the fall was detected. Once the count of the counter is advanced in this step, the counter continues to count unless the measurement period is reset in steps S9 and S12 described later. After this step, the control device 20 proceeds to step S7.

[0058] <Step S7> This step determines whether a predetermined period has elapsed since the control device 20 detected the fall of person M. The control device 20 refers to the information of the counter that started counting in step S6, and if the information of the counter indicates that the predetermined period has elapsed or more, it proceeds to step S10; if the information of the counter indicates that the predetermined period has elapsed or less, it proceeds to step S8. The predetermined period is, for example, 5 minutes.

[0059] <Step S8> This step is for the control device 20 to determine whether or not it has detected that person M is still in a fallen state. Person M may stand up immediately after falling. Therefore, in this embodiment, within a predetermined period of time from the detection of the fall, it is determined whether or not the fallen state is continuing. This detection is performed, for example, in the same manner as the first detection method in step S5, by which the control device 20 determines that if there is no dynamic object in the first region MA1, the fallen state is continuing, and if there is a dynamic object in the first region MA1, the fallen state is not continuing. Alternatively, the control device 20 extracts the shape of person M from among the objects located in the third region MA3, and if such extraction is possible, it determines that the fallen state is continuing, and if such extraction is not possible, it determines that the fallen state is not continuing. Other methods may be used to detect whether person M is still in a fallen state. If the control device 20 detects that person M is still in a fallen state, it returns to step S7, and if it does not detect that person M is still in a fallen state, it proceeds to step S9.

[0060] <Step S9> This step is for the control device 20 to reset the measurement information for the period since it detected the fall of person M, which began in step S6. Accordingly, the control device 20 stops counting with the counter and resets the counter. This step resets the operation of the control device 20 when a fall is detected. After this step, the control device 20 returns to step S3.

[0061] <Step S10> This step is in which the control device 20 outputs a predetermined signal. In this embodiment, the output signal is sent to the control room CR. In this step of this embodiment, it is detected that person M has fallen and remains in that state even after a predetermined time has elapsed, so even if a predetermined signal is output, the output of the signal continues until a reset signal is input in the next step. In this step, the output of the predetermined signal can call the toilet manager or other person stationed in the control room CR. After this step, the control device 20 proceeds to step S11.

[0062] In this step, the control device 20 may output point cloud data or image data based on the point cloud data to the control room CR along with a predetermined signal. The control device 20 may also output a predetermined signal to the audio output device 50. In this case, the predetermined signal may be an audio signal. The audio output device 50 may, for example, emit a voice prompting the person in the private room 2 to press the reset button (not shown) in the private room 2 if they have not fallen. The control room CR may also output a predetermined signal to the audio output device 50, for example, via the control device 20.

[0063] <Step S11> This step is for the control device 20 to determine whether or not a predetermined reset signal has been input to it. As described above, if a predetermined signal is output to the control room CR, the control room CR may output a reset signal. Alternatively, the reset signal may be output when a reset button (not shown) in the private room 2 is pressed. This button may be pressed by an administrator who has rushed to the scene, or by a person M in the private room 2 who has stood up. Alternatively, the reset signal may be output from the lock detection device 35 when the lock detection device 35 detects that the lock has been released. If the control device 20 receives a reset signal, it proceeds to step S12; if it does not receive a reset signal, it repeats this step.

[0064] <Step S12> This step, like step S9, is a step in which the control device 20 resets the measurement information for the period since detecting the fall of person M, which was started in step S6. The control device 20 stops counting by the counter and resets the counter, just as in step S9. After this step, the control device 20 proceeds to step S13.

[0065] <Step S13> This step terminates the detection of the state inside the private room 2 by the LiDAR device 10. In this step, the control device 20 outputs a predetermined control signal to the control unit 11 of the LiDAR device 10. Upon receiving this control signal, the control unit 11 controls various parts of the LiDAR device 10. This control causes the LiDAR device 10 to stop scanning inside the private room 2. This step resets all operations of the fall detection. After this step, the control device 20 returns to step S1.

[0066] As described above, the control device 20 of this embodiment outputs a predetermined signal when a locking signal is input, a seating signal is not input, and a fall of person M is detected from the point cloud data. Furthermore, the program executed by the control device 20 of this embodiment includes a step of outputting a predetermined signal to the control device 20 in the above case. Furthermore, the toilet monitoring system 1 of this embodiment comprises a locking detection device 35, a seating detection device 45, a LiDAR device 10, and a control device 20, and the control device 20 outputs a predetermined signal in the above case.

[0067] The point cloud data output from the LiDAR device 10 can identify human movement and objects, but it cannot identify individuals. Therefore, by detecting the state inside the private room 2 using the LiDAR device 10, privacy inside the private room 2 can be protected. By detecting falls from the point cloud data input from the LiDAR device 10, false detections that a person has fallen when luggage is placed on the floor can be suppressed. Also, even if person M inside the private room 2 performs an action that would be falsely detected as a fall by the control device 20, it is not a fall if the person remains seated. Therefore, by detecting a fall from the point cloud data when no seating signal is input, false detections can be suppressed. In this way, when a fall of person M is detected, the control device 20 outputs a predetermined signal, which can cause other devices to take action indicating that a person has fallen.

[0068] The present invention has been described above with reference to the above embodiments, but the present invention is not limited thereto. For example, in the above embodiments, when a fall of person M is detected, a predetermined signal is output after a predetermined period of time has elapsed since the fall was detected. However, the control device 20 may output a predetermined signal without waiting for the predetermined period of time to elapse after detecting a fall of person M. In this case, steps S6 to S9 and S12 in the flowchart of Figure 3 are unnecessary. Therefore, the control device 20 proceeds to step S10 when it detects a fall of person M in step S5, and proceeds to step S13 when it detects the input of a reset signal in step S11.

[0069] Furthermore, in the above embodiment, a predetermined signal output from the control device 20 was input to the control room CR. However, the predetermined signal from the control device 20 may be input to, for example, a monitoring device, or only the audio output device 50, or to other devices. The toilet monitoring system 1 does not need to be equipped with the audio output device 50. [Industrial applicability]

[0070] According to the present invention, a control device, program, and toilet monitoring system can be provided that can detect a person falling in a toilet while protecting privacy and suppressing false detections, and are expected to be used in fields such as crisis management systems for toilets. [Explanation of Symbols]

[0071] 1. Toilet monitoring system 2...Private Rooms 10...LiDAR device 20. Control device 35. Lock detection device 45. Seating detection device MA...Monitoring area MA1...1st area MA2...Second area MA3...Third area

Claims

1. A control device that receives a lock signal from a lock detection device that detects the locking of a toilet stall, a seating signal from a seating detection device that detects someone sitting on the toilet seat inside the stall, and point cloud data output from a LiDAR device that detects the state inside the stall, When the aforementioned locking signal is input, the aforementioned seating signal is not input, and a person falls from the point cloud data, a predetermined signal is output. A control device characterized by the following features.

2. If no dynamic object located in a region higher than the toilet seat is detected from the point cloud data, it is assumed that the person has fallen. The control device according to feature 1.

3. Objects located above the toilet seat in the point cloud data and overlapping with the toilet seat in the vertical direction are not detected. The control device according to claim 1 or 2.

4. A program executed by a control device that receives a lock signal from a lock detection device that detects the locking of a toilet stall, a seating signal from a seating detection device that detects someone sitting on the toilet seat inside the stall, and point cloud data output from a LiDAR device that detects the state inside the stall, The steps include determining whether or not the locking signal is input to the control device, The step of determining whether or not the seating signal is input to the control device, The steps include detecting a person falling using the aforementioned point cloud data, The steps include: outputting a predetermined signal when the locking signal is input, the seating signal is not input, and a person falls from the point cloud data; Equipped with A program characterized by the following features.

5. A lock detection device that detects whether a toilet stall is locked, A seating detection device that detects when a person sits on the toilet seat inside the private room, A LiDAR device for detecting the state inside the private room, A control device that receives a locking signal from the locking detection device, a seating signal from the seating detection device, and point cloud data from the LiDAR device, Equipped with, The control device outputs a predetermined signal when the locking signal is input, the seating signal is not input, and a person has fallen from the point cloud data. A toilet monitoring system characterized by the following features.

6. The control device determines that a person has fallen if it does not detect any dynamic objects located in a region higher than the toilet seat from the point cloud data. The toilet monitoring system according to claim 5.

7. The control device de-detects objects located above the toilet seat in the point cloud data and in a region that overlaps with the toilet seat in the vertical direction. The toilet monitoring system according to claim 5 or 6, characterized in that it is the most advanced version of the toilet monitoring system according to claim 5 or 6.

8. The point cloud data does not include information about objects located above the toilet seat and in the region that overlaps with the toilet seat in the vertical direction. The toilet monitoring system according to claim 5 or 6, characterized in that it is the most advanced version of the toilet monitoring system according to claim 5 or 6.

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