Monitoring device, monitoring method and monitoring program

Abstract

A monitoring device (100) is characterized by comprising: an acquisition unit (121) that acquires the intensity of a signal received by a moving body sensor provided in a vehicle and the coordinates of a moving body identified on the basis of the information detected by the moving body sensor; and a determination unit (122) which determines that the moving body is an object that should not be detected, such determination made if the standard deviation of the intensity of the signal acquired by the acquisition unit (121) is less than a threshold and the standard deviation of a movement distance is less than a threshold.

Description

Monitoring device, monitoring method, and monitoring program

[0001] The present invention relates to a monitoring device, a monitoring method, and a monitoring program.

[0002] Conventionally, there is a technology for microwave sensors that use microwaves to detect objects, which accurately distinguishes between objects that should be detected, such as a human body, and objects that should not be detected (for example, plants swaying in the wind), thereby avoiding false alarms (for example, Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2003-207462

[0004] However, conventional technologies may not be able to accurately determine an object that should not be detected. For example, when the movement of a person, which is the object to be detected, is small or when the person is far away, there is a risk that the person, which is the object to be detected, may be mistakenly detected as an object that should not be detected. Thus, the above-mentioned problem is one example of the problem that the present invention aims to solve.

[0005] In order to solve the above-mentioned problems and achieve the object, the invention described in claim 1 is characterized by having an acquisition unit that acquires the strength of a signal received by a motion sensor installed in the vehicle and the coordinates of a moving object identified based on the information detected by the motion sensor, and a determination unit that determines that the moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit is less than a threshold value and the standard deviation of the moving distance is less than a threshold value.

[0006] The invention described in claim 4 is a method executed by a monitoring device, characterized in that it includes an acquisition process in which a motion sensor installed in a vehicle acquires the strength of a signal received and the coordinates of a moving object identified based on information detected by the motion sensor, and a determination process in which, if the standard deviation of the signal strength acquired by the acquisition process is less than a threshold value and the standard deviation of the moving distance is less than a threshold value, the moving object is determined to be an object that should not be detected.

[0007] The invention described in claim 5 is characterized in that a computer is made to execute an acquisition step of acquiring the strength of a signal received by a motion sensor installed in a vehicle and the coordinates of a moving object identified based on information detected by the motion sensor, and a determination step of determining that the moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition step is less than a threshold value and the standard deviation of the moving distance is less than a threshold value.

[0008] FIG. 1 is a diagram illustrating an example of the configuration of a monitoring device system according to an embodiment. FIG. 2 is a diagram illustrating an example of the configuration of a monitoring device according to an embodiment. FIG. 3 is a diagram illustrating an example of an installation location of a motion sensor according to an embodiment. FIG. 4 is a diagram illustrating an example of a determination process performed by a monitoring device according to an embodiment. FIG. 5 is a diagram illustrating an example of a determination process performed by a monitoring device according to an embodiment. FIG. 6 is a diagram illustrating a change process performed by a monitoring device according to an embodiment. FIG. 7 is a flowchart illustrating an example of a process flow performed by a monitoring device according to an embodiment. FIG. 8 is a diagram illustrating an example of a determination process performed by a monitoring device according to an embodiment. FIG. 9 is a diagram illustrating an example of a determination process performed by a monitoring device according to an embodiment. FIG. 10 is a diagram illustrating an example of a determination process performed by a monitoring device according to an embodiment. FIG. 11 is a diagram illustrating an example of a determination process performed by a monitoring device according to an embodiment. FIG. 12 is a flowchart illustrating an example of a process flow performed by a monitoring device according to an embodiment. FIG. 13 is a flowchart illustrating an example of a process flow performed by a monitoring device according to an embodiment. FIG. 14 is a flowchart illustrating an example of a process flow performed by a monitoring device according to an embodiment. FIG. 15 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of a monitoring device.

[0009] Hereinafter, a mode for carrying out the present invention (hereinafter referred to as an embodiment) will be described with reference to the drawings. Note that the present invention is not limited to the embodiment described below. Furthermore, in the description of the drawings, the same parts are given the same reference numerals.

[0010] [First embodiment] [1. System configuration] First, the configuration of a monitoring system according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the configuration of a monitoring system according to an embodiment. Fig. 1 shows a monitoring system 1 as an example of a monitoring system according to an embodiment.

[0011] 1, the monitoring system 1 may include an in-vehicle device 10 and a monitoring device 100. The in-vehicle device 10 and the monitoring device 100 are connected to each other via a network N so as to be able to communicate with each other via a wired or wireless connection. The monitoring system 1 shown in FIG. 1 may include any number of in-vehicle devices 10 and any number of monitoring devices 100.

[0012] The in-vehicle device 10 may be a dedicated sensor device built into or externally attached to the vehicle VEx, or may be a recording device (drive recorder) or other device installed in the vehicle VEx for crime prevention or to prevent tailgating.

[0013] The in-vehicle device 10 may also be configured with a sensor device and a notification device. As an example, the in-vehicle device 10 may be a composite device in which a sensor device and a notification device that are independent of each other are connected to each other so as to be able to communicate with each other. As another example, the in-vehicle device 10 may be a single device having a sensor function and a notification function.

[0014] Furthermore, a user can connect a predetermined sensor to a portable terminal device (e.g., a smartphone, a tablet terminal, a notebook PC, a desktop PC, a PDA, or the like) that they use on a daily basis and install a predetermined application, thereby substituting the portable terminal device as the in-vehicle device 10. For example, a portable terminal device that is equipped with a predetermined sensor or to which a predetermined sensor is connected can be understood as the in-vehicle device 10 referred to here. When the portable terminal device is used as the in-vehicle device 10, it is installed, for example, on the dashboard of the vehicle VEx while driving.

[0015] The in-vehicle device 10 may also include various sensors, such as a distance sensor, a motion sensor such as a microwave sensor or a LiDAR (light detection and ranging) sensor, a temperature sensor, a microphone, a GPS sensor, an acceleration sensor, a gyro sensor, a camera, and an air pressure sensor.

[0016] The monitoring device 100 may acquire various types of data based on sensor information detected by these sensors (for example, by analyzing the sensor information). For example, the monitoring device 100 acquires information on moving objects inside and outside the vehicle from a moving object sensor. Also, for example, the monitoring device 100 acquires the temperature inside the vehicle from a temperature sensor. Also, for example, the monitoring device 100 acquires audio from a microphone. Also, for example, the monitoring device 100 acquires angular velocity from a gyro sensor. Also, for example, the monitoring device 100 acquires video data of the outside captured from inside the vehicle VEx by a camera. Note that the monitoring device 100 may acquire sensor information detected not only by sensors provided in the in-vehicle device 10, but also by sensors provided in the vehicle VEx itself.

[0017] The monitoring device 100 is a device that determines objects that should not be detected. Conventionally, parked vehicles have been monitored to prevent crimes such as car theft and break-ins. In such devices that monitor parked vehicles, objects to be detected are people who approach or peer into the parked vehicle. However, if objects that should not be detected, such as plants such as grass and trees, or banners and flags, are present near the parked vehicle, the device may mistakenly detect the presence of a person, which is an object that should be detected. Therefore, the monitoring device 100 accurately determines objects that should not be detected near the parked vehicle, preventing false detections.

[0018] For example, when the standard deviation of the strength of a signal received by a motion sensor provided in the vehicle and the standard deviation of the coordinates of a moving object identified based on information detected by the motion sensor are less than a threshold, the monitoring device 100 determines that the moving object is an object that should not be detected. Also, for example, the monitoring device 100 determines whether the moving object is an object that should not be detected based on the coordinates of the moving object identified based on information detected by the motion sensor provided in the vehicle.

[0019] Here, if the in-vehicle device 10 is an edge computer that performs edge processing near the user, the monitoring device 100 may be, for example, a cloud computer that performs processing on the cloud side. In other words, the monitoring device 100 may be a server device.

[0020] Furthermore, in the following embodiment, an example is shown in which the monitoring according to the embodiment is realized in the monitoring system 1 by transmitting and receiving information between the in-vehicle device 10 and the monitoring device 100. However, the monitoring according to the embodiment may be realized only on the edge side, i.e., by the in-vehicle device 10. In this case, the in-vehicle device 10 may be configured to behave like the monitoring device 100, for example, by a monitoring program according to the embodiment.

[0021] 2. Configuration of the Monitoring Device Next, the monitoring device 100 according to the embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example configuration of the monitoring device 100 according to the embodiment. As shown in Fig. 2, the monitoring device 100 has a communication unit 110, a storage unit 130, and a control unit 120. Each unit of the monitoring device 100 will be described below.

[0022] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the in-vehicle device 10, for example.

[0023] The storage unit 130 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk, an optical disk, etc. The storage unit 130 stores information such as the location where the motion sensor is installed, the strength of the signal to be transmitted, the sensitivity of receiving the signal, the strength of the received signal, the angle calculated from the received signal, the distance, the coordinates of the motion sensor, and other information necessary for determining whether an object should not be detected.

[0024] The control unit 120 is realized using a CPU (Central Processing Unit), an NP (Network Processor), an FPGA (Field Programmable Gate Array), etc., and executes processing programs stored in memory. As shown in Fig. 2, the control unit 120 has an acquisition unit 121, a determination unit 122, and a change unit 123. Each unit of the control unit 120 will be described below.

[0025] The acquisition unit 121 acquires the strength of a signal received by a motion sensor provided in the vehicle and the coordinates of a moving object identified based on information detected by the motion sensor. For example, the acquisition unit 121 acquires the strength of a signal received by the motion sensor provided in the vehicle and the coordinates of a moving object identified from information on the distance and angle detected by the motion sensor. In this case, the number of motion sensors may be multiple. For example, the acquisition unit 121 acquires the strength of each signal received by multiple motion sensors provided in the vehicle so that their detection ranges include the vehicle interior, and the coordinates of a moving object identified based on information detected by the multiple motion sensors.

[0026] The location of the motion sensor is not limited as long as it is installed inside the vehicle. For example, it may be installed near the rearview mirror as shown in Fig. 3(1) or on the center pillar as shown in Fig. 3(2). That is, the motion sensor may be installed in a location inside the vehicle depending on the purpose, such as the front pillar, center pillar, rear pillar, rearview mirror, ceiling, seat, or rear window.

[0027] The determination unit 122 determines that a moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit 121 is less than a threshold value and the standard deviation of the movement distance is less than a threshold value. Here, the movement distance (movement amount) may be the movement distance of the coordinates of the moving object acquired by the acquisition unit 121, or the movement distance of the center of gravity, which is the midpoint of the coordinates of consecutive moving objects. Furthermore, the standard deviation may be calculated based on samples taken up to a predetermined period (e.g., 2.0 seconds) before a given sample, or may be calculated based on samples taken up to a predetermined number (e.g., 40) before a given sample. Specific examples of the processing by the determination unit 122 will be described later in the determination processing section.

[0028] In other words, the determination unit 122 determines that a moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit 121 is less than the threshold value for a period of at least a specified percentage of the specified period, and the standard deviation of the movement distance is less than the threshold value for a period of at least a specified percentage of the specified period.

[0029] More specifically, the determination unit 122 determines that a moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit 121 is less than the threshold value (1.3) for 90% or more of a period of 3.5 seconds and the standard deviation of the movement distance is less than the threshold value (4.0) for 90% or more of a period of 3.5 seconds.

[0030] The above-mentioned time element condition may be expressed by the number of data pieces. For example, if 20 data pieces are acquired per second, the above-mentioned 3.5 seconds is expressed by 70 data pieces. That is, the determination unit 122 determines that a moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit 121 is less than the threshold value (1.3) for 63 or more data pieces and the standard deviation of the movement distance is less than the threshold value (4.0) for 63 or more data pieces.

[0031] Furthermore, the determination unit 122 can determine that the moving object is an object that should not be detected by adding a condition of the distance between the moving object and the moving object sensor. For example, the determination unit 122 determines that the moving object is an object that should not be detected when the standard deviation of the intensity of the signal acquired by the acquisition unit 121 is less than a threshold, the standard deviation of the movement distance is less than a threshold, and the distance between the moving object and the moving object sensor is less than a threshold.

[0032] More specifically, the determination unit 122 determines that a moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit 121 is less than a threshold value (1.3), the standard deviation of the movement distance is less than a threshold value (4.0), and the distance between the moving object and the moving object sensor is less than 300 cm. Here, the condition for the distance between the moving object and the moving object sensor may be expressed as the distance on each of the X and Y axes. For example, assuming that the coordinates of the moving object sensor are X-axis: 0 and Y-axis: 0, the condition for the distance between the moving object and the moving object sensor may be expressed as "when a moving object is detected within the coordinate range of X-axis: -300 to 300 cm, Y-axis: 0 to 500 cm."

[0033] The change unit 123 changes the settings of the motion sensor when the determination unit 122 determines that a moving object is an object that should not be detected. For example, the change unit 123 changes the sensitivity with which the motion sensor receives signals when the determination unit 122 determines that a moving object is an object that should not be detected. For example, when the determination unit 122 determines that a moving object is an object that should not be detected, the change unit 123 lowers the sensitivity with which signals reflected near the coordinates of the moving object are received. Furthermore, for example, when the determination unit 122 determines that a moving object is an object that should not be detected, the change unit 123 lowers the sensitivity with which signals from the coordinate direction of the moving object are received.

[0034] 4 and 5, the determination process performed by the monitoring device 100 will be described. FIGS. 4 and 5 are diagrams for explaining an example of the determination process performed by the monitoring device 100. FIG. 4(1) shows data identified based on information detected by a motion sensor in a situation where a tree is swaying. For example, information such as the coordinates (X, Y) of the moving object and the signal strength (Level) is shown. Here, when an object that should not be detected, such as a swaying tree, is detected by the motion sensor, characteristic coordinate movement and signal strength as described below are observed.

[0035] For example, when a motion sensor detects the swaying movement of a tree, the coordinates of the moving object move slightly due to the small movements of the branches and leaves. That is, as shown in Figure 4 (2), the standard deviation of the amount of movement is low. Also, when a motion sensor detects the swaying movement of a tree, for example, plants do not move spontaneously and their position does not change much, so there is little change in signal strength. That is, as shown in Figure 4 (3), the standard deviation of signal strength is low.

[0036] Therefore, the determination unit 122 determines whether an object that should not be detected is an object that should not be detected based on coordinate movement and signal intensity change that are characteristically observed when an object that should not be detected is detected by the motion sensor. For example, as shown in Figure 4 (2), the determination unit 122 determines that a moving object is an object that should not be detected when the standard deviation of the movement distance acquired by the acquisition unit 121 is less than the threshold value (4.0) for 90% or more of a period of 3.5 seconds, and when the standard deviation of the signal intensity is less than the threshold value (1.3) for 90% or more of a period of 3.5 seconds, as shown in Figure 4 (3).

[0037] This allows the monitoring device 100 to determine that a moving object is an object that should not be detected based on the signal strength that is characteristically observed when an object that should not be detected is detected as a moving object and the movement of the coordinates of the moving object.

[0038] Next, the addition of a distance condition by the determination unit 122 will be described. Figures 5(1) and 5(2) both show the coordinates of a moving object (person) detected at a position far away from the vehicle. When a moving object is detected at a position far away from the vehicle, blurring, noise, and attenuation occur in the identified coordinates and signal strength of the moving object. For example, as shown in Figure 5(1), when a moving object is detected at a position far away from the vehicle on the X axis, coordinates in which the coordinates of the moving object move minutely within a certain range and signal strength with little fluctuation are obtained. The same applies to a case where a moving object is detected at a position far away from the vehicle on the Y axis, as shown in Figure 5(2).

[0039] That is, even for a moving object detected at a distant location, erroneous determination (false detection) may occur if determination is made using only the coordinates of the moving object and the standard deviation of the signal intensity as explained with reference to Fig. 4. Therefore, the determination unit 122 further adds a condition of the distance between the moving object and the moving object sensor to determine that the moving object is an object that should not be detected.

[0040] For example, the determination unit 122 determines that a moving object is an object that should not be detected when the standard deviation of the signal strength acquired by the acquisition unit 121 is less than the threshold value (1.3) for 90% or more of a period of 3.5 seconds, the standard deviation of the moving distance is less than the threshold value (4.0) for 90% or more of a period of 3.5 seconds, the distance on the X coordinate between the moving object and the moving object sensor is within 300 cm, and the distance on the Y coordinate between the moving object and the moving object sensor is within 500 cm. In addition to the distance condition, the determination unit 122 can appropriately combine other conditions, such as the signal strength being greater than 0 and the moving object not having entered the vehicle interior.

[0041] This allows the monitoring device 100 to exclude moving objects detected at a distant location from the targets of the judgment, thereby preventing erroneous judgment. Note that the distances from the moving object on the X and Y coordinates described above are example values ​​indicated by an experiment conducted using a minivan with a total length of approximately 4600 mm and a width of approximately 1700 mm as the target vehicle, and when using the technology described in this specification, it is desirable to change them appropriately depending on the vehicle model, vehicle size, situation, etc.

[0042] 4. Change Processing Next, the change processing performed by the monitoring device 100 will be described with reference to Fig. 6. Fig. 6 is a diagram for explaining an example of the change processing performed by the monitoring device 100. In the example of Fig. 6, a tree is located near the right front seat of the vehicle. If this tree sways due to the influence of wind, for example, the determination unit 122 determines through the above-described determination processing that the moving object is an object that should not be detected.

[0043] Thereafter, the change unit 123 changes the setting of the motion sensor. For example, when the determination unit 122 determines that a moving object (tree) located near the front right seat of the vehicle is an object that should not be detected, the change unit 123 lowers the sensitivity for receiving signals reflected near the coordinates (X-axis: XX, Y-axis: XX) of the moving object (tree). At this time, the change unit 123 does not need to change the sensitivity for receiving signals reflected from other than the coordinates of the moving object (tree).

[0044] The change unit 123 can also lower the sensitivity for receiving signals from the direction in which a moving object determined to be an object that should not be detected is located. For example, the change unit 123 lowers the sensitivity for receiving signals from an angle (000° to 000°) in which a moving object (tree) determined to be an object that should not be detected is located.

[0045] In other words, the monitoring device 100 reduces the sensitivity for receiving signals from moving objects that are determined to be objects that should not be detected, thereby preventing signals from moving objects that do not need to be monitored from being received, and can receive signals from other positions and directions without turning off the power to the moving object sensor and continuously perform the determination process, thereby accurately determining objects that should not be detected.

[0046] 5. Flowchart Next, the processing performed by the monitoring device 100 configured as described above will be described using the flowchart in Fig. 7. The flowchart in Fig. 7 is mainly executed by the control unit 120. This flowchart can also be configured as a program executed by the CPU of the control unit 120 to form a monitoring program. Note that the steps below can be executed in a different order, and some processing may be omitted.

[0047] First, the acquisition unit 121 acquires the strength of a signal received by a motion sensor provided in the vehicle and the coordinates of a moving object identified based on information detected by the motion sensor (step S101). For example, the acquisition unit 121 acquires the strength of a signal received by the motion sensor provided in the vehicle and the coordinates of a moving object identified from information on the distance and angle detected by the motion sensor.

[0048] Next, the determination unit 122 determines whether the standard deviation of the signal strength acquired by the acquisition unit 121 is less than the threshold value (step S102). If the determination unit 122 determines that the standard deviation of the signal strength is not less than the threshold value (step S102 "No"), the process returns to step S101.

[0049] On the other hand, if the determination unit 122 determines that the standard deviation of the signal intensity is less than the threshold value ("Yes" in step S102), the determination unit 122 determines whether the standard deviation of the moving distance calculated from the coordinates of the moving object acquired by the acquisition unit 121 is less than the threshold value (step S103). Here, if the determination unit 122 determines that the standard deviation of the moving distance is not less than the threshold value ("No" in step S103), the process returns to step S101 again.

[0050] On the other hand, if the determination unit 122 determines that the standard deviation of the movement distance is less than the threshold value ("Yes" in step S103), the determination unit 122 determines whether the distance between the moving object and the moving object sensor is less than a predetermined threshold value (step S104). For example, the determination unit 122 determines whether the distance between the moving object and the moving object sensor, calculated from the coordinates of the moving object and the coordinates of the moving object sensor, is less than the threshold value. Here, if the determination unit 122 determines that the distance between the moving object and the moving object sensor is not less than the threshold value ("No" in step S104), the process returns to step S101 again.

[0051] On the other hand, if the determination unit 122 determines that the distance between the moving object and the moving object sensor is less than the threshold value ("Yes" in step S104), the determination unit 122 determines that the moving object is an object that should not be detected (step S105). Subsequently, the change unit 123 changes the setting of the moving object sensor (step S106). For example, the change unit 123 reduces the receiving sensitivity for signals from the coordinate direction of the moving object determined to be an object that should not be detected.

[0052] 6. Effects The monitoring device 100 according to the embodiment includes an acquisition unit 121 that acquires the strength of a signal received by a motion sensor provided in the vehicle and the coordinates of a moving object identified based on information detected by the motion sensor, and a determination unit 122 that determines that the moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit 121 is less than a threshold value and the standard deviation of the moving distance is also less than a threshold value.

[0053] As a result, monitoring device 100 can accurately determine whether an object that should not be detected is an object that should not be detected by determining whether the standard deviation of the signal strength and the standard deviation of the moving distance of the moving object are each below a threshold value. In other words, monitoring device 100 determines that a moving object is an object that should not be detected based on the signal strength that is characteristically observed when an object that should not be detected is detected as a moving object and the movement of the coordinates of the moving object.

[0054] The determination unit 122 of the monitoring device 100 according to the embodiment further determines that the moving object is an object that should not be detected if the distance between the moving object and the moving object sensor is less than a threshold value. As a result, the monitoring device 100 can accurately determine whether the standard deviation of the signal intensity and the standard deviation of the coordinates of the moving object are both less than the threshold value and whether the distance between the moving object and the moving object sensor is less than the threshold value.

[0055] The monitoring device 100 according to the embodiment further includes a change unit 123 that changes the settings of the motion sensor when the determination unit 122 determines that a moving object is an object that should not be detected. As a result, the monitoring device 100 reduces the reception sensitivity of signals from a moving object determined to be an object that should not be detected, thereby preventing signals from moving objects that do not need to be monitored from being received, and can receive signals from other positions and directions without turning off the power to the motion sensor and continue to perform determination processing, thereby accurately determining objects that should not be detected.

[0056] [Second embodiment] [1. Configuration of monitoring device] In the first embodiment, an example was described in which information on the signal strength and the coordinates of a moving object was used to determine whether or not the moving object is an object that should not be detected, but in the second embodiment described below, an example will be described in which whether or not the moving object is an object that should not be detected is determined based on the coordinates of the moving object. Note that descriptions of the same content as in the first embodiment will be omitted as appropriate.

[0057] First, a monitoring device 100 according to an embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the monitoring device 100 according to an embodiment. As shown in Fig. 2, the control unit 120 of the monitoring device 100 includes an acquisition unit 121, a determination unit 122, and a change unit 123. Each unit included in the control unit 120 will be described below.

[0058] The acquisition unit 121 acquires the coordinates of the specified moving object based on information detected by a moving object sensor provided in the vehicle. For example, the acquisition unit 121 acquires the coordinates of the specified moving object from information on the distance and angle detected by the moving object sensor.

[0059] The determination unit 122 determines whether the moving object is an object that should not be detected based on the coordinates of the moving object acquired by the acquisition unit 121. For example, the determination unit 122 determines that the moving object is an object that should not be detected if the value obtained by dividing the total amount of movement of the coordinates of the moving object acquired by the acquisition unit 121 over a predetermined period by the amount of movement of the coordinates of the moving object between the start point and the end point over the predetermined period is equal to or greater than a threshold. In this case, the determination unit 122 can perform threshold determination by calculating each of the X coordinate and the Y coordinate. More specifically, the determination unit 122 determines that the moving object is an object that should not be detected if the value calculated using Equation 1 is equal to or greater than a threshold (15) and the value calculated using Equation 2 is equal to or greater than a threshold (15).

[0060]

[0061]

[0062] Furthermore, the determination unit 122 can perform threshold determination on the number of data items that exceed a threshold. For example, when the total number of data items is 100, the determination unit 122 determines that a moving object is an object that should not be detected if the number of data items whose values ​​calculated using Equation 1 are equal to or greater than the threshold (15) is equal to or greater than the threshold (20) and the number of data items whose values ​​calculated using Equation 2 are equal to or greater than the threshold (15) is equal to or greater than the threshold (20). Note that any value can be used for each threshold depending on the purpose.

[0063] Furthermore, the determination unit 122 determines that the moving object is an object that should not be detected if the value obtained by dividing the total amount of movement of the coordinates of the moving object acquired by the acquisition unit 121 over a predetermined period by the square root of the sum of the square of the difference between the maximum and minimum values ​​of the X coordinates of the moving object over the predetermined period and the square of the difference between the maximum and minimum values ​​of the Y coordinates of the moving object over the predetermined period is equal to or greater than a threshold value. More specifically, the determination unit 122 determines that the moving object is an object that should not be detected if the value calculated using Equation 3 is equal to or greater than a threshold value (15).

[0064]

[0065] Furthermore, the determination unit 122 performs frequency analysis on the coordinates of the moving object acquired by the acquisition unit 121, and if high-frequency components are included, determines that the moving object is an object that should not be detected. For example, the determination unit 122 performs frequency analysis using a Fourier transform on the coordinates of the moving object acquired by the acquisition unit 121, and if high-frequency components equal to or higher than a threshold value (2 Hz) are included, estimates that the moving object is an object that should not be detected. Note that any value can be used as the threshold value depending on the purpose.

[0066] Furthermore, the determination unit 122 can determine that the moving object is an object that should not be detected by adding a condition of the distance between the moving object and the moving object sensor. For example, the determination unit 122 further determines that the moving object is an object that should not be detected when the distance between the moving object and the moving object sensor is less than a threshold value.

[0067] More specifically, if the distance between the moving object and the moving object sensor is less than 300 cm, the determination unit 122 determines that the moving object is an object that should not be detected. Here, the condition for the distance between the moving object and the moving object sensor may be expressed as the distance on each of the X and Y axes. For example, assuming that the coordinates of the moving object sensor are X-axis: 0 and Y-axis: 0, the condition for the distance between the moving object and the moving object sensor may be expressed as "when a moving object is detected within the coordinate range of X-axis: -300 to 300 cm, Y-axis: 0 to 500 cm."

[0068] The change unit 123 changes the settings of the motion sensor when the determination unit 122 determines that a moving object is an object that should not be detected. For example, the change unit 123 changes the sensitivity with which the motion sensor receives signals when the determination unit 122 determines that a moving object is an object that should not be detected. For example, when the determination unit 122 determines that a moving object is an object that should not be detected, the change unit 123 lowers the sensitivity with which signals from the vicinity of the coordinates of the moving object are received. For example, when the determination unit 122 determines that a moving object is an object that should not be detected, the change unit 123 lowers the sensitivity with which signals from the coordinate direction of the moving object are received.

[0069] 8 to 11, the determination process performed by the monitoring device 100 will be described. Figures 8 to 11 are diagrams for explaining an example of the determination process performed by the monitoring device 100. First, an example will be described using Figures 8 and 9 in which an object that should not be detected is determined using the sum of the movement amounts of each point relative to the movement amounts of the start point and end point.

[0070] The difference between detecting a person and detecting an object that should not be detected will be explained using Figures 8 and 9. The left side of Figure 8 shows the X coordinate, Y coordinate, X coordinate ratio value, and Y coordinate ratio value when a motion sensor detects a moving object (person). The ratio value is the ratio of the total movement amount in a predetermined period to the movement amount between the start point and end point in a predetermined period. The right side of Figure 8 shows the movement amount between the start point and end point with arrows and each movement amount with a line.

[0071] When the motion sensor detects a moving object (person), there is little data that exceeds the threshold (15) for the ratio value of the X coordinate, as shown on the left in Figure 8. Similarly, there is little data that exceeds the threshold (15) for the ratio value of the Y coordinate. Furthermore, when the motion sensor detects a moving object (person), it can be visually seen from the right in Figure 8 that the total movement amount of each point relative to the movement amount of the start point and end point is small.

[0072] The left side of Figure 9(1) shows the X coordinate, Y coordinate, X coordinate ratio value, and Y coordinate ratio value when the motion sensor detects a moving object (tree swaying). The right side of Figure 9(1) shows the movement amount of the start point and end point with arrows and the movement amount of each point with lines. When the motion sensor detects a moving object (tree swaying), as shown in the left side of Figure 9(1), there is a lot of data that exceeds the threshold value (15) for the X coordinate ratio value, and similarly, there is a lot of data that exceeds the threshold value (15) for the Y coordinate ratio value. Furthermore, when the motion sensor detects a moving object (person), it can be visually understood from the right side of Figure 9(1) that the total movement amount of each point is large compared to the movement amount of the start point and end point.

[0073] In other words, when a person is detected as a moving object, the person rarely stays in a fixed position and moves around a lot, so the total amount of movement of each point relative to the amount of movement of the start and end points is small.In contrast, when the swaying of a tree is detected as a moving object, although the branches move slightly up and down and left and right, they move within a certain range, so compared to the case of a person, the total amount of movement of each point relative to the amount of movement of the start and end points is larger.

[0074] Therefore, the monitoring device 100 performs a threshold determination on the sum of the movement amounts of each point relative to the movement amounts of the start point and the end point. For example, as shown in the condition of FIG. 9 (2), when the total number of data is 200, the determination unit 122 determines that a moving object is an object that should not be detected if the number of data pieces in which the sum of the movement amounts of each point on the X coordinate for 30 samples divided by the movement amount between the start point and the end point on the X coordinate is equal to or greater than the threshold (25) is equal to or greater than the threshold (25), and the number of data pieces in which the sum of the movement amounts of each point on the Y coordinate for 30 samples divided by the movement amount between the start point and the end point on the Y coordinate is equal to or greater than the threshold (25). As a result, the monitoring device 100 can accurately determine whether an object should not be detected by performing a threshold determination on the value obtained by dividing the total movement amount by the movement amount between the start point and the end point on the coordinate.

[0075] Next, an example of determining an object that should not be detected using the total amount of movement in a predetermined position coordinate area will be described with reference to FIG. 10. FIG. 10(1) shows the coordinate movement when grass sways in the wind. For example, when a plant sways in the wind, its branches and leaves move in a fixed position. In other words, the total amount of movement within a predetermined position coordinate area tends to be large. Here, the predetermined position coordinate area is an area determined by the maximum and minimum values ​​of the X coordinate and the maximum and minimum values ​​of the Y coordinate over a predetermined period, as shown by the diagonal line (La) of the rectangle in FIG. 9(1).

[0076] For example, La is expressed as the square root of the sum of the square of the difference between the maximum and minimum values ​​of the X coordinate of the moving object in a predetermined period and the square of the difference between the maximum and minimum values ​​of the Y coordinate of the moving object in a predetermined period. Note that the predetermined period may be represented by the number of data points.

[0077] For example, the monitoring device 100 performs a threshold determination on the amount of movement in a predetermined position coordinate area under the conditions shown in Fig. 10 (2). For example, when the total number of data samples is 100, the determination unit 122 determines that the moving object is an object that should not be detected if the value obtained by dividing the total distance moved for the 100 samples by the square root of the sum of the square of the difference between the maximum and minimum values ​​of the X coordinate and the square of the difference between the maximum and minimum values ​​of the Y coordinate of the moving object over a predetermined period of time is equal to or greater than a predetermined threshold.

[0078] As a result, the monitoring device 100 performs a threshold judgment on the value obtained by dividing the total movement amount by the square root of the sum of the squares of the differences between the maximum and minimum values ​​for each coordinate axis, thereby evaluating the movement distance of each point without separating the X and Y coordinates, and can accurately determine objects that should not be detected.

[0079] Next, an example of determining an object that should not be detected by frequency analysis will be described with reference to Fig. 11. Fig. 11(1) shows the coordinate movement of a moving object detected by the swaying of a tree. As shown in Figs. 11(2) and 11(3), the coordinate movement of the moving object detected by the swaying of the tree shown in Fig. 11(1) contains multiple frequencies. That is, because trees that sway due to the influence of wind or the like perform repetitive movements in a fixed position, the coordinate movement of the moving object detected by the swaying of the tree contains high-frequency components that are not seen when a person passes near a vehicle or looks into the vehicle.

[0080] Therefore, the determination unit 122 performs frequency analysis on the coordinate data of the moving object, and if high-frequency components equal to or greater than a threshold are included, determines that the moving object is an object that should not be detected. For example, the determination unit 122 performs frequency analysis using a Fourier transform on the coordinates of the moving object acquired by the acquisition unit 121, and if high-frequency components equal to or greater than a threshold (2 Hz) are included, estimates that the moving object is an object that should not be detected.

[0081] This allows the monitoring device 100 to determine whether the coordinates of a moving object that should not be detected show characteristic movements or properties, and thereby determine that the moving object is an object that should not be detected that makes repetitive movements in a fixed position.

[0082] 12 to 14. The flowcharts of FIGS. 12 to 14 are executed primarily by the control unit 120. These flowcharts can be configured as a program executed by the CPU of the control unit 120 to create a monitoring program. The steps below can be executed in a different order, and some steps may be omitted.

[0083] 12, the monitoring device 100 determines that a moving object is an object that should not be detected by using a method that uses the sum of the movement amounts of each point relative to the movement amount between the start point and the end point. First, the acquisition unit 121 acquires the coordinates of the moving object identified based on information detected by a moving object sensor installed in the vehicle (step S201). For example, the acquisition unit 121 acquires the coordinates of the moving object identified from information on the distance and angle detected by the moving object sensor.

[0084] Next, the determination unit 122 determines whether the value obtained by dividing the total amount of movement of the coordinates of the moving object acquired by the acquisition unit 121 over a predetermined period by the amount of movement of the coordinates of the moving object between the start point and the end point over the predetermined period is equal to or greater than a threshold (step S202). For example, the determination unit 122 determines whether the value calculated using Equation 1 is equal to or greater than the threshold, and whether the value calculated using Equation 2 is equal to or greater than the threshold. Here, if the determination unit 122 determines that the total amount of movement is not equal to or greater than the threshold (step S202 "No"), the process returns to step S201.

[0085] On the other hand, if the determination unit 122 determines that the distance is equal to or greater than the threshold value (step S202 "Yes"), the determination unit 122 determines whether the distance between the moving object and the moving object sensor is less than the threshold value (step S203). Here, if the determination unit 122 determines that the distance is not less than the threshold value (step S203 "No"), the process returns to step S201 again.

[0086] On the other hand, if the determination unit 122 determines that the moving object is less than the threshold value ("Yes" in step S203), the determination unit 122 determines that the moving object is an object that should not be detected (step S204). Subsequently, the change unit 123 changes the setting of the moving object sensor (step S205). For example, the change unit 123 lowers the receiving sensitivity for signals from the coordinate direction of the moving object determined to be an object that should not be detected.

[0087] Next, the procedure for the monitoring device 100 to determine that a moving object is an object that should not be detected by using the method of summing the amount of movement in a predetermined position coordinate area will be described with reference to Figure 13. First, the acquisition unit 121 acquires the coordinates of the moving object identified based on information detected by a moving object sensor installed in the vehicle (step S301). For example, the acquisition unit 121 acquires the coordinates of the moving object identified from information on the distance and angle detected by the moving object sensor.

[0088] Next, the determination unit 122 determines whether the value obtained by dividing the total amount of movement of the coordinates of the moving object acquired by the acquisition unit 121 over a predetermined period by the square root of the sum of the square of the difference between the maximum and minimum X coordinates of the moving object over the predetermined period and the square of the difference between the maximum and minimum Y coordinates of the moving object over the predetermined period is equal to or greater than a threshold (step S302). For example, the determination unit 122 determines whether the value calculated using Equation 3 is equal to or greater than a threshold. If the determination unit 122 determines that the value is not equal to or greater than the threshold (step S302 "No"), the process returns to step S301.

[0089] On the other hand, if the determination unit 122 determines that the distance is equal to or greater than the threshold value (step S302 "Yes"), the determination unit 122 determines whether the distance between the moving object and the moving object sensor is less than the threshold value (step S303). If the determination unit 122 determines that the distance is not less than the threshold value (step S303 "No"), the process returns to step S301.

[0090] On the other hand, if the determination unit 122 determines that the moving object is less than the threshold value ("Yes" in step S303), the determination unit 122 determines that the moving object is an object that should not be detected (step S304). Subsequently, the change unit 123 changes the setting of the moving object sensor (step S305). For example, the change unit 123 lowers the receiving sensitivity for signals from the coordinate direction of the moving object determined to be an object that should not be detected.

[0091] Next, the process steps of the monitoring device 100 for determining, through frequency analysis, that a moving object is an object that should not be detected will be described with reference to Fig. 14. First, the acquisition unit 121 acquires the coordinates of the moving object identified based on information detected by a moving object sensor provided in the vehicle (step S401). For example, the acquisition unit 121 acquires the coordinates of the moving object identified from information on the distance and angle detected by the moving object sensor.

[0092] Next, the determination unit 122 performs frequency analysis on the coordinate data of the moving object (step S402). For example, the determination unit 122 performs frequency analysis on the coordinate data of the moving object using a Fourier transform. Next, the determination unit 122 determines whether the coordinate data of the moving object contains high-frequency components (step S403). For example, the determination unit 122 determines whether the coordinate data of the moving object subjected to frequency analysis contains high frequencies equal to or greater than a predetermined threshold. Here, if the determination unit 122 determines that the frequency is not equal to or greater than the threshold (step S403 "No"), the process returns to step S401.

[0093] On the other hand, if the determination unit 122 determines that a high-frequency component is included ("Yes" in step S403), the determination unit 122 determines whether the distance between the moving object and the moving object sensor is less than the threshold value (step S404). If the determination unit 122 determines that the distance is not less than the threshold value ("No" in step S404), the process returns to step S401.

[0094] On the other hand, if the determination unit 122 determines that the moving object is less than the threshold value ("Yes" in step S404), the determination unit 122 determines that the moving object is an object that should not be detected (step S405). Subsequently, the change unit 123 changes the setting of the moving object sensor (step S406). For example, the change unit 123 lowers the receiving sensitivity for signals from the coordinate direction of the moving object determined to be an object that should not be detected.

[0095] 4. Effects The monitoring device 100 according to the embodiment includes an acquisition unit 121 that acquires coordinates of a moving object identified based on information detected by a moving object sensor provided inside the vehicle, and a determination unit 122 that determines whether the moving object is an object that should not be detected, based on the coordinates of the moving object acquired by the acquisition unit 121.

[0096] This allows the monitoring device 100 to accurately determine whether an object should not be detected based on the coordinates of the moving object. That is, by determining whether characteristic movements or properties are observed in the coordinates of the moving object, the monitoring device 100 can determine that the moving object is an object that makes repetitive movements in a fixed position and should not be detected.

[0097] The determination unit 122 of the monitoring device 100 according to the embodiment determines that the moving object is an object that should not be detected when the value obtained by dividing the total amount of movement of the coordinates of the moving object in a predetermined period acquired by the acquisition unit 121 by the amount of movement of the coordinates of the moving object between the start point and the end point in the predetermined period is equal to or greater than a threshold. As a result, the monitoring device 100 can accurately determine whether the object is an object that should not be detected by performing threshold determination on the value obtained by dividing the total amount of movement by the amount of movement of the coordinates between the start point and the end point.

[0098] The determination unit 122 of the monitoring device 100 according to the embodiment determines that the moving object is an object that should not be detected if the value obtained by dividing the total amount of movement of the coordinates of the moving object acquired by the acquisition unit 121 over a specified period by the square root of the sum of the square of the difference between the maximum and minimum values ​​of the X coordinates of the moving object over the specified period and the square of the difference between the maximum and minimum values ​​of the Y coordinates of the moving object over the specified period is equal to or greater than a threshold value.

[0099] As a result, the monitoring device 100 performs a threshold judgment on the value obtained by dividing the total movement amount by the square root of the sum of the squares of the differences between the maximum and minimum values ​​for each coordinate axis, thereby evaluating the movement distance of each point without separating the X and Y coordinates, and can accurately determine objects that should not be detected.

[0100] The determination unit 122 of the monitoring device 100 according to the embodiment performs frequency analysis on the coordinates of the moving object acquired by the acquisition unit 121, and if a high-frequency component is included, determines that the moving object is an object that should not be detected. In this way, the monitoring device 100 can accurately determine whether the data on the coordinates of the moving object that has been subjected to frequency analysis includes a high frequency that is equal to or greater than a predetermined threshold.

[0101] The determination unit 122 of the monitoring device 100 according to the embodiment further determines that the moving object is an object that should not be detected if the distance between the moving object and the moving object sensor is less than a threshold value. This allows the monitoring device 100 to accurately determine whether the moving object has characteristic movements or properties in its coordinates and whether the distance between the moving object and the moving object sensor is less than a threshold value.

[0102] The monitoring device 100 according to the embodiment further includes a change unit 123 that changes the settings of the motion sensor when it is determined that a moving object is an object that should not be detected. As a result, the monitoring device 100 reduces the reception sensitivity of signals from a moving object determined to be an object that should not be detected, thereby preventing signals from moving objects that do not need to be monitored from being received, and can receive signals from other positions and directions without turning off the power of the motion sensor to continuously perform determination processing, thereby accurately determining objects that should not be detected.

[0103] [Others] [1. Hardware Configuration] The monitoring device 100 according to the above-described embodiment is realized, for example, by a computer 1000 configured as shown in Fig. 11. Fig. 11 is a hardware configuration diagram showing an example of a computer that realizes the functions of the monitoring device 100. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, a HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0104] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0105] The HDD 1400 stores programs executed by the CPU 1100 and data used by the programs. The communication interface 1500 receives data from other devices via a predetermined communication network and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0106] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0107] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1200. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0108] For example, when the computer 1000 functions as the monitoring device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200 to realize the functions of the control unit 120. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0109] [2. Other] While one example of an embodiment of the present invention has been described above, the present invention is not limited to the above example. In other words, a person skilled in the art can implement various modifications in accordance with conventionally known knowledge without departing from the gist of the present invention. As long as such modifications still comprise the monitoring device of the present invention, they are of course included in the scope of the present invention.

[0110] REFERENCE SIGNS LIST 1 monitoring system 10 in-vehicle device 100 monitoring device 110 communication unit 120 control unit 121 acquisition unit 122 determination unit 123 change unit 130 storage unit

Claims

1. A monitoring device comprising: an acquisition unit that acquires the strength of a signal received by a motion sensor installed in a vehicle and the coordinates of a moving object identified based on information detected by the motion sensor; and a determination unit that determines that the moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition unit is less than a threshold value and the standard deviation of the moving distance is less than a threshold value.

2. The monitoring device according to claim 1, characterized in that the determination unit further determines that the moving object is an object that should not be detected when the distance between the moving object and the moving object sensor is less than a threshold value.

3. The monitoring device according to claim 1, further comprising a change unit which changes the settings of the motion sensor when the determination unit determines that the moving object is an object that should not be detected.

4. A method executed by a monitoring device, comprising: an acquisition step of acquiring, by a motion sensor installed in a vehicle, the strength of a signal received and the coordinates of a moving object identified based on information detected by the motion sensor; and a determination step of determining that the moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition step is less than a threshold value and the standard deviation of the moving distance is less than a threshold value.

5. A monitoring program that causes a computer to execute the following steps: an acquisition step of acquiring, by a motion sensor installed in a vehicle, the strength of a signal received and the coordinates of a moving object identified based on information detected by the motion sensor; and a determination step of determining that the moving object is an object that should not be detected if the standard deviation of the signal strength acquired by the acquisition step is less than a threshold value and the standard deviation of the moving distance is less than a threshold value.

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