Monitoring system, monitoring device, monitoring method, and program

Abstract

Provided is a technology for easily identifying a mutual correspondence relationship between a plurality of signal strength distributions. Provided is a monitoring system comprising: a signal strength distribution generation means for generating, for each of a plurality of optical fiber cables disposed at intervals, a signal strength distribution of backscattered light in the longitudinal direction of the optical fiber cables by causing pulsed light to enter the plurality of optical fiber cables and receiving the backscattered light of the plurality of optical fiber cables; an aggregation means for aggregating the plurality of signal strength distributions into one to generate an aggregated signal strength distribution; a spectrogram generation means for generating a spectrogram on the basis of the aggregated signal strength distribution; and an output means for outputting the spectrogram.

Description

Monitoring system, monitoring device, monitoring method, and program

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

[0002] As a means for monitoring vibrations and temperature changes of a monitoring target, distributed fiber optic sensing technology is known. Distributed fiber optic sensing technology is a technology that uses an optical fiber cable itself as a sensor to measure vibrations and temperature changes of a monitoring target.

[0003] Specifically, a sensing device connected to an optical fiber cable injects a pulse signal into the optical fiber cable. When the pulse signal propagates through the optical fiber cable, backscattered light is generated. The sensing device receives this backscattered light for each pulse transmission interval. When vibrations or temperature changes occur in the optical fiber cable, the backscattered light received by the sensing device changes. The sensing device estimates the position of the vibrations or temperature changes that occurred in the optical fiber cable based on the time from when the pulse signal was injected until the change in the backscattered light is detected. Also, when the sensing device measures vibrations using an optical fiber cable, it analyzes the amplitude fluctuations of Rayleigh scattered light among the backscattered light. This type of technology is also called DAS (Distributed Acoustic Sensor).

[0004] The measurement results of the vibration distribution using an optical fiber cable are typically visualized using a spectrogram. As an example, the horizontal axis of the spectrogram indicates the distance from the sensing device, the vertical axis is the time axis, and the color of each pixel indicates the vibration intensity.

[0005] Patent Document 1 discloses a technique for detecting a person walking in a zigzag pattern on a platform by providing a plurality of optical fibers on the platform of a station.

[0006] Japanese Unexamined Patent Application Publication No. 2024-092385

[0007] Incidentally, there have been numerous cases of drug trafficking and other illegal activities across national borders. In particular, some countries have areas such as remote desert regions where there are no physical barriers such as fences or walls along the border, and it is necessary to understand the actual situation of border crossings in such areas.

[0008] The targets of surveillance are moving objects such as people and vehicles, while the surveillance area spans hundreds of kilometers. There are extremely limited methods for monitoring moving objects while covering such a wide area at a realistic cost.

[0009] For example, low-Earth orbit satellites equipped with visible light or near / far infrared cameras can detect moving objects over a wide area, but satellites are not always positioned over national borders, so monitoring opportunities are limited.

[0010] One effective method is the aforementioned DAS (Data Acquisition System). Specifically, by installing optical fiber sensors, including optical fibers, along border fences and walls, it is possible to monitor a section of the border spanning tens of kilometers without power supply. In cases where there are fences or walls along the border, smuggling takes place near the fence or wall, causing moving objects to remain in the vicinity for a certain period of time, and thus enabling highly reliable detection of these moving objects.

[0011] On the other hand, if there are no physical barriers such as fences or walls along the border, moving objects will cross the border in a short amount of time. Even if fiber optic sensors are installed along the border, it will be difficult to distinguish the detection results of moving objects from noise.

[0012] Therefore, it is conceivable to configure the optical fiber sensor using multiple optical fiber cables. In this case, it would be possible to detect moving objects crossing national borders multiple times in a short period of time, making it relatively easy to distinguish the detection results from noise.

[0013] In this case, it is conceivable to visualize the signal intensity distribution of backscattered light for each of the multiple optical fiber cables using a spectrogram. Specifically, it is conceivable to generate a spectrogram for each of the multiple optical fiber cables and compare the generated spectrograms side by side. This is expected to allow for a multifaceted understanding of the movement of a moving object crossing a national border, including the crossing point, crossing angle, and crossing speed.

[0014] However, when comparing multiple spectrograms side by side, there was a problem in that it was difficult to grasp the correspondence between the signal intensity distributions of backscattered light across the multiple spectrograms.

[0015] Therefore, the purpose of this disclosure is to provide a technology that makes it easy to understand the correspondence between multiple signal intensity distributions.

[0016] A monitoring system is provided, which includes: a signal intensity distribution generation means that generates a signal intensity distribution of backscattered light in the longitudinal direction of each of the multiple optical fiber cables by injecting pulsed light into multiple optical fiber cables arranged at intervals and receiving backscattered light from the multiple optical fiber cables; an aggregation means that aggregates the multiple signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram.

[0017] A monitoring device is provided, which includes: a signal intensity distribution generation means that incident pulsed light onto multiple optical fiber cables arranged at intervals and receives the backscattered light from the multiple optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each of the multiple optical fiber cables; an aggregation means that aggregates the multiple signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram.

[0018] A monitoring method is provided, in which a computer incidents pulsed light onto multiple optical fiber cables arranged at intervals and receives backscattered light from the multiple optical fiber cables, generates a signal intensity distribution of the backscattered light in the longitudinal direction of each of the multiple optical fiber cables, aggregates the multiple signal intensity distributions into one to generate an aggregated signal intensity distribution, generates a spectrogram based on the aggregated signal intensity distribution, and outputs the spectrogram.

[0019] A program is provided that causes a computer to function as: a signal intensity distribution generation means that generates a signal intensity distribution of backscattered light in the longitudinal direction of each of the multiple optical fiber cables by injecting pulsed light into multiple optical fiber cables arranged at intervals and receiving the backscattered light from the multiple optical fiber cables; an aggregation means that aggregates the multiple signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram.

[0020] According to this disclosure, the correspondence between multiple signal intensity distributions can be easily understood.

[0021] This is a block diagram of the monitoring system. This is the operation flow of the monitoring system. This is a schematic diagram of the monitoring system. This is a block diagram of the monitoring device. This is an explanatory diagram of the aggregation of signal intensity distribution. This is an example of spectrogram output. This is an example of behavior estimation result output. This is the operation flow of the monitoring device. This is an explanatory diagram of the aggregation of signal intensity distribution. This is an explanatory diagram of the aggregation of signal intensity distribution. This is an explanatory diagram of the aggregation of signal intensity distribution. This is an explanatory diagram of the aggregation of signal intensity distribution. This is a schematic diagram of the monitoring system. This is an example of spectrogram output. This is an example of behavior estimation result output. This is a block diagram illustrating the hardware configuration of a computer.

[0022] (Summary of this disclosure) First, an overview of this disclosure will be provided. Figure 1 is a block diagram of the monitoring system 100. As shown in Figure 1, the monitoring system 100 includes a signal intensity distribution generation means 101, an aggregation means 102, a spectrogram generation means 103, and an output means 104.

[0023] The signal intensity distribution generation means 101 generates a signal intensity distribution of the backscattered light in the longitudinal direction of each optical fiber cable by injecting pulsed light into a plurality of optical fiber cables arranged at intervals and receiving the backscattered light from the plurality of optical fiber cables.

[0024] The aggregation means 102 aggregates multiple signal intensity distributions into one to generate an aggregated signal intensity distribution.

[0025] The spectrogram generation means 103 generates a spectrogram based on the aggregated signal intensity distribution.

[0026] The output means 104 outputs a spectrogram.

[0027] Next, the operation of the monitoring system 100 will be explained. Figure 2 shows the operation flow of the monitoring system 100. As shown in Figure 2, first, the signal intensity distribution generation means 101 incidents pulsed light onto a plurality of optical fiber cables arranged at intervals and receives the backscattered light from the plurality of optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each optical fiber cable (S101). Next, the aggregation means 102 aggregates the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution (S102). Next, the spectrogram generation means 103 generates a spectrogram based on the aggregated signal intensity distribution (S103). Finally, the output means 104 outputs the spectrogram (S104).

[0028] With the above configuration, the correspondence between multiple signal intensity distributions can be easily understood.

[0029] The present invention will be described below through embodiments of the invention, but the invention claimed is not limited to the following embodiments. Furthermore, not all of the configurations described in the embodiments are necessarily essential as means of solving the problem. For clarity of explanation, the following descriptions and drawings have been omitted and simplified as appropriate. In each drawing, the same elements are denoted by the same reference numerals, and redundant explanations have been omitted where necessary.

[0030] In the following embodiments, the description will be divided into multiple sections or embodiments where necessary for convenience. Unless otherwise specified, these are not unrelated, and one may be a modification, application, detailed explanation, or supplementary explanation of part or all of the other. Furthermore, in the following embodiments, when referring to the number of elements (including number, numerical value, quantity, and range), unless otherwise specified or clearly limited to a specific number in principle, it is not limited to that specific number, and may be greater than or less than that number.

[0031] Furthermore, in the following embodiments, the components (including operation steps, etc.) are not necessarily essential unless specifically stated or considered to be clearly essential in principle. Similarly, in the following embodiments, when referring to the shape or positional relationship of components, etc., it shall include those substantially similar to or resembling their shape, etc., unless specifically stated or considered to be not in principle. The same applies to the numbers, etc. (including the number of items, numerical values, quantities, and ranges) mentioned above.

[0032] (First Embodiment) Next, a first embodiment of the present disclosure will be described. Figure 3 is a schematic diagram of the monitoring system 1.

[0033] As shown in Figure 3, in this embodiment, the monitoring system 1 includes an optical fiber sensor 3 positioned along the border 2 and a monitoring device 4.

[0034] In this embodiment, the border 2 is located in a desert area, for example. No barriers such as fences or walls are provided along the border 2. However, this is not limited to this, and barriers may be provided along the border 2.

[0035] The optical fiber sensor 3 is installed to extend along the border 2. The optical fiber sensor 3 is composed of a plurality of optical fiber cables 5. In this embodiment, the plurality of optical fiber cables 5 include a first optical fiber cable 5a and a second optical fiber cable 5b. The first optical fiber cable 5a and the second optical fiber cable 5b are spaced apart. The first optical fiber cable 5a and the second optical fiber cable 5b extend parallel to each other. That is, the distance D between the first optical fiber cable 5a and the second optical fiber cable 5b is constant. The first optical fiber cable 5a is closer to the border 2 than the second optical fiber cable 5b.

[0036] In this embodiment, for the sake of explanation, it is assumed that the vehicle 6 crosses the border 2 and the optical fiber sensor 3 in the order described. Therefore, after crossing the border 2, the vehicle 6 first crosses the first optical fiber cable 5a, and then crosses the second optical fiber cable 5b. If there is no barrier or road along the border 2, the vehicle 6 travels in a straight line connecting the starting point and the destination. Therefore, the vehicle 6 typically crosses the border 2 and the optical fiber sensor 3 diagonally. That is, the crossing angle θ, which is the angle between the direction of travel of the vehicle 6 and the longitudinal direction of the optical fiber sensor 3, satisfies the relationship 0 < θ < 90. Figure 3 shows both the crossing point 7a where the vehicle 6 crosses the first optical fiber cable 5a and the crossing point 7b where the vehicle 6 crosses the second optical fiber cable 5b. The vehicle 6 is one specific example of a moving object. The moving object is not limited to the vehicle 6, but may be a person traveling on foot or on horseback, or an unmanned aerial vehicle such as a drone.

[0037] The monitoring device 4 is connected to the optical fiber sensor 3. The monitoring device 4 uses the optical fiber sensor 3 to detect vehicles 6 crossing the optical fiber sensor 3. Specifically, the monitoring device 4 uses the optical fiber sensor 3 to detect or estimate the crossing point, crossing angle θ, and crossing speed of vehicles 6 crossing the optical fiber sensor 3. The crossing point, crossing angle θ, and crossing speed are also referred to as the crossing pattern. The crossing pattern includes at least one of the crossing point, crossing angle θ, and crossing speed. In this embodiment, the crossing pattern includes the crossing point, crossing angle θ, and crossing speed. The monitoring device 4 is implemented by a single device. However, it is not limited to this, and the monitoring device 4 may be implemented by distributed processing using multiple devices.

[0038] Figure 4 shows a block diagram of the monitoring device 4. As shown in Figure 4, the monitoring device 4 includes a map data storage unit 10, a detection data storage unit 11, an aggregated data storage unit 12, a signal intensity distribution generation unit 13, an aggregation unit 14, a spectrogram generation unit 15, a cross-sectional pattern estimation unit 16, a spectrogram output unit 17, a behavior estimation unit 18, and a map output unit 19.

[0039] The map data storage unit 10 stores map data. The map data shows the locations of multiple settlements, roads, national borders, fiber optic sensors 3, and other locations in a geographic coordinate system. A settlement includes cities, towns, and villages. In the map data, roads, national borders, and fiber optic sensors 3 are typically defined by multiple nodes and multiple links connecting those nodes.

[0040] The detection data storage unit 11 stores the signal intensity distribution generated by the signal intensity distribution generation unit 13.

[0041] The aggregated data storage unit 12 stores the aggregated signal intensity distribution generated by the aggregation unit 14.

[0042] The signal intensity distribution generation unit 13 emits pulsed light to a plurality of optical fiber cables 5 arranged at intervals, and receives the backward scattered light of the plurality of optical fiber cables 5, thereby generating, for each of the plurality of optical fiber cables 5, the signal intensity distribution of the backward scattered light in the longitudinal direction of the optical fiber cable 5. The signal intensity distribution generation unit 13 is a specific example of the signal intensity distribution generation means.

[0043] Specifically, at time t0, the signal intensity distribution generation unit 13 simultaneously emits pulsed light to the plurality of optical fiber cables 5. Next, the signal intensity distribution generation unit 13 receives, for each of the plurality of optical fiber cables 5, the backward scattered light caused by the pulsed light incident at time t0. The signal intensity distribution generation unit 13 generates, for each of the plurality of optical fiber cables 5, the signal intensity distribution of the backward scattered light in the longitudinal direction of the optical fiber cable 5 based on the Rayleigh scattered light having the same wavelength as the pulsed light among the received backward scattered light. Similarly, the signal intensity distribution generation unit 13 repeats the generation of the signal intensity distribution at times t1, t2,.... Thus, the signal intensity distribution generation unit 13 repeats the generation of the signal intensity distribution at a predetermined time interval and for each of the plurality of optical fiber cables 5. The signal intensity distribution generation unit 13 stores the generated plurality of signal intensity distributions in the detection data storage unit 11. As a result, the detection data storage unit 11 stores a plurality of signal intensity distributions corresponding to time t0, a plurality of signal intensity distributions corresponding to time t1, a plurality of signal intensity distributions corresponding to time t2,....

[0044] In this embodiment, the signal intensity distribution generation unit 13 generates a signal intensity distribution of backscattered light in the longitudinal direction of the optical fiber cable 5 based on Rayleigh scattered light of the same wavelength as the pulsed light among the received backscattered light. Therefore, this signal intensity distribution corresponds to the vibration distribution in the longitudinal direction of the corresponding optical fiber cable 5. The vibration distribution can also be called a vibration intensity distribution or amplitude distribution. When a vehicle 6 crosses the optical fiber sensor 3, local vibrations occur in multiple optical fiber cables 5, so by focusing on Rayleigh scattered light among the backscattered light, it is possible to suitably detect that a vehicle 6 has crossed the optical fiber sensor 3. However, the signal intensity distribution generation unit 13 may also generate a signal intensity distribution of backscattered light in the longitudinal direction of the optical fiber cable 5 based on Raman scattered light among the received backscattered light. In this case, this signal intensity distribution corresponds to the temperature change distribution in the longitudinal direction of the corresponding optical fiber cable 5.

[0045] The aggregation unit 14 aggregates multiple signal intensity distributions into one to generate an aggregated signal intensity distribution. The aggregation unit 14 is one specific example of an aggregation means. The aggregation unit 14 reads multiple signal intensity distributions corresponding to time t0 from the detection data storage unit 11 and generates an aggregated signal intensity distribution by adding the multiple signal intensity distributions. This aggregation method will be specifically explained with reference to Figure 5. In Figure 5, (a) is a graph of the signal intensity distribution of the first optical fiber cable 5a corresponding to time t0, (b) is a graph of the signal intensity distribution of the second optical fiber cable 5b corresponding to time t0, and (c) is a graph of the aggregated signal intensity distribution corresponding to time t0. In each graph in Figure 5, the horizontal axis represents the position of the optical fiber sensor 3 in the longitudinal direction, and the vertical axis represents the signal intensity. As shown in Figure 5, in this embodiment, the aggregated signal intensity distribution (c) is generated by simply adding the signal intensity distribution of (a) and the signal intensity distribution of (b). Similarly, the aggregation unit 14 repeatedly performs the above aggregation process on multiple signal intensity distributions corresponding to time t1, multiple signal intensity distributions corresponding to time t2, and so on. The aggregation unit 14 stores the generated multiple aggregated signal intensity distributions in the aggregated data storage unit 12. As a result, the aggregated data storage unit 12 stores the aggregated signal intensity distribution corresponding to time t0, the aggregated signal intensity distribution corresponding to time t1, the aggregated signal intensity distribution corresponding to time t2, and so on.

[0046] The spectrogram generation unit 15 reads a plurality of aggregated signal intensity distributions from the aggregated data storage unit 12 and generates a spectrogram based on the plurality of aggregated signal intensity distributions. The spectrogram generation unit 15 is a specific example of the spectrogram generation means. FIG. 6 is an output example of the spectrogram. In FIG. 6, the horizontal axis of the spectrogram is the position in the longitudinal direction of the optical fiber sensor 3, and the vertical axis is time. The shading of the pixels of the spectrogram indicates the signal intensity. Relatively dark pixels mean that the signal intensity is relatively high, and relatively light pixels mean that the signal intensity is relatively low. The pixels of the spectrogram are updated at a predetermined time interval so that the pixels of the spectrogram move upward with the passage of time. Therefore, the latest aggregated signal intensity distribution is displayed at the bottom end of the spectrogram, and the oldest aggregated signal intensity distribution is displayed at the top end of the spectrogram. Also, the oldest aggregated signal intensity distribution displayed at the top end of the spectrogram will be pushed out simultaneously when a new aggregated signal intensity distribution is displayed at the bottom end of the spectrogram.

[0047] In the spectrogram of FIG. 6, there are two relatively dark regions. The region 8a where the position in the longitudinal direction of the optical fiber sensor 3 is about 38 meters is due to the signal intensity distribution corresponding to the first optical fiber cable 5a and corresponds to the crossing point 7a in FIG. 3. The region 8b where the position in the longitudinal direction of the optical fiber sensor 3 is about 50 meters is due to the signal intensity distribution corresponding to the second optical fiber cable 5b and corresponds to the crossing point 7b in FIG. 3. As time passes, the regions 8a and 8b move straight up on the spectrogram. Since the vehicle 6 passes through the crossing point 7b after passing through the crossing point 7a, the region 8a is displayed on the spectrogram earlier than the region 8b and is pushed out of the spectrogram earlier than the region 8b. Also, as shown in FIG. 3, the vehicle 6 crosses the optical fiber sensor 3 obliquely, and the distance L1 between the crossing point 7a and the monitoring device 4 is shorter than the distance L2 between the crossing point 7b and the monitoring device 4. Therefore, as shown in FIG. 6, the region 8a corresponding to the crossing point 7a is always located on the left side of the region 8b corresponding to the crossing point 7b.

[0048] A spectrogram is sometimes also called a waterfall plot.

[0049] The crossing pattern estimation unit 16 estimates the crossing pattern when the vehicle 6 crosses the optical fiber sensor 3 based on multiple signal intensity distributions. The crossing pattern estimation unit 16 is one specific example of a crossing pattern estimation means.

[0050] Specifically, as shown in Figure 3, the crossing pattern estimation unit 16 identifies the crossing point 7a and the time of crossing when the vehicle 6 crossed the first optical fiber cable 5a by analyzing a plurality of signal intensity distributions corresponding to the first optical fiber cable 5a (the plurality of signal intensity distributions are generated by the signal intensity distribution generation unit 13 at predetermined time intervals). Similarly, the crossing pattern estimation unit 16 identifies the crossing point 7b and the time of crossing when the vehicle 6 crossed the second optical fiber cable 5b by analyzing a plurality of signal intensity distributions corresponding to the second optical fiber cable 5b.

[0051] Next, the crossing pattern estimation unit 16 estimates the crossing angle θ when the vehicle 6 crosses the optical fiber sensor 3, based on crossing points 7a and 7b. Specifically, the crossing pattern estimation unit 16 estimates the crossing angle θ using trigonometric functions based on the difference ΔL between distance L1 and distance L2, and the aforementioned distance D. As an example, as shown in Figure 3, if the crossing angle θ is defined as the angle between the orthogonal direction perpendicular to the longitudinal direction of the second optical fiber cable 5b and the direction of travel of the vehicle 6, the crossing pattern estimation unit 16 can determine the crossing angle θ using arctan(ΔL / D).

[0052] Next, the crossing pattern estimation unit 16 estimates the crossing speed v when the vehicle 6 crosses the optical fiber sensor 3, based on the crossing point 7a and its crossing time, and the crossing point 7b and its crossing time. Specifically, the crossing speed v can be estimated by the following formula. However, in the following formula, t ａ This is the time of crossing at crossing point 7a, and t ｂ This is the time of crossing at crossing point 7b.

[0053] Next, the spectrogram output unit 17 outputs the spectrogram generated by the spectrogram generation unit 15. The spectrogram output unit 17 is one specific example of an output means. The spectrogram output unit 17 may output the spectrogram to a display device provided by the monitoring device 4, or it may output the spectrogram to an external device connected to the monitoring device 4. This makes it easier to understand the correspondence between multiple signal intensity distributions compared to the case where a spectrogram is generated for each of the multiple optical fiber cables 5 and displayed side by side.

[0054] In this embodiment, as shown in Figure 6, the spectrogram output unit 17 outputs the cross-sectional pattern of the vehicle 6 estimated by the cross-sectional pattern estimation unit 16 superimposed on the spectrogram in vector format. Specifically, the spectrogram output unit 17 outputs a vector icon 20 superimposed on the spectrogram based on the cross-sectional pattern of the vehicle 6 estimated by the cross-sectional pattern estimation unit 16. Here, as an example, the cross-sectional pattern estimation unit 16 sets the starting point of the vector icon 20 to the region 8a corresponding to the crossing point 7a, sets the inclination of the vector icon 20 with respect to the vertical axis to the crossing angle θ, and determines the length of the vector icon 20 according to the crossing speed v. This makes it possible to simultaneously read the cross-sectional pattern of the vehicle 6 on the spectrogram.

[0055] The behavior estimation unit 18 estimates the azimuth angle of the vehicle 6's movement, the vehicle 6's departure point, the vehicle 6's destination, and the time of arrival of the vehicle 6 at its destination, based on the crossing pattern estimated by the crossing pattern estimation unit 16. The behavior estimation unit 18 is one specific example of a behavior estimation means.

[0056] The motion estimation unit 18 calculates the azimuth angle of movement, which is the azimuth angle of vehicle 6's movement when it crosses the optical fiber sensor 3, based on the crossing angle θ and map data. Specifically, the motion estimation unit 18 obtains the longitudinal azimuth angle of the link containing the crossing point 7a of the first optical fiber cable 5a based on the map data, and calculates the azimuth angle of movement of vehicle 6 when it crosses the optical fiber sensor 3 by adding the crossing angle θ to the longitudinal azimuth angle of the link.

[0057] Next, the behavior estimation unit 18 calculates the geographic coordinates of the crossing point 7a based on the distance L1 between the monitoring device 4 and the crossing point 7a and the map data.

[0058] Next, the behavior estimation unit 18 estimates the starting point and destination of the vehicle 6 based on the geographic coordinates of the crossing point 7a and the azimuth angle of the vehicle 6. Specifically, the behavior estimation unit 18 assumes that the vehicle 6 moves in a straight line from the starting point to the destination, estimates the linear movement trajectory of the vehicle 6 with the crossing point 7a as a passing point based on the azimuth angle of the vehicle 6, and extracts settlements located along the movement trajectory as the starting point and destination. Of the settlements located along the movement trajectory, the settlements where the vehicle 6 could have been located before the vehicle 6 crossed the optical fiber sensor 3 are the starting points, and the settlements that the vehicle 6 could reach after the vehicle 6 crossed the optical fiber sensor 3 are the destinations.

[0059] Furthermore, the behavior estimation unit 18 calculates the distance between the crossing point 7a and the destination based on map data, and estimates the time the vehicle 6 will arrive at the destination by adding the time obtained by dividing the distance by the crossing speed v to the crossing time at the crossing point 7a.

[0060] In addition, when the behavior estimation unit 18 estimates the departure point, destination, and arrival time at the destination of the vehicle 6, it typically uses the first optical fiber cable 5a and crossing point 7a as references. However, it is not limited to these, and the behavior estimation unit 18 may also estimate the departure point, destination, and arrival time at the destination of the vehicle 6 using the second optical fiber cable 5b and crossing point 7b as references. This is because, in practice, crossing point 7a and crossing point 7b are only a few meters apart.

[0061] The map output unit 19 generates a map superimposed image by superimposing the estimation results from the action estimation unit 18 onto the map, and outputs the generated map superimposed image. The map output unit 19 is one specific example of a map output means. The map output unit 19 may output the map superimposed image to a display device provided by the monitoring device 4, or it may output the map superimposed image to an external device connected to the monitoring device 4. Figure 7 shows an example of a map superimposed image M. As shown in Figure 7, as an example, the map m shown by the map data includes a settlement p, a road q, and a national border 2. The map output unit 19 determines the direction and magnitude of the vehicle 6's movement vector g based on the vehicle 6's movement azimuth angle and the vehicle 6's crossing speed v, and draws the movement vector g on the map m, for example, in the form of a white arrow. The vehicle 6's movement vector g is an example of the estimation result from the action estimation unit 18.

[0062] Furthermore, the map output unit 19 displays the destination d estimated by the behavior estimation unit 18 as a circle, and also displays the estimated arrival time to the destination d near the destination d. This allows for proactive measures against illegally crossing vehicles 6, such as strengthening the surveillance network around the destination d.

[0063] Next, the operation of the monitoring device 4 will be explained with reference to Figure 8. First, the signal intensity distribution generation unit 13 incidents pulsed light onto a plurality of optical fiber cables 5 arranged at intervals and receives backscattered light from the plurality of optical fiber cables 5 to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each optical fiber cable 5 (S200). Next, the aggregation unit 14 aggregates the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution (S210). Next, the spectrogram generation unit 15 generates a spectrogram based on the plurality of aggregated signal intensity distributions (S220). Next, the crossing pattern estimation unit 16 estimates the crossing pattern when the vehicle 6 crosses the optical fiber sensor 3 based on the plurality of signal intensity distributions (S230). Next, the spectrogram output unit 17 outputs the spectrogram generated by the spectrogram generation unit 15 (S240). Next, the motion estimation unit 18 estimates the azimuth angle of the vehicle 6's movement, the vehicle 6's starting point, the vehicle 6's destination, and the time of arrival of the vehicle 6 at its destination based on the crossing pattern estimation unit 16 (S250). Then, the map output unit 19 superimposes the estimation results from the motion estimation unit 18 onto the map m to generate a map superimposed image M, outputs the generated map superimposed image M (S260), and returns the process to step S200.

[0064] The first embodiment of this disclosure has been described above. The above embodiment has the following features.

[0065] The monitoring device 4 includes a signal intensity distribution generation unit 13 (signal intensity distribution generation means), an aggregation unit 14 (aggregation means), a spectrogram generation unit 15 (spectrogram generation means), and a spectrogram output unit 17 (output means). The signal intensity distribution generation unit 13 generates a signal intensity distribution of the backscattered light in the longitudinal direction of each of the optical fiber cables 5 by incidenting pulsed light onto a plurality of optical fiber cables 5 arranged at intervals and receiving the backscattered light from the plurality of optical fiber cables 5. The aggregation unit 14 aggregates the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution. The spectrogram generation unit 15 generates a spectrogram based on the aggregated signal intensity distribution. The spectrogram output unit 17 outputs a spectrogram. With the above configuration, the correspondence between the plurality of signal intensity distributions can be easily grasped.

[0066] Furthermore, the monitoring device 4 includes a crossing pattern estimation unit 16 (crossing pattern estimation means). The crossing pattern estimation unit 16 estimates the crossing pattern, including the crossing point, crossing angle, and crossing speed, when the vehicle 6 crosses the optical fiber sensor 3, based on a plurality of signal intensity distributions. The spectrogram output unit 17 outputs the crossing pattern superimposed on a spectrogram. With the above configuration, the crossing pattern of the vehicle 6 can be read simultaneously on the spectrogram.

[0067] Furthermore, the spectrogram output unit 17 superimposes the cross-sectional view of the vehicle 6 onto the spectrogram in vector format. With this configuration, the cross-sectional view of the vehicle 6 can be visually read on the spectrogram in a short amount of time.

[0068] Furthermore, the monitoring device 4 further includes a behavior estimation unit 18 (behavior estimation means) that estimates the azimuth angle of the vehicle 6's movement, the vehicle 6's starting point, the vehicle 6's destination, and the time of arrival of the vehicle 6 at its destination, based on the crossing pattern. With the above configuration, tracking of the vehicle 6 is possible.

[0069] (Second Embodiment) Next, a second embodiment of the present disclosure will be described. This embodiment will be described focusing on the differences between it and the first embodiment, and redundant explanations will be omitted.

[0070] In the first embodiment described above, the aggregation unit 14 generates an aggregated signal strength distribution (c) by simply adding the signal strength distribution (a) of the first optical fiber cable 5a and the signal strength distribution (b) of the second optical fiber cable 5b, as shown in Figure 5. In this case, the signal strength caused by the vehicle 6 crossing each signal strength distribution does not change significantly before and after the addition, but the noise included in each signal strength distribution doubles, so the SNR (signal-noise ratio) of the aggregated signal strength distribution decreases.

[0071] In contrast, in this embodiment, the aggregation unit 14 generates an aggregated signal intensity distribution by selecting the maximum value of a plurality of signal intensity distributions for each position in the longitudinal direction of the optical fiber sensor 3. Specifically, please refer to Figure 9. In Figure 9, (a) is a graph of the signal intensity distribution of the first optical fiber cable 5a corresponding to time t0, (b) is a graph of the signal intensity distribution of the second optical fiber cable 5b corresponding to time t0, and (c) is a graph of the aggregated signal intensity distribution corresponding to time t0. In each graph in Figure 9, the horizontal axis represents the position in the longitudinal direction of the optical fiber sensor 3, and the vertical axis represents the signal intensity. As shown in Figure 9, the aggregation unit 14 first focuses on a specific position xi in the longitudinal direction of the optical fiber sensor 3, and extracts the signal intensity of the signal at that position xi from the signal intensity distribution in (a) and the signal intensity distribution in (b). The signal strength of the signal at position xi in the signal strength distribution of (a) is defined as signal strength Sa(xi), and the signal strength of the signal at position xi in the signal strength distribution of (b) is defined as signal strength Sb(xi). The aggregation unit 14 then selects the maximum signal strength from signal strength Sa(xi) and signal strength Sb(xi), and defines the selected signal strength as signal strength Sc(xi) of the signal at position xi in the aggregated signal strength distribution. Similarly, the aggregation unit 14 performs the above aggregation process for each position in the longitudinal direction of the optical fiber sensor 3. Similarly, the aggregation unit 14 performs the same aggregation process for multiple signal strength distributions corresponding to time t1, multiple signal strength distributions corresponding to time t2, ... The aggregation unit 14 stores the generated multiple aggregated signal strength distributions in the aggregated data storage unit 12. As a result, the aggregated signal strength distribution corresponding to time t0, the aggregated signal strength distribution corresponding to time t1, the aggregated signal strength distribution corresponding to time t2, ... are stored in the aggregated data storage unit 12.

[0072] Thus, in this embodiment, the aggregation unit 14 generates an aggregated signal intensity distribution by selecting the maximum value of a plurality of signal intensity distributions for each position in the longitudinal direction of the optical fiber sensor 3. With this configuration, the decrease in the SNR of the aggregated signal intensity distribution can be suppressed compared to the first embodiment.

[0073] (Third Embodiment) Next, a third embodiment of the present disclosure will be described. This embodiment will be described focusing on the differences between it and the first embodiment, and redundant explanations will be omitted.

[0074] In this embodiment, the aggregation unit 14 sets a threshold for each of the multiple signal intensity distributions, assigns a first weight to signals higher than the threshold, assigns a second weight smaller than the first weight to signals lower than the threshold, and generates an aggregated signal intensity distribution by adding the multiple signal intensity distributions together.

[0075] For specifics, please refer to Figures 10 to 12. In Figure 10, (a1) is a graph of the signal strength distribution of the first optical fiber cable 5a corresponding to time t0, and (a2) is a weighted graph of the signal strength distribution of the first optical fiber cable 5a corresponding to time t0. In Figure 11, (b1) is a graph of the signal strength distribution of the second optical fiber cable 5b corresponding to time t0, and (b2) is a weighted graph of the signal strength distribution of the second optical fiber cable 5b corresponding to time t0. In Figure 12, (c) is a graph of the aggregated signal strength distribution corresponding to time t0. In each graph from Figures 10 to 12, the horizontal axis represents the position of the optical fiber sensor 3 in the longitudinal direction, and the vertical axis represents the signal strength. As shown in Figures 10 and 11, in this embodiment, the noise component of the signal intensity distributions of the first optical fiber cable 5a and the second optical fiber cable 5b is compressed in advance, and then an aggregated signal intensity distribution is generated by adding the signal intensity distribution of the first optical fiber cable 5a and the signal intensity distribution of the second optical fiber cable 5b.

[0076] First, the compression process of the aggregation unit 14 for the signal intensity distribution of the first optical fiber cable 5a will be explained with reference to (a1) and (a2) in Figure 10. First, as shown in (a1), the aggregation unit 14 sets a threshold 14a used for the compression process of the signal intensity distribution in (a1). Typically, the threshold 14a is the average value of the signal intensity distribution in (a1). However, it is not limited to this, and the threshold 14a may be the median, mode, or other statistical value of the signal intensity distribution in (a1). Next, as shown in (a2), the aggregation unit 14 assigns a first weight to signals in the signal intensity distribution in (a1) that are higher than the threshold 14a, and assigns a second weight smaller than the first weight to signals that are lower than the threshold 14a. The first weight is typically 1.0. The second weight is typically 0.5. However, the second weight may be 1 for each set of signal intensity distributions aggregated by the aggregation unit 14. In this case, when the number of sets of signal intensity distributions aggregated by the aggregation unit 14 is 3, the second weight is typically 1 / 3.

[0077] Similarly, the compression process of the aggregation unit 14 on the signal intensity distribution of the second optical fiber cable 5b will be explained with reference to (b1) and (b2) of Figure 11. First, as shown in (b1), the aggregation unit 14 sets a threshold 14b used for the compression process on the signal intensity distribution of (b1). Typically, the threshold 14b is the average value of the signal intensity distribution of (b1). However, it is not limited to this, and the threshold 14b may be the median, mode, or other statistical value of the signal intensity distribution of (b1). Next, as shown in (b2), the aggregation unit 14 assigns a first weight to signals in the signal intensity distribution of (b1) that are higher than the threshold 14b, and a second weight to signals that are lower than the threshold 14b. Here, the first and second weights may be the same first and second weights used in the compression process for the signal intensity distribution shown in Figure 10 (a1), or they may be newly determined separately from the first and second weights used in the compression process for the signal intensity distribution shown in Figure 10 (a1).

[0078] The aggregation unit 14 then generates the aggregated signal intensity distribution shown in Figure 12(c) by adding the weighted signal intensity distribution of the first optical fiber cable 5a shown in Figure 10(a2) and the weighted signal intensity distribution of the second optical fiber cable 5b shown in Figure 11(b2). Similarly, the aggregation unit 14 performs the same aggregation process on multiple signal intensity distributions corresponding to time t1, multiple signal intensity distributions corresponding to time t2, and so on. The aggregation unit 14 stores the generated multiple aggregated signal intensity distributions in the aggregated data storage unit 12. As a result, the aggregated data storage unit 12 stores the aggregated signal intensity distribution corresponding to time t0, the aggregated signal intensity distribution corresponding to time t1, the aggregated signal intensity distribution corresponding to time t2, and so on.

[0079] Thus, in this embodiment, the aggregation unit 14 sets thresholds (thresholds 14a and 14b) for each of the multiple signal intensity distributions, assigns a first weight to signals higher than the threshold, assigns a second weight to signals lower than the threshold, and generates an aggregated signal intensity distribution by adding the multiple signal intensity distributions together. With this configuration, the decrease in the SNR of the aggregated signal intensity distribution can be suppressed compared to the first embodiment described above.

[0080] (Fourth Embodiment) Next, a fourth embodiment of the present disclosure will be described. The following description will focus on the differences between this embodiment and the first embodiment described above, and redundant explanations will be omitted.

[0081] Figure 13 is a schematic diagram of the monitoring system 1. In this embodiment, the multiple optical fiber cables 5 constituting the optical fiber sensor 3 include a first optical fiber cable 5a, a second optical fiber cable 5b, and a third optical fiber cable 5c. Figure 13 shows the crossing point 7a where the vehicle 6 crosses the first optical fiber cable 5a, the crossing point 7b where the vehicle 6 crosses the second optical fiber cable 5b, and the crossing point 7c where the vehicle 6 crosses the third optical fiber cable 5c. In this way, by increasing the number of multiple optical fiber cables 5 constituting the optical fiber sensor 3, the number of times the vehicle 6 crosses the optical fiber cables 5 increases, so that false detections and over-detections regarding the vehicle 6 crossing the optical fiber sensor 3 can be suppressed. Therefore, the number of multiple optical fiber cables 5 constituting the optical fiber sensor 3 may be, for example, four or more.

[0082] Figure 14 shows an example of the spectrogram output in this embodiment. In the spectrogram of Figure 14, there are three relatively dense regions. As mentioned above, region 8a, where the optical fiber sensor 3 is located at approximately 38 meters in the longitudinal direction, corresponds to cross point 7a in Figure 13, and region 8b, where the optical fiber sensor 3 is located at approximately 50 meters in the longitudinal direction, corresponds to cross point 7b in Figure 13. In addition, region 8c, where the optical fiber sensor 3 is located at approximately 45 meters in the longitudinal direction, corresponds to cross point 7c in Figure 13.

[0083] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be made that will be understood by those skilled in the art within the scope of the present disclosure. The first to fourth embodiments can be implemented in combination as appropriate. Each of the above embodiments can be modified, for example, as follows.

[0084] That is, as shown in Figure 15, the map output unit 19 generates a map superimposed image M by superimposing the estimation result from the action estimation unit 18 onto the map m. Here, the estimation result from the action estimation unit 18 is the linear movement trajectory s of the vehicle 6, with the crossing point 7a as a passing point. That is, the action estimation unit 18 may also generate the map superimposed image M by superimposing the movement trajectory s onto the map m.

[0085] Furthermore, the scope of application of surveillance system 1 is not limited to border 2; it can also be applied to, for example, the boundaries of power plants, airports, military / secret facilities, plants, and farm sites.

[0086] Furthermore, from the perspective of improving detection accuracy by distinguishing signals from noise, signals that are not detected by both fibers within a certain period of time may be judged as noise and false alarms may be suppressed.

[0087] Furthermore, by detecting speed, it's possible to make inferences about the moving object, such as whether it's a person, a horse, or a car.

[0088] <Example of Hardware Configuration> The following describes how each functional configuration of the monitoring device 4 is realized through a combination of hardware and software.

[0089] Figure 16 is a block diagram illustrating the hardware configuration of a computer. The device in this disclosure can realize the above-described functions using a computer 500 including the hardware configuration shown in Figure 10. The computer 500 may be a portable computer such as a smartphone or tablet terminal, or a stationary computer such as a PC. The computer 500 may be a dedicated computer designed to realize each device, or it may be a general-purpose computer. The computer 500 can realize the corresponding functions by installing a predetermined program.

[0090] The computer 500 includes a bus 502, a processor 504, memory 506, a storage device 508, an input / output interface 510 (an interface is also called an I / F (Interface)), and a network interface 512. The bus 502 is a data transmission path for the processor 504, memory 506, storage device 508, input / output interface 510, and network interface 512 to send and receive data to and from each other. However, the method of connecting the processor 504 and the other components to each other is not limited to a bus connection.

[0091] The processor 504 is a variety of processor such as a CPU, GPU, or FPGA. The memory 506 is a main memory implemented using RAM (Random Access Memory) or the like.

[0092] The storage device 508 is an auxiliary storage device implemented using a hard disk, SSD, memory card, or ROM (Read Only Memory). The storage device 508 stores a program for implementing a predetermined function. The processor 504 reads this program into the memory 506 and executes it to implement each functional component of each device.

[0093] The input / output interface 510 is an interface for connecting the computer 500 with input / output devices. For example, input devices such as keyboards and output devices such as display devices are connected to the input / output interface 510.

[0094] The network interface 512 is an interface for connecting the computer 500 to a network.

[0095] The above describes examples of hardware configurations in this disclosure, but the embodiments described above are not limited thereto. This disclosure can also be implemented by having a processor execute a computer program to perform any processing.

[0096] In the examples described above, the program includes a set of instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include temporary computer-readable medium or a communication medium that includes electrical, optical, acoustic or other forms of propagating signals.

[0097] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments, rather than being associated with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps described in any of the drawings may be changed as appropriate.

[0098] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) A monitoring system comprising: a signal intensity distribution generation means that incident pulsed light onto a plurality of optical fiber cables arranged at intervals and receives the backscattered light from the plurality of optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each of the plurality of optical fiber cables; an aggregation means that aggregates the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram. (Note 2) A monitoring system according to Note 1, wherein the aggregation means generates the aggregated signal intensity distribution by selecting the maximum value of the plurality of signal intensity distributions for each position in the longitudinal direction of the plurality of optical fiber cables. (Note 3) A monitoring system according to Note 1, wherein the aggregation means sets a threshold for each of the plurality of signal intensity distributions, assigns a first weight to signals higher than the threshold, assigns a second weight smaller than the first weight to signals lower than the threshold, and generates the aggregated signal intensity distribution by adding the plurality of signal intensity distributions. (Note 4) A monitoring system according to Note 3, wherein the threshold is one of the mean, median, or mode of the corresponding signal intensity distribution. (Note 5) A monitoring system according to Note 1, further comprising a crossing pattern estimation means that estimates a crossing pattern, which is at least one of the crossing point, crossing angle, and crossing speed when a moving object crosses the plurality of optical fiber cables, based on the plurality of signal intensity distributions, wherein the output means outputs the crossing pattern superimposed on the spectrogram. (Note 6) A monitoring system as described in Note 5, wherein the output means superimposes the cross-sectional view of the moving body in vector form onto the spectrogram.(Note 7) A monitoring system as described in Note 5, further comprising a behavior estimation means for estimating at least one of the following based on the cross-sectional view: the azimuth angle of the movement of the moving object, the starting point of the moving object, the destination of the moving object, and the time of arrival of the moving object at its destination. (Note 8) A monitoring device comprising: a signal intensity distribution generation means for generating a signal intensity distribution of backscattered light in the longitudinal direction of a plurality of optical fiber cables by injecting pulsed light into a plurality of optical fiber cables arranged at intervals and receiving backscattered light from the plurality of optical fiber cables; an aggregation means for generating an aggregated signal intensity distribution by aggregating the plurality of signal intensity distributions into one; a spectrogram generation means for generating a spectrogram based on the aggregated signal intensity distribution; and an output means for outputting the spectrogram. (Note 9) A monitoring method comprising: a computer incident pulsed light onto a plurality of optical fiber cables arranged at intervals and receiving the backscattered light from the plurality of optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each of the plurality of optical fiber cables; aggregating the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution; generating a spectrogram based on the aggregated signal intensity distribution; and outputting the spectrogram. (Note 10) A program that causes a computer to function as: a signal intensity distribution generation means for incident pulsed light onto a plurality of optical fiber cables arranged at intervals and receiving the backscattered light from the plurality of optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each of the plurality of optical fiber cables; an aggregation means for aggregating the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means for generating a spectrogram based on the aggregated signal intensity distribution; and an output means for outputting the spectrogram.

[0099] Some or all of the elements (e.g., configuration and function) described in Appendices 2 to 7 that are subordinate to Appendice 1 may also be subordinate to Appendices 8 to 10 in the same manner as those described in Appendices 2 to 7. Some or all of the elements described in any appendice may be applied to various hardware, software, recording means, systems, and methods for recording software.

[0100] Although the present invention has been described above with reference to embodiments, the present invention is not limited thereto. Various modifications to the structure and details of the present invention can be made within the scope of the invention as can be understood by those skilled in the art. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0101] This application claims priority based on Japanese Patent Application No. 2024-189609, filed on 29 October 2024, and incorporates all of its disclosures herein.

[0102] 1. Monitoring system 2. Border 3. Optical fiber sensor 4. Monitoring device 5. Optical fiber cable 5a. First optical fiber cable 5b. Second optical fiber cable 5c. Third optical fiber cable 6. Vehicle 7a. Crossing point 7b. Crossing point 7c. Crossing point 8a. Area 8b. Area 8c. Area 10. Map data storage unit 11. Detection data storage unit 12. Aggregation data storage unit 13. Signal intensity distribution generation unit 14. Aggregation unit 14a. Threshold 14b. Threshold 15. Spectrogram generation unit 16. Crossing pattern estimation unit 17. Spectrogram output unit 18. Action estimation unit 19. Map output unit 20. Vector icon

Claims

1. A monitoring system comprising: a signal intensity distribution generation means that generates a signal intensity distribution of backscattered light in the longitudinal direction of each of the multiple optical fiber cables by incidenting pulsed light onto multiple optical fiber cables arranged at intervals and receiving backscattered light from the multiple optical fiber cables; an aggregation means that aggregates the multiple signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram.

2. A monitoring system according to claim 1, wherein the aggregation means generates the aggregated signal intensity distribution by selecting the maximum value of the plurality of signal intensity distributions for each position in the longitudinal direction of the plurality of optical fiber cables.

3. A monitoring system according to claim 1, wherein the aggregation means sets a threshold for each of the plurality of signal intensity distributions, assigns a first weight to signals higher than the threshold, assigns a second weight smaller than the first weight to signals lower than the threshold, and generates the aggregated signal intensity distribution by adding the plurality of signal intensity distributions.

4. The monitoring system according to claim 3, wherein the threshold is one of the mean, median, or mode of the corresponding signal intensity distribution.

5. A monitoring system according to claim 1, further comprising a crossing pattern estimation means for estimating a crossing pattern, which is at least one of a crossing point, crossing angle, and crossing velocity when a moving object crosses the plurality of optical fiber cables, based on the plurality of signal intensity distributions, wherein the output means outputs the crossing pattern superimposed on the spectrogram.

6. A monitoring system according to claim 5, wherein the output means superimposes the cross-sectional view of the moving body in vector form onto the spectrogram.

7. A monitoring system according to claim 5, further comprising a behavior estimation means for estimating at least one of the azimuth angle of movement of the moving body, the starting point of the moving body, the destination of the moving body, and the time of arrival of the moving body at the destination, based on the cross-sectional view.

8. A monitoring device comprising: a signal intensity distribution generation means that incident pulsed light onto a plurality of optical fiber cables arranged at intervals and receives the backscattered light from the plurality of optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each of the plurality of optical fiber cables; an aggregation means that aggregates the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram.

9. A monitoring method comprising: a computer incident pulsed light onto a plurality of optical fiber cables arranged at intervals, and receiving the backscattered light from the plurality of optical fiber cables; generating a signal intensity distribution of the backscattered light in the longitudinal direction of each of the plurality of optical fiber cables; aggregating the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution; generating a spectrogram based on the aggregated signal intensity distribution; and outputting the spectrogram.

10. A program that causes a computer to function as: a signal intensity distribution generation means that incident pulsed light onto a plurality of optical fiber cables arranged at intervals and receives the backscattered light from the plurality of optical fiber cables to generate a signal intensity distribution of the backscattered light in the longitudinal direction of each of the plurality of optical fiber cables; an aggregation means that aggregates the plurality of signal intensity distributions into one to generate an aggregated signal intensity distribution; a spectrogram generation means that generates a spectrogram based on the aggregated signal intensity distribution; and an output means that outputs the spectrogram.

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