Creeping plant monitoring system and creeping plant monitoring program

Abstract

To make it possible to know how long it will take for creeping plants to reach power lines.SOLUTION: A creeping plant monitoring system includes a photographing device 2 for photographing the periphery of an electric pole P with power lines L installed, and a monitoring server 3 for storing creeping plant information including a rising speed of creeping plants W wrapping around the electric pole P, determining whether the creeping plants wrap around the electric pole P on the basis of an image photographed by the photographing device 2, and determining a time until the creeping plants W reach the power lines L of the electric pole P on the basis of the photographed image and the creeping plant information in the case of determining that they wrap around the electric pole.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a kudzu monitoring system and a kudzu monitoring program for monitoring the approach of kudzu (vine) to electric wires.

Background Art

[0002] When vines such as thorns or kudzu wrap around utility poles or guy wires (wires that support the utility pole so that it does not fall) and come into contact with electric wires, there is a risk of causing a power outage. For this reason, conventionally, utility poles have been patrolled and inspected to remove and eliminate vines that may come into contact with electric wires. On the other hand, there is a known technique of installing a monitoring device on a utility pole to photograph the situation of the separation distance between the vine plant (kudzu) and the distribution line (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, the conventional patrol inspection requires time and labor, and moreover, it requires a great deal of time, labor, and cost to patrol and inspect a large number of utility poles installed over a wide area. In addition, in the conventional patrol inspection, only the approach situation of the kudzu to the electric wire was confirmed, and it was necessary for a person to judge how long it would take for the kudzu to come into contact with the electric wire, and it was difficult to make an appropriate judgment. For this reason, it has been difficult to appropriately plan the removal work of kudzu over a wide area. Similarly, even if the monitoring device described in Patent Document 1 is installed on a utility pole, only the situation of the separation distance between the kudzu and the electric wire can be known, and it is difficult to appropriately judge how long it will take for the kudzu to come into contact with the electric wire.

[0005] Therefore, an object of the present invention is to provide a kudzu monitoring system and a kudzu monitoring program capable of knowing in what period the kudzu reaches the electric wire.

Means for Solving the Problems

[0006] In order to solve the above problems, the invention according to claim 1 includes photographing means for photographing around a utility pole on which an electric wire is installed, kudzu information storage means for storing kudzu information including the rising speed of the kudzu wound around the utility pole, and based on the image photographed by the photographing means, determining whether the kudzu is wound around the utility pole, and if it is determined that the kudzu is wound around the utility pole, based on the image and the kudzu information, determining the period until the kudzu reaches the electric wire of the utility pole. A kudzu monitoring system characterized by comprising determination means.

[0007] The invention according to claim 2 is the kudzu monitoring system according to claim 1, wherein the kudzu information includes the rising speed of the kudzu wound around the support column of the utility pole, and the determination means determines whether the kudzu is wound around the support column of the utility pole based on the image, and if it is determined that the kudzu is wound around the support column of the utility pole, based on the image and the kudzu information, determining the period until the kudzu reaches the electric wire of the utility pole.

[0008] The invention according to claim 3 is the kudzu monitoring system according to claim 1, further comprising weather information acquisition means for acquiring weather information of the installation area of the utility pole, and the determination means determines the period until the kudzu reaches the electric wire of the utility pole based on the image, the kudzu information, and the weather information.

[0009] The invention according to claim 4 is the kudzu monitoring system according to claim 1, wherein the determination means determines the period until the kudzu reaches the electric wire of the utility pole based on the image, the kudzu information, and the current season.

[0010] The invention according to claim 5 is the vine monitoring system according to claim 1, wherein the determination means determines whether or not a vine wraps around a surrounding object including a tree around a utility pole based on the image.

[0011] The invention according to claim 6 is the vine monitoring system according to claim 1, wherein the determination means uses a learning model for vine monitoring that is machine-learned based on past performance data so that when the image and the vine information are input, a period until the vine reaches the electric wire of the utility pole is output.

[0012] The invention according to claim 7 is the vine monitoring system according to claim 1, wherein the photographing means is disposed on a moving body, and the photographing means continuously photographs around a plurality of the utility poles.

[0013] The invention according to claim 8 is a vine monitoring program that causes a computer to function as a vine information storage means for storing vine information including an ascending speed of a vine wound around a utility pole, and a determination means for determining whether or not a vine is wound around a utility pole based on an image of the area around the utility pole where the electric wire is installed, and when it is determined that the vine is wound around the utility pole, determining a period until the vine reaches the electric wire of the utility pole based on the image and the vine information.

[0014] The invention according to claim 9 is the vine monitoring program according to claim 8, wherein the vine information includes an ascending speed of a vine wound around a support column of a utility pole, and the determination means determines whether or not a vine is wound around a support column of a utility pole based on the image, and when it is determined that the vine is wound around the support column, determines a period until the vine reaches the electric wire of the utility pole based on the image and the vine information.

[0015] The invention according to claim 10 is the vine monitoring program according to claim 8, wherein the determination means determines whether or not a vine wraps around a surrounding object including a tree around a utility pole based on the image.

[0016] The invention according to claim 11 is characterized in that, in the vine monitoring program according to claim 8, when the image and the vine information are input, the determination means uses a learning model for vine monitoring that is machine-learned based on past performance data so as to output the period until the vine reaches the electric wire of the utility pole.

Advantages of the Invention

[0017] According to the inventions described in claim 1 and claim 8, when a vine is wound around a utility pole, based on the image around the utility pole and the rising speed of the vine wound around the utility pole, the period (arrival period) until the vine reaches the electric wire is automatically determined and predicted. That is, it becomes possible to know how much time remains from the time of shooting until the vine reaches the electric wire, and based on this arrival period, it becomes possible to appropriately plan the removal work of the vine (remove the vine before it reaches the electric wire). Moreover, since the arrival period is determined based on the rising speed of the vine wound around the utility pole and the current situation, it becomes possible to determine and know an appropriate arrival period.

[0018] According to the inventions described in claim 2 and claim 9, when a vine is wound around the column of a utility pole, based on the image around the utility pole and the rising speed of the vine wound around the column, etc., the arrival period is automatically determined. Thus, even when a vine is wound around the column, it becomes possible to determine and know the arrival period and appropriately plan the removal work of the vine. Moreover, since the arrival period is determined based on the rising speed of the vine wound around the column and the rising speed of the vine wound around the utility pole, it becomes possible to determine and know an appropriate arrival period.

[0019] According to the invention described in claim 3, since the arrival period is determined based on the weather information of the installation area of the utility pole, it becomes possible to determine and know an appropriate arrival period considering the growth degree of the vine due to the weather.

[0020] According to the invention described in claim 4, since the arrival period is determined based on the current season, it is possible to determine and obtain an appropriate arrival period in consideration of the growth degree of the ivy according to the season.

[0021] According to the inventions described in claim 5 and claim 10, it is determined whether the ivy wraps around surrounding objects including trees around the utility pole. If it is determined that the ivy wraps around the surrounding objects, the ivy will not reach the electric wire. Thus, since it is also possible to determine and predict the case where the ivy does not reach the electric wire, it is possible to appropriately plan the ivy removal work.

[0022] According to the inventions described in claim 6 and claim 11, since the arrival period is output using the machine-learned learning model for ivy monitoring, it is possible to determine and obtain a more appropriate arrival period.

[0023] According to the invention described in claim 7, while the photographing means moves with the moving body, the surroundings of a plurality of utility poles are continuously photographed, so it is possible to easily and quickly photograph the surroundings of a large number of utility poles arranged over a wide area.

Brief Description of the Drawings

[0024]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Embodiments for Carrying Out the Invention

[0025] Hereinafter, the present invention will be described based on the illustrated embodiments.

[0026] FIG. 1 is a schematic configuration diagram showing a kudzu monitoring system 1 according to an embodiment of the present invention. This kudzu monitoring system 1 is a system for monitoring the approach of kudzu W to an electric wire L, and includes a photographing device (photographing means) 2 and a monitoring server 3. Here, the electric wire L is installed via the armrest P1 of the utility pole P, and some utility poles P are provided with supports to prevent the utility poles P from falling. In addition to columnar supports, this support also includes a linear branch line (ground branch line) P2 as shown in the figure. In this embodiment, mainly the case where the branch line P2 is provided will be described. Note that reference numeral P3 in the figure is a tubular branch line cover for covering the branch line P2 to draw attention.

[0027] The photographing device 2 is photographing equipment for photographing around the utility pole P. In this embodiment, it is disposed on the upper part of a vehicle (moving body) C and continuously photographs around a plurality of utility poles P while moving. That is, it is equipped with a camera and GPS and is disposed on the vehicle C so that the surrounding state including the utility pole P can be photographed. Then, while moving with the vehicle C, the camera continuously photographs around the utility pole P (including the utility pole P, the electric wire L, etc.), and by sequentially storing the photographed images and position information (latitude, longitude) at each time, it is possible to know which utility pole P each image is an image of. Further, the photographed and stored images, position information, and photographing date and time are sequentially or at a predetermined timing transmitted to the monitoring server 3.

[0028] Here, the vehicle C travels at a speed at which the situation around the utility pole P and the growth situation of the kudzu W can be appropriately photographed. Thus, in this embodiment, while moving with the vehicle C, a plurality of areas around the utility pole P are continuously photographed. However, a person may also photograph around each individual utility pole P and transmit the photographed image and the identification information (utility pole number or position information) of the utility pole P to the monitoring server 3.

[0029] The monitoring server 3 is a computer that determines and predicts the period and time until the ivy W wrapped around a utility pole P or the like reaches the electric wire L. In this embodiment, it is arranged in the management office of a general power transmission and distribution company that manages the utility pole P and the electric wire L. As shown in FIG. 2, this monitoring server 3 mainly includes an input unit 31, a display unit 32, a communication unit 33, a storage unit 34, a weather information acquisition task (weather information acquisition means) 35, a determination task (determination means) 36, a learning task 37, and a central processing unit 38 that controls these components.

[0030] The input unit 31 is an interface for inputting various types of information and commands. Specifically, it inputs ivy information into the ivy information database 342 described later or inputs a start command for the determination task 36. The display unit 32 is a display for displaying various types of data and information. Specifically, it displays the image received from the imaging device 2 or the determination result by the determination task 36. The communication unit 33 is an interface for communicating with the outside via the Internet or a telephone communication network. Specifically, it receives an image and position information from the imaging device 2 or receives weather information from the weather information server 4 described later.

[0031] The storage unit 34 mainly includes a utility pole database (utility pole information storage means) 341, an ivy information database (ivy information storage means) 342, an ivy monitoring learning model 343, and an ivy monitoring performance database 344. Here, the databases 341 and 342 will be described, and the ivy monitoring learning model 343 and the ivy monitoring performance database 344 will be described later.

[0032] The utility pole database 341 is a database that stores information about each utility pole P to be monitored. Specifically, for each identification information (utility pole number) of the utility pole P, the installation area, position information (latitude, longitude), the image received from the imaging device 2 and the imaging date and time, the determination result by the determination task 36, etc. are stored. Here, as described above, based on the image and position information received from the imaging device 2, the received image is stored in association with the utility pole P corresponding to the received position information.

[0033] The vine information database 342 is a database that stores information about the vine W (vine information). Specifically, it stores the ascending speed V1 of the vine W wound around the utility pole P (the speed of climbing the utility pole P), the ascending speed V2 of the vine W wound around the branch line P2 of the utility pole P (the speed of climbing the branch line P2), and so on. Also stored is how these ascending speeds V1 and V2 change depending on weather information (such as weather and temperature) and seasons. For example, it is stored that when days with higher temperatures continue throughout the year, the ascending speeds V1 and V2 increase (the percentage increase), that the ascending speeds V1 and V2 increase from the rainy season to summer, and that the ascending speeds V1 and V2 are lower (the percentage decrease) in coastal areas than in mountainous areas. Here, such ascending speeds (for example, how much it climbs in one day) V1, V2, etc. are based on the results obtained from observations and experiments at the actual site.

[0034] The weather information acquisition task 35 is a task program that acquires the weather information of the installation area of the utility pole P. In this embodiment, it is activated by the determination task 36 described later and acquires the weather information of the area where the utility pole P to be determined in the determination task 36 is installed. Specifically, it accesses the weather information server 4 that provides weather information and weather forecasts for each area via the communication unit 33, and acquires short-term, medium-term, and long-term weather information and weather forecasts in the installation area of the utility pole P. Here, the weather information includes information that affects the vine W, such as predicted temperature, humidity, rainfall, solar radiation, and sunshine.

[0035] Based on the image captured by the imaging device 2, the entanglement determination task 36 determines whether the vine W is wound around the utility pole P or the branch line P2. When it is determined that the vine is wound around, based on the image and the vine information, it is a task / program for determining the period / time (reach period) until the vine W reaches the electric wire L of the utility pole P. That is, when a start command is input to the input unit 31, it is started or periodically started, and the latest image of the utility pole P to be determined is obtained from the utility pole database 341. When the vine W is wound around the utility pole P or the branch line P2, it determines / predicts how much time will pass from the latest shooting date and time until the vine W reaches the electric wire L of the utility pole P.

[0036] Here, the utility pole P to be determined is the utility pole P specified at startup, the utility pole P belonging to the area specified at startup, etc. Also, when it is periodically started, the utility pole P that meets the preset conditions is the target. For example, it targets all utility poles P for which the determination by the entanglement determination task 36 has not been performed on the image with the latest shooting date and time at the startup time. Then, the reach period is determined for all such utility poles P to be determined.

[0037] Specifically, first, the image around the utility pole P is analyzed by image analysis to determine whether the vine W is wound around the utility pole P or the branch line P2. Then, when it is determined that the vine W is wound around the utility pole P, the distance D1 from the position / height reached by the vine W on the utility pole P to the electric wire L installed on the utility pole P is calculated by image analysis. Next, based on the calculated distance D1 and the rising speed V1 of the vine W with respect to the utility pole P, the reach period until the vine W reaches the electric wire L is calculated and determined.

[0038] Also, as shown in FIG. 3, when it is determined that the vine W is wound around the branch line P2 (including the branch line cover P3) of the utility pole P, the distance D2 from the position and height reached by the vine W on the branch line P2 to the upper end (joint with the utility pole P) of this branch line P2 is calculated by image analysis. Next, based on the calculated distance D2 and the rising speed V2 of the vine W with respect to the branch line P2, the period K1 until reaching the upper end of the branch line P2 is calculated and determined. Subsequently, the distance D3 from the upper end (joint with the utility pole P) of the branch line P2 to the electric wire L is calculated by image analysis. Next, based on the calculated distance D3 and the rising speed V1 of the vine W with respect to the utility pole P, the period K2 until reaching the electric wire L from the upper end of the branch line P2 is calculated and determined. Then, based on the period K1 until reaching the upper end of the branch line P2 and the period K2 until reaching the electric wire L thereafter, the period (K1 + K2) until the vine W reaches the electric wire L is calculated and determined.

[0039] Based on such arrival periods, considering the following matters, a more appropriate arrival period is calculated and determined.

[0040] First, the weather information acquisition task 35 is activated to acquire the weather information of the installation area of the utility pole P to be determined, and the arrival period is calculated and determined based on the acquired weather information. For example, when the weather information in the installation area is predicted to have days with higher temperatures than throughout the year in the future, or when it is predicted to have continuous drought in the future, based on the vine information stored in the vine information database 342, the rising speeds V1 and V2 are increased to calculate and determine the arrival period. Also, when the installation area of the utility pole P is a coastal area, based on the vine information stored in the vine information database 342, the rising speeds V1 and V2 are decreased to calculate and determine the arrival period.

[0041] Second, calculate and determine the arrival period based on the current season at the time of determination. For example, when the current season at the time of determination is from the rainy season to summer, based on the kudzu information stored in the kudzu information database 342, increase the rising speeds V1 and V2 to calculate and determine the arrival period. Similarly, when the current season at the time of determination is winter, based on the kudzu information stored in the kudzu information database 342, decrease the rising speeds V1 and V2 to calculate and determine the arrival period.

[0042] Third, analyze and calculate the growth rate and rising speed of the kudzu W around the utility pole P based on the latest image around the utility pole P and the image before it, and calculate and determine the arrival period based on this growth rate and rising speed.

[0043] Furthermore, even when the kudzu W is wound around the utility pole P or the branch line P2, based on the image around the utility pole P, determine whether the kudzu W will wind around the surrounding objects including the tree T around the utility pole P. That is, as shown in FIG. 4, in the image around the utility pole P, when the kudzu W wound around the utility pole P or the branch line P2 extends toward the surrounding tree T or the like, it is determined that there is a possibility that the kudzu W will wind around the surrounding objects (without reaching the electric wire L) in the future. Also, when the kudzu W wound around the utility pole P or the branch line P2 is actually wound around the surrounding tree T or the like at its tip, the same determination is made. In these cases, the arrival period may be calculated simultaneously.

[0044] Such a determination task 36 uses a kudzu monitoring learning model 343 that is machine-learned based on past performance data so that when an image around the utility pole P and kudzu information are input, the period until the kudzu W reaches the electric wire L of the utility pole P is output. This kudzu monitoring learning model 343 is created by a learning task 37.

[0045] That is, the learning task 37 creates a learning model 343 for kudzu monitoring using a known machine learning algorithm such as a neural network with the past performance data recorded and stored in the performance database 344 for kudzu monitoring. This performance database 344 for kudzu monitoring is a database in which performance data including, as input information, an image around the utility pole P, kudzu information, the installation area, weather information, and the season, and the arrival period determined and predicted by experts and skilled persons regarding the monitoring and management of the kudzu W, or the actually arrived period, is recorded and stored. Note that the past performance data includes actual images, kudzu information, etc., data created based on the arrival period actually determined and predicted by experts and skilled persons, or the actually arrived period, as well as data created by pre-training, etc.

[0046] As shown in FIG. 5, this learning task 37 uses machine learning and deep learning using a neural network, and based on the performance data recorded in the performance database 344 for kudzu monitoring, creates, for example, a neural network with an image, kudzu information, the installation area, weather information, and the season as the input layer, the arrival period as the output layer, and the analysis process from the input layer to the output layer as the intermediate layer. Then, the learning task 37 uses the performance data of the learning model 343 for kudzu monitoring as learning data to perform learning on various parameters in the intermediate layer. That is, the learning task 37 performs learning on various parameters in the intermediate layer so that an appropriate arrival period is output based on an image, kudzu information, the installation area, weather information, and the season.

[0047] Also, whether or not the kudzu W wound around the utility pole P or the branch line P2 will wind around surrounding objects is similarly determined using the learning model 343 for kudzu monitoring.

[0048] Then, the arrival period calculated and determined in this way is displayed on the display unit 32 for each piece of identification information of the utility pole P, and is also transmitted to a pre-registered administrator's mobile terminal or the like. Further, when the calculated and determined arrival period is shorter than a predetermined period, the utility pole P that requires urgency is displayed on the display unit 32 or transmitted to the administrator's mobile terminal or the like. Also, when it is determined that the kudzu vine W is wound around a surrounding object, display or the like on the display unit 32 is performed.

[0049] As described above, according to this kudzu vine monitoring system 1, when the kudzu vine W is wound around the utility pole P, based on the image around the utility pole P and the rising speed V1 of the kudzu vine W wound around the utility pole P, the period until the kudzu vine W reaches the electric wire L (arrival period) is automatically determined and predicted. That is, it becomes possible to know how much time it will take for the kudzu vine W to reach the electric wire L from the time of shooting, and based on this arrival period, it becomes possible to appropriately plan the removal work of the kudzu vine W (remove the kudzu vine W before it reaches the electric wire L). Moreover, since the arrival period is determined based on the rising speed V1 of the kudzu vine W wound around the utility pole P and the current situation, it becomes possible to determine and obtain an appropriate arrival period.

[0050] Also, when the kudzu vine W is wound around the branch line P2 of the utility pole P, the arrival period is automatically determined based on the image around the utility pole P and the rising speed V2 of the kudzu vine W wound around the branch line P2, etc. In this way, even when the kudzu vine W is wound around the branch line P2, it becomes possible to determine and know the arrival period and appropriately plan the removal work of the kudzu vine W. Moreover, since the arrival period is determined based on the rising speed V2 of the kudzu vine W wound around the branch line P2 and the rising speed V1 of the kudzu vine W wound around the utility pole P, it becomes possible to determine and obtain an appropriate arrival period.

[0051] Also, since the arrival period is determined based on the weather information of the installation area of the utility pole P, it becomes possible to determine and obtain an appropriate arrival period considering the growth degree of the kudzu vine W due to the weather. Similarly, since the arrival period is determined based on the current season, it becomes possible to determine and obtain an appropriate arrival period considering the growth degree of the kudzu vine W due to the season.

[0052] Furthermore, since the reaching period is output using the machine-learned learning model 343 for kudzu monitoring, it becomes possible to determine and acquire a more appropriate reaching period.

[0053] Also, it is determined whether the kudzu W wraps around the surrounding objects including the trees T around the utility pole P. If it is determined that the kudzu W wraps around the surrounding objects, the kudzu W will not reach the electric wire L. In this way, since the case where the kudzu W does not reach the electric wire L can also be determined and predicted, it becomes possible to appropriately plan the removal work of the kudzu W.

[0054] On the other hand, while the imaging device 2 moves with the vehicle C, the surroundings of a plurality of utility poles P are continuously imaged, so it becomes possible to easily and quickly image the surroundings of a large number of utility poles P arranged over a wide area.

[0055] As described above, the embodiments of the present invention have been described in detail. However, the specific configuration is not limited to this embodiment, and design changes and the like within the scope not departing from the gist of the present invention are also included in the present invention. For example, in the above embodiment, the monitoring server 3 is configured as an integrated server, but it may be configured with a plurality of computers or servers, etc., and they may be arranged at different locations.

[0056] On the other hand, by installing the following kudzu monitoring program on a general-purpose computer, the above-described kudzu monitoring system 1 and monitoring server 3 may be configured.

[0057] That is, a program that causes a computer to function as a kudzu information storage means (kudzu information database 342) for storing kudzu information including the rising speed of the kudzu W wound around the utility pole P and the branch line P2, and based on an image taken of the area around the utility pole P where the electric wire L is installed, determines whether the kudzu W is wound around the utility pole P or the branch line P2. When it is determined that the kudzu is wound around, based on the image around the utility pole P and the kudzu information, a determination means (determination task 36) for determining the period (arrival period) until the kudzu W reaches the electric wire L of the utility pole P. The determination means determines the arrival period based on the weather information and the current season of the installation area of the utility pole P, and also determines whether the kudzu W will wind around the surrounding objects including the trees T around the utility pole P based on the image around the utility pole P. When the image around the utility pole P and the kudzu information are input, a kudzu monitoring learning model 343 learned based on past performance data is used so that the arrival period is output.

Explanation of Signs

[0058] 1 Kudzu monitoring system 2 Photographing device (photographing means) 3 Monitoring server 341 Utility pole database (utility pole information storage means) 342 Kudzu information database (kudzu information storage means) 343 Kudzu monitoring learning model 344 Kudzu monitoring performance database 35 Weather information acquisition task (weather information acquisition means) 36 Determination task (determination means) 4 Weather information server W Kudzu L Electric wire P Utility pole P2 Branch line (support column) C Vehicle (mobile body)

Claims

1. Imaging means for imaging around a utility pole with an electric wire installed thereon, Kudzu information storage means for storing kudzu information including the ascending speed of kudzu wound around the utility pole, Determination means for determining whether kudzu is wound around the utility pole based on the image captured by the imaging means, and when it is determined that the kudzu is wound around the pole, determining the period until the kudzu reaches the electric wire of the pole based on the image and the kudzu information, A kudzu monitoring system, characterized by comprising the above.

2. The kudzu information includes the ascending speed of kudzu wound around the support column of the utility pole, The determination means determines whether kudzu is wound around the support column of the utility pole based on the image, and when it is determined that the kudzu is wound around the pole, determines the period until the kudzu reaches the electric wire of the pole based on the image and the kudzu information. The kudzu monitoring system according to claim 1, characterized by the above.

3. Weather information acquisition means for acquiring weather information of the installation area of the utility pole is provided, The determination means determines the period until the kudzu reaches the electric wire of the utility pole based on the image, the kudzu information, and the weather information. The kudzu monitoring system according to claim 1, characterized by the above.

4. The determination means determines the period until the kudzu reaches the electric wire of the utility pole based on the image, the kudzu information, and the current season. The kudzu monitoring system according to claim 1, characterized by the above.

5. The determination means determines whether kudzu is wound around surrounding objects including trees around the utility pole based on the image. The kudzu monitoring system according to claim 1, characterized by the above.

6. When the image and the kudzu information are input, the determination means uses a learning model for kudzu monitoring that is machine-learned based on past performance data so that the period until the kudzu reaches the electric wire of the utility pole is output. The kudzu monitoring system according to claim 1, characterized by the above.

7. The imaging means is disposed on a moving body, The imaging means continuously images around a plurality of the utility poles. The kudzu monitoring system according to claim 1, characterized by the above.

8. A computer, Kudzu information storage means for storing kudzu information including the ascending speed of kudzu wound around a utility pole, Based on an image taken around a utility pole with wires installed, it is determined whether the ivy is wrapped around the utility pole. When it is determined that the ivy is wrapped around the pole, a determination means determines the period until the ivy reaches the wires of the utility pole based on the image and the ivy information. An ivy monitoring program characterized by functioning as such.

9. The ivy information includes the rising speed of the ivy wrapped around the pole of the utility pole. The determination means determines whether the ivy is wrapped around the pole of the utility pole based on the image. When it is determined that the ivy is wrapped around the pole, the determination means determines the period until the ivy reaches the wires of the utility pole based on the image and the ivy information. The ivy monitoring program according to claim 8, characterized by the above.

10. The determination means determines whether the ivy is wrapped around surrounding objects including trees around the utility pole based on the image. The ivy monitoring program according to claim 8, characterized by the above.

11. When the image and the ivy information are input, the determination means uses a learned model for ivy monitoring that is machine-learned based on past performance data so that the period until the ivy reaches the wires of the utility pole is output. The ivy monitoring program according to claim 8, characterized by the above.

Images