KR20240066735A - System for predicting grass damage range by analyzing movement and behavior of golf course visitors - Google Patents

Abstract

The present invention relates to a system for predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors. It tracks and monitors the movement and behavior of golf course visitors, and predicts the extent of turf damage in the golf course through the tracking and monitoring results. By doing so, it is about a system for predicting the extent of turf damage through analysis of the movement and behavior of visitors to the golf course, which enables efficient maintenance and management of the turf.

Description

Grass damage range prediction system through analysis of movement and behavior of golf course visitors {SYSTEM FOR PREDICTING GRASS DAMAGE RANGE BY ANALYZING MOVEMENT AND BEHAVIOR OF GOLF COURSE VISITORS}

The present invention relates to a system for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course. More specifically, the system tracks and monitors the movement and behavior of visitors to a golf course, and uses the results of tracking and monitoring to determine the extent of turf damage in a golf course. This is about a system for predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors, which enables efficient maintenance and management of the turf by predicting the extent of damage.

Golf is a sport in which players compete based on the number of strokes required to hit a ball stopped on a golf course with a club and put it into a hole. The teeing ground, fairway, green, rough, etc. that make up the golf course have grass. Planted and managed.

The growth state of grass planted on a golf course varies depending on ground conditions such as temperature, humidity, and ground salinity. If the ground temperature is too low or high, the grass may dry out or burn and die. In addition, grass can stop growing if it lacks nutrients and is vulnerable to pests and diseases, so each golf course invests a lot of manpower and money into maintenance management.

Golf courses have a very large area, and the grass can be damaged when golf course visitors constantly step on or swing clubs. Therefore, in order for the manager to manage the grass planted on the golf course, there was the inconvenience of having to physically inspect the golf course by walking around a large area, and there was a problem of greatly increasing time and cost.

Accordingly, there is a need to introduce technology to confirm or predict which part of the golf course where grass is planted is damaged and to perform maintenance and management of the grass based on the confirmed or predicted results. In other words, if the degree of damage to the turf can be predicted in advance according to people's movement or club use, the manpower required to perform maintenance management as well as costs can be greatly reduced, so the introduction of related technology is necessary at each golf course.

Therefore, in the present invention, the movement and behavior of visitors to the golf course are tracked and confirmed through a plurality of cameras and communication terminals including GPS functions scattered throughout the golf course, and the degree of grass damage is predicted based on the results, thereby maintaining the lawn. We would like to suggest a way to carry out management efficiently.

Next, we will briefly describe the prior inventions existing in the technical field of the present invention, and then describe the technical details that the present invention seeks to achieve differently compared to the prior inventions.

First, Korean Patent No. 2046606 (2019.12.02.) is a lawn monitoring system that is installed in various locations where grass is grown, such as golf courses, soccer fields, and baseball fields, and allows lawn managers to manage the grass by receiving information on the state of the grass. It is a prior invention regarding .

In addition, Korea Patent Publication No. 2022-0028591 (2022.03.08.) provides course condition information (e.g. humidity, rainfall, ground temperature, temperature, wind speed, PH value, ionic conductivity, etc.) collected from sensor devices installed at various points on the golf course. By combining the basic information of the golf course (e.g. location, altitude, date) and nearby pest information (e.g. information on pests and diseases in nearby golf courses), big data analysis is performed to determine optimal course management measures and course disaster risk (e.g. This is a prior invention regarding a big data-based golf course management system that realizes efficient course management by deriving pest control recommendations according to pests and diseases.

However, the present invention records the movement paths of golf course visitors and equipment and predicts the degree of damage to the grass by using actions that affect grass damage, such as the golf member's swing, and thus information on the temperature, moisture, and salinity of the grass. Using Korean Patent No. 2046606, which allows the lawn manager to effectively manage the lawn by transmitting information to the lawn manager terminal, and multiple sensors pre-installed at various points on the golf course, course condition information, basic golf course information, and nearby There is a significant difference in composition between the present invention and Korea Patent Publication No. 2022-0028591, which manages the course of a golf course using pest and disease information.

In particular, the present invention uses the movement and behavioral characteristics (club swing characteristics) of visitors and golf members who are not stationary and moving, but the above prior arts do not use the state of the grass at rest and information affecting the state of the grass. Since the condition of the grass is monitored and managed by collecting or using course humidity, rainfall, ground temperature, air temperature, wind speed, and pest information around the golf course, there is a clear difference in technical configuration.

The present invention was created to solve the above problems, and its purpose is to provide a system that can predict whether the grass is damaged by checking the movement lines or actions of visitors to the golf course.

Another purpose of the present invention is to provide a system that can predict whether or not grass is damaged based on the movement lines and behavior of golf course visitors tracked and monitored through a communication terminal including a plurality of cameras and GPS functions.

In addition, the present invention is a system that can collect accurate location data by correcting the location of the direction information taken obliquely by looking at it from above when tracking and monitoring the movement path of visitors to the golf course through cameras scattered throughout the golf course. Another purpose is to provide.

In addition, the present invention provides a system that can predict turf damage by assigning weights based on the accumulated number of movements in each area, time spent, golf swing, etc., when predicting damage to the turf through the movement and behavior of visitors to the golf course. It is for another purpose.

Another purpose of the present invention is to provide a system that can predict whether the grass is damaged based on a predetermined radius from the current location of a golf course visitor.

Another purpose of the present invention is to provide a system that can visualize turf damage information predicted according to the movement and behavior of golf course visitors through a visualization tool and provide it to a manager terminal.

A system for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to an embodiment of the present invention includes an information collection unit that collects location and behavior information of visitors to the golf course; And a lawn damage prediction unit that predicts the degree of damage to the grass based on the collected location and behavior information of visitors to the golf course, and performs lawn repair in the golf course based on the information about the predicted degree of damage to the grass. You can.

In addition, the information collection unit includes a location information collection unit that receives GPS information about the current location from the communication terminal of the golf course visitor, and tracks and confirms the location information of each golf course visitor through the received GPS information; and a behavior information collection unit that verifies behavior information of visitors to each golf course from image data captured by a plurality of cameras provided in the golf course.

In addition, the communication terminal is any one of a smartphone, a tablet, and a distance meter including a GPS receiver owned by a golf course visitor or provided by the golf course, and the location information collection unit is a golf course visitor who has agreed to provide the location information. Location information can be collected.

In addition, the behavior information collection unit inputs the image captured by the camera into a preset learning model for golf club recognition, and recognizes that the golf course visitor performed a swing at the corresponding location according to the output result of the learning model. Behavioral information can be collected.

In addition, the behavior information collection unit determines that the golf course visitor confirmed through the location information collection unit has stopped at the current location for exceeding a preset reference time, and the current location of the golf course visitor is not a road or a hazard, but within the golf course. Behavioral information of visitors to the golf course can be collected only for the teeing ground, fairway, and rough.

In addition, the location information collection unit further includes confirming the location information of the golf course visitor from an object extracted from the image data captured by the camera, and when checking the location information of the golf course visitor, the location of the object is selected as the corresponding location. After correcting it to a position viewed vertically from top to bottom, the location of visitors to the golf course can be confirmed by mapping it with a map of the corresponding location of the golf course set in advance.

In addition, the turf damage range prediction system assigns different weights according to location and behavior information, including the cumulative number of movements of each golf course visitor to a specific location, the time each golf course visitor stays at a specific location, and the swing of the golf club. It may further include a weight application unit for applying a weight, and the grass damage prediction unit may further include predicting whether the grass is damaged by referring to the weight applied by the weight application unit.

In addition, the lawn damage extent prediction system divides and visualizes the degree of damage to the grass for each location predicted by the lawn damage prediction unit into a plurality of stages, and provides the degree of damage to the grass for each visualized location to the administrator terminal. It may further include a visualization processing unit that supports maintenance management.

In addition, a method for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to an embodiment of the present invention includes the steps of: collecting location and behavior information of visitors to the golf course in a turf damage extent prediction system; And in the turf damage extent prediction system, predicting the extent of damage to the turf based on the collected location and behavior information of visitors to the golf course, wherein the turf within the golf course is based on the information on the predicted extent of damage to the turf. Repairs can be performed.

In addition, the method for predicting the extent of turf damage includes, in the turf damage extent prediction system, the cumulative number of movements of each golf course visitor to a specific location, the time each golf course visitor stays at a specific location, the location including the swing of the golf club, and Applying different weights according to behavioral information; And, in the lawn damage range prediction system, predicting whether the grass is damaged according to the applied weight.

In addition, the method for predicting the extent of turf damage includes, in the turf damage extent prediction system, visualizing the predicted extent of damage to the turf for each location by dividing it into a plurality of stages; And it may further include supporting maintenance management by providing the degree of damage to the turf for each visualized location to the manager terminal.

As described above, according to the system for predicting the extent of turf damage through analysis of the movement and behavior of visitors to the golf course of the present invention, the movement and behavior of visitors to the golf course are monitored through a plurality of cameras scattered throughout the golf course and communication terminals including GPS functions. By tracking and monitoring and predicting the degree of damage to the grass in the golf course based on the results, it is possible to perform efficient maintenance and management of the grass.

However, the effects of the present invention are not limited to the effects described above, and effects not mentioned can be clearly understood by those skilled in the art from this specification and the attached drawings.

Figure 1 is a diagram schematically showing the overall configuration of a system for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to an embodiment of the present invention.
Figure 2 is a diagram showing in detail the configuration of a turf damage range prediction system according to an embodiment of the present invention.
Figure 3 is a diagram showing in more detail the configuration of the location information collection unit applied to the lawn damage range prediction system according to an embodiment of the present invention.
Figure 4 is a diagram showing in more detail the configuration of the behavior information collection unit applied to the lawn damage range prediction system according to an embodiment of the present invention.
Figure 5 is a flowchart showing in detail the operation process of a method for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to an embodiment of the present invention.

Hereinafter, specific embodiments of the present invention will be described in detail with reference to the drawings. However, the spirit of the present invention is not limited to the presented embodiments, and a person skilled in the art who understands the spirit of the present invention may add, change, or delete other components within the scope of the same spirit, thereby creating other degenerative inventions or the present invention. Other embodiments that are included within the scope of the invention can be easily proposed, but this will also be said to be included within the scope of the invention of the present application.

In addition, components having the same function within the scope of the same idea shown in the drawings of each embodiment will be described using the same reference numerals.

Figure 1 is a diagram schematically showing the overall configuration of a system for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to an embodiment of the present invention.

As shown in Figure 1, the present invention includes a turf damage extent prediction system 100 (hereinafter referred to as a turf damage extent prediction system) through analysis of the movement and behavior of golf course visitors, at least one golf course visitor communication terminal 200, It is configured to include at least one manager terminal 300, a database 400, etc.

The grass damage range prediction system 100 is a maintenance management device based on a network developed to support grass maintenance on a golf course, and is not only used by visitors to the golf course (i.e. golfers), but also by caddies and The movements and actions of managers and others are continuously tracked and monitored.

In addition, the grass damage range prediction system 100 predicts whether the grass in the golf course is damaged through the tracking and monitoring results, and quickly performs maintenance and management of the predicted damage or damaged grass by referring to the predicted results. make it possible

To this end, the turf damage extent prediction system 100 collects location information on the movement lines of visitors from golf course visitor communication terminals 200 including GPS functions possessed by golf course visitors, and at the same time, the grass damage range prediction system 100 collects location information on the movement lines of visitors to the golf course and is distributed throughout the golf course. Behavior information of golf course visitors is collected from images captured by a plurality of cameras 300, and whether the grass is damaged is determined through location information and behavior information collected from the golf course visitor communication terminal 200 and camera 300, respectively. predict

At this time, the golf course visitor communication terminal 200 may utilize a communication terminal including a GPS reception function and a communication module capable of communicating over a network, such as a smartphone, watch, tablet, or rangefinder owned by the golf course visitor. In addition, it is possible for the golf course to provide golf course visitors with a dedicated GPS receiver containing a communication module.

In addition, the turf damage range prediction system 100 predicts whether the turf is damaged according to the movement or behavior of the golf course visitor, and predicts whether the grass is damaged according to the movement or behavior of the golf course visitor. It is desirable to predict whether the grass is damaged based on . In other words, the turf damage range prediction system 100 can accurately measure where a golf course visitor is within the golf course through GPS information and images captured by a camera, but limiting the specified location may cause errors. Because the probability may increase, it is recommended to predict grass damage based on a certain radius to improve the prediction accuracy of grass damage.

In addition, when predicting whether the grass is damaged through the movement and behavior of golf course visitors, the turf damage range prediction system 100 determines the time the golf course visitor stayed at a specific location, whether or not the golf swing was performed, and the movement of multiple golf course visitors to a specific location. Damage to grass can be predicted by assigning weights to the number of times.

In addition, the turf damage range prediction system 100 visualizes turf damage information predicted according to the movement and behavior of visitors to the golf course through a preset visualization tool (e.g., application program, graphic editing tool, etc.), and visualizes the turf damage information predicted according to the movement and behavior of golf course visitors. Grass damage information can be provided to the corresponding manager terminal 400 that performs maintenance management.

Meanwhile, when tracking and monitoring the movement lines of golf course visitors, the turf damage range prediction system 100 uses a plurality of cameras 300 in addition to using GPS information using the golf course visitor communication terminal 200. It will also be possible to track and monitor the movements of visitors to each golf course.

For example, when tracking and monitoring the movement path of visitors to each golf course with the camera 300, most of the cameras 300 are photographed diagonally rather than vertically, so the grass damage range prediction system ( 100) can collect accurate location data of visitors to the golf course by correcting the direction information taken obliquely by the camera 300 into coordinates as seen from above.

The golf course visitor communication terminal 200 transmits location information (i.e., GPS information) that changes according to the movement of golf course visitors to the turf damage extent prediction system 100 through the network.

The camera 300 captures images of golf use by visitors to the golf course and transmits them to the turf damage extent prediction system 100 through a network.

The manager terminal 400 is a communication terminal owned by executives and employees belonging to the golf course, and periodically receives information about grass damage in the golf course from the grass damage range prediction system 100 and displays it on the screen. The grass damage information displayed at this time may be provided in various forms such as graphics and text.

The database 500 stores and manages various programs used in the turf damage extent prediction system 100, and stores and manages information about the golf course for each golf course.

In addition, the database 500 stores and manages the location and behavior information of visitors to the golf course for each golf course, and accumulates and stores and manages turf damage prediction information predicted based on this information.

At this time, the location and behavior information of each golf course visitor must be temporarily stored and managed, and deleted and managed after a certain period of time has elapsed after being used to predict turf damage. To protect personal information, personal identification information, faces, etc. must be included. If so, it is of course necessary to anonymize or blur the information.

Figure 2 is a diagram showing in detail the configuration of a turf damage range prediction system according to an embodiment of the present invention.

As shown in FIG. 2, the turf damage range prediction system 100 includes an information collection unit 110, a turf damage prediction unit 120, a weight application unit 130, a visualization processing unit 140, and a maintenance information unit. It consists of studying (150), etc.

In addition, although not shown in the drawing, the turf damage range prediction system 100 includes a processor, memory, a bus connecting them, various interface cards, etc. in hardware, and is driven through the processor in the memory in software. Programs to be performed are stored, and may additionally include a user interface to perform operations according to commands from the user or network, an update management unit that manages updates to various operating programs, and an interface unit for sending and receiving data to and from external devices such as databases. You can.

The information collection unit 110 collects location and behavior information of each golf course visitor from the golf course visitor communication terminal 200 and camera 300 through a network, and recalls the collected location and behavior information of each golf course visitor. It is output to the turf damage prediction unit 120.

The information collection unit 110 consists of a location information collection unit 111 and a behavior information collection unit 112.

The location information collection unit 111 receives GPS information about the current location from the golf course visitor communication terminal 200, tracks and confirms the location information of each golf course visitor through the received GPS information, and tracks and confirms the location information of each golf course visitor. The confirmed results are output to the turf damage prediction unit 120.

Additionally, in addition to collecting location information of visitors to each golf course using the GPS information, the location information collection unit 111 can also collect location information through images captured by the camera 300. This will be explained in more detail in Figure 3 below.

Meanwhile, the collection of the location information, like the collection of behavioral information in the behavioral information collection unit 112, must be performed on the premise of consent to the collection of information from visitors to the golf course.

The behavior information collection unit 112 checks the behavior information of visitors to each golf course from image data captured by a plurality of cameras 300 provided in the golf course, and uses the behavior information of the confirmed visitors to the golf course to the turf damage prediction unit. Prints as (120).

At this time, the behavior information collection unit 112 uses artificial intelligence (Artificial Intelligence) techniques to check the behavior information of each golf course visitor from the image data, and the method will be described in more detail in FIG. 4 below.

The turf damage prediction unit 120 predicts the degree of turf damage in each golf course based on the location information and behavior information of visitors to each golf course collected by the information collection unit 110, and sends the predicted results to the maintenance information provider. It is provided to the corresponding manager terminal 400 through (150) so that the manager can quickly perform lawn repair based on the information on the predicted degree of damage to the lawn.

In other words, by collecting the movement patterns of visitors to each golf course as well as their behavioral patterns, we comprehensively check which course they move to, which position they stay in for a long time, and which position they swing the golf club from, and based on this, damage to the grass. predicting whether or not

For example, as a result of checking the movement and behavior of visitors to each golf course, if it is confirmed that visitors move and visit the golf course more frequently or stay for a longer period of time at a certain location on the golf course than at other locations, the grass at that location is stepped on more or the golf course is moved more frequently. Damage such as dents due to swinging the club is predicted, and damage to the turf can be predicted by comparing these numbers with preset reference data.

At this time, when predicting grass damage, the grass damage prediction unit 120 preferably does not predict grass damage based on a specific area, but rather predicts grass damage based on a certain radius of the corresponding area. For example, the entire golf course can be divided in detail into predetermined areas, and the predicted degree of turf damage can be predicted for each divided area.

The weight application unit 130 uses the location information and behavior information collected by the information collection unit 110 to calculate the cumulative number of movements of visitors to each golf course to a specific location, the time each golf course visitor stays at a specific location, and the golf Different weights are applied according to location information and behavior information, including the swing of the club, and information on the applied weights is provided to the grass damage prediction unit 120.

Accordingly, the turf damage prediction unit 120 can predict whether the turf is damaged for each location of each golf course using the weight information. At this time, it is desirable to apply the above weight to predict turf damage, but it is not required and may not be applied depending on the system environment or golf course characteristics.

The visualization processing unit 140 visualizes turf damage information for each location based on the turf damage prediction results provided from the turf damage prediction unit 120, and determines the degree of damage to the visualized turf by the maintenance information provider ( 150).

At this time, the visualization processing unit 140 visualizes the degree of damage to the grass at each location by dividing it into a plurality of stages through color classification, so that the manager can intuitively determine at which location the grass is damaged through information about the visualized grass damage. Be sure to check it immediately.

The maintenance information providing unit 150 periodically provides the turf damage prediction results performed by the turf damage prediction unit 120 to the corresponding manager terminal 400 to quickly perform lawn maintenance management. The turf damage prediction results provided at this time may be data converted into numbers.

In addition, the maintenance information providing unit 150 provides the degree of damage to the grass at each location processed by the visualization processing unit 140 to the manager terminal 400 to perform maintenance management. The turf damage prediction results provided at this time may be numerical or graphically processed data.

Meanwhile, when the maintenance information provider 150 provides the turf damage prediction results to the relevant manager, it is preferable to provide them in a visualized manner rather than providing only numbers.

Figure 3 is a diagram showing in more detail the configuration of the location information collection unit applied to the lawn damage range prediction system according to an embodiment of the present invention.

As shown in FIG. 3, the location information collection unit 111 consists of an image reception unit 111a, an image correction unit 111b, a mapping unit 111c, and a location confirmation unit 111d.

In addition to collecting location information of visitors to each golf course using the GPS information as described in the corresponding part of FIG. 2, the location information collection unit 111 also collects location information through images captured by the camera 300. It is possible to collect In other words, location information of visitors to the golf course can be confirmed from objects (eg, people) extracted from image data captured by the camera 300.

In this way, in order to check the location information of visitors to the golf course from the image data captured by the camera 300 in the location information collection unit 111, each of the plurality of cameras 300 is first transmitted through the image receiver 111a. Receive captured image data and check the object.

At this time, since the image data captured by the camera 300 is an image captured in an oblique direction, the position of the object is converted to coordinates of a position viewed vertically from the top to the bottom through the image correction unit 111b. After conversion and correction, it is mapped with a map of the corresponding location of the golf course set in advance through the mapping unit 111c.

Next, the mapping result is confirmed through the location confirmation unit 111d to finally confirm the location of the visitor to the golf course, and the confirmed location information is provided to the turf damage prediction unit 120. If a weight is used, the location information is provided to the weight application unit 130.

Figure 4 is a diagram showing in more detail the configuration of the behavior information collection unit applied to the lawn damage range prediction system according to an embodiment of the present invention.

As shown in FIG. 4, the behavior information collection unit 112 consists of an image reception unit 112a and a behavior recognition unit 112b.

The image receiver 112a receives image data captured by each of the plurality of cameras 300 and outputs it to the action recognition unit 112b.

The action recognition unit 112b preprocesses the image data received from the image receiver 112a and then inputs the preprocessed image data into a preset learning model for golf club recognition. At this time, the preprocessing refers to the task of converting image data captured by the camera 300 into data to be input to the learning model for golf club recognition (i.e., adjusting data size, resolution, etc.).

In addition, the behavior recognition unit 112b collects behavior information by recognizing whether a visitor to the golf course has performed a swing at the corresponding location through the output result of the learning model for golf club recognition, and collects the collected behavior information. It is provided to the turf damage prediction unit 120. If a weight is used, the location information is provided to the weight application unit 130.

At this time, the behavior recognition unit 112b determines that the golf course visitor identified through the location information collection unit 111 has stopped at the current location for exceeding a preset reference time, and at the same time, the current location of the golf course visitor is determined to be on the road. Information on the behavior of visitors to the golf course can be collected only in the case of teeing grounds, fairways, and rough within the golf course, rather than hazards.

Meanwhile, the behavior information collection unit 112 applies the image captured by the camera to a preset learning model for object extraction to extract objects (e.g., people, tools such as golf clubs held by people, etc.), The extracted object is input into a preset learning model for golf club recognition, and when the golf club is recognized through the output result of the learning model, behavioral information is collected by confirming that the golf course visitor performed a swing at the corresponding location. possible. In this case, it is possible to more accurately recognize whether a person is holding a golf club from the image captured by the camera.

Next, an embodiment of the method for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to the present invention configured as described above will be described in detail with reference to FIG. 5. At this time, the order of each step according to the method of the present invention may be changed depending on the usage environment or a person skilled in the art.

Figure 5 is a flowchart showing in detail the operation process of a method for predicting the extent of turf damage through analysis of the movement and behavior of visitors to a golf course according to an embodiment of the present invention.

As shown in FIG. 5, first, the turf damage extent prediction system 100 performs a step of collecting location and behavior information of visitors to the golf course (S100).

That is, GPS information on the current location is received from the golf course visitor communication terminal 200, the location information of each golf course visitor is tracked and confirmed, and the behavior information of each golf course visitor is obtained from the image data captured by the plurality of cameras 300. is to check. At this time, as described above, the verification of the behavioral information utilizes artificial intelligence.

In addition, the turf damage extent prediction system 100 performs a step of applying different weights to the location information and behavior information of the golf course visitors collected in step S100 (S200).

That is, different weights are applied according to location information and behavioral information, including the cumulative number of movements of each golf course visitor to a specific location, the time each golf course visitor stays at a specific location, and the swing of the golf club.

After weighting the location information and behavior information of each golf course visitor collected in step S100 through step S200, the grass damage extent prediction system 100 performs a step of predicting whether the grass in the golf course is damaged (S300) .

Next, the turf damage extent prediction system 100 performs a step of visualizing the damage extent of the turf at each location predicted in step S300 by dividing it into a plurality of stages (S400), and visualizing the extent of turf damage at each location visualized. The level of damage is provided to the manager terminal 400 to support maintenance management (S500).

In this way, the present invention checks the movement lines and actions of visitors to the golf course through a communication terminal including a plurality of cameras and a GPS function, and predicts the degree of damage to the grass in the golf course according to the confirmation results, thereby efficiently maintaining the grass. It can be managed.

In the attached drawings, in order to more clearly express the technical idea of the present invention, components that are unrelated or less relevant to the technical idea of the present invention are briefly expressed or omitted.

In the above, the configuration and features of the present invention have been described based on the embodiments according to the present invention, but the present invention is not limited thereto, and various changes or modifications may be made within the spirit and scope of the present invention. It is obvious to those skilled in the art, and therefore, it is stated that such changes or modifications fall within the scope of the appended patent claims.

100: Grass damage range prediction system 110: Information collection unit
111: location information collection unit 111a: video reception unit
111b: Image correction unit 111c: Mapping unit
111d: Location confirmation unit 112: Behavior information collection unit
112a: video receiver 112b: action recognition unit
120: Grass damage prediction unit 130: Weight application unit
140: Visualization processing unit 150: Maintenance information provision unit
200: Golf course visitor communication terminal 300: Camera
400: Administrator terminal 500: Database

Claims (11)

An information collection unit that collects location and behavior information of golf course visitors; and
It includes a turf damage prediction unit that predicts the degree of damage to the turf based on the collected location and behavior information of visitors to the golf course,
A system for predicting the extent of turf damage through analysis of the movements and behavior of golf course visitors, characterized in that turf repair within the golf course is performed based on information on the predicted extent of turf damage.
In claim 1,
The information collection department,
A location information collection unit that receives GPS information about the current location from the communication terminal of the golf course visitor, and tracks and confirms the location information of each golf course visitor through the received GPS information; and
A system for predicting the extent of turf damage through analysis of the movement lines and behavior of visitors to a golf course, comprising: a behavior information collection unit that checks the behavior information of each golf course visitor from video data captured by a plurality of cameras installed in the golf course.
In claim 2,
The communication terminal is,
Any of the smartphones, tablets, and range finders including GPS receivers owned by visitors to the golf course or provided by the golf course,
The location information collection unit,
A system for predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors, characterized in that it collects location information from golf course visitors who have agreed to provide the location information.
In claim 2,
The behavioral information collection department,
Input the video captured by the camera into a preset learning model for golf club recognition,
A system for predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors, characterized in that it recognizes that the golf course visitor has performed a swing at the corresponding location according to the output result of the learning model and collects behavioral information.
In claim 4,
The behavioral information collection department,
A visitor to the golf course confirmed through the location information collection unit is stopped at the current location for exceeding a preset standard time,
Grass damage through analysis of the movement and behavior of golf course visitors, characterized in that behavioral information of golf course visitors is collected only when the current location of the golf course visitor is not a road or hazard, but the teeing ground, fairway, and rough within the golf course. Range prediction system.
In claim 2,
The location information collection unit,
It further includes confirming location information of visitors to the golf course from objects extracted from image data captured by the camera,
When checking the location information of the golf course visitor, the location of the object is corrected to a position viewed vertically from the top to the bottom at the corresponding location, and then mapped with a preset map of the golf course location to determine the location of the golf course visitor. A system for predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors, characterized by checking.
In claim 1,
The grass damage range prediction system is,
It further includes a weight application unit that applies different weights according to location and behavior information, including the accumulated number of movements of each golf course visitor to a specific location, the time spent at a specific location by each golf course visitor, and the swing of the golf club. ,
The lawn damage prediction unit further includes predicting whether the grass is damaged by referring to the weight applied by the weight application unit.
In claim 1,
The grass damage range prediction system is,
a visualization processing unit that divides and visualizes the degree of damage to the grass for each location predicted by the grass damage prediction unit into a plurality of stages and provides the degree of damage to the grass for each location visualized to an administrator terminal to support maintenance management; A system for predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors, further comprising:
In the turf damage range prediction system, collecting location and behavior information of visitors to the golf course; and
In the turf damage extent prediction system, predicting the extent of turf damage based on the collected location and behavior information of visitors to the golf course,
A method of predicting the extent of turf damage through analysis of the movement and behavior of golf course visitors, characterized in that turf repair within the golf course is performed based on information on the predicted extent of turf damage.
In claim 9,
The method for predicting the extent of turf damage is,
In the turf damage range prediction system, different weights are applied according to location and behavior information, including the accumulated number of movements of each golf course visitor to a specific location, the time spent at a specific location by each golf course visitor, and the swing of the golf club. step; and
In the turf damage extent prediction system, a method of predicting the extent of turf damage through analysis of the movements and behavior of golf course visitors, further comprising predicting whether the turf is damaged according to the applied weight.
In claim 9,
The method for predicting the extent of turf damage is,
In the turf damage extent prediction system, visualizing the predicted extent of damage to the turf at each location by dividing it into a plurality of stages; and
A method of predicting the extent of turf damage through analysis of the movements and behavior of visitors to a golf course, further comprising providing the degree of turf damage for each visualized location to an administrator terminal to support maintenance management.