Ai-based garden design system taking into account information about sunlight, climate and terrain features

Abstract

The present invention relates to an AI-based garden design system that takes into account information about sunlight, climate and terrain features, and can design a garden in consideration of the type, color, and quantity of plantings selected by a client together with the sunlight information, climate information and terrain feature information according to location information of a target construction area requested by the client.

Description

An AI-based garden design system that takes into account sunlight, climate, and terrain information.

[0001] The present invention relates to an AI-based garden design system that takes into account sunlight, climate, and feature information, which can design a garden by taking into account sunlight information, climate information, and feature information according to location information of a construction site requested by a client, as well as the type, color, and quantity of planting materials selected by the client.

[0002] In general, gardens (landscaping) are created in the yards of multi-family houses or country houses according to necessity or building codes to achieve the purposes of improving the environment, enhancing visual appearance, improving quality of life, promoting health, and protecting the environment.

[0003] In particular, as the number of people seeking a nature-friendly lifestyle or a safe and comfortable life with their pets rapidly increases, the number of country houses is rapidly increasing, leading to a significant increase in interest in gardens.

[0004] Meanwhile, it is desirable to design a garden so that the most suitable types of plants are selected and planted in the most suitable locations while considering the sunlight, climate, and topography of the area to be constructed to improve life expectancy, reduce costs, and ease of management, and to meet the client's needs.

[0005] However, because the technology for designing gardens by taking the above-mentioned factors into consideration has not been properly developed, only uniform gardens can be designed and constructed.

[0006] Therefore, in order to break away from the standardized structure and construct a garden with unique characteristics, it is necessary to research and develop technologies that can conveniently and effectively design a garden that meets the client's needs while taking into account the characteristics of the construction target area.

[0007] The present invention was invented to solve the above-mentioned problems, and the purpose of the present invention is to provide an AI-based garden design system that takes into account regional characteristics, which can conveniently and effectively design a garden that meets the needs of the client while taking into account the characteristics of the target area for construction, so as to break away from a uniform structure and construct a garden with unique characteristics.

[0008] The purpose of the present invention is not limited to the purpose mentioned above, and other purposes not mentioned can be sufficiently included in the purpose of the present invention while being clearly understood from the description below.

[0009] In order to achieve the above object, the present invention provides an AI-based garden design system that considers sunlight, climate, and feature information, for designing a customized garden in a construction area requested by a client, and may be configured with: a sunlight information collection unit that collects sunlight information according to changes in shadows throughout the day in the construction area; a climate information collection unit that collects climate information based on location information about the construction area; a feature information collection unit that collects feature information existing in the construction area; a construction area determination unit that sets a construction area in the construction area where planting can be constructed based on the sunlight information and the feature information; a planting recommendation unit that recommends a type of planting that can be constructed in the construction area from among a plurality of types of plantings that can be constructed for a garden, taking into account the climate information and the sunlight information; a planting selection unit that selects a planting to be constructed in the construction area from among the plantings recommended by the planting recommendation unit, according to an input from the client; and a virtual construction image generation unit that generates a virtual image of the construction area in which the planting selected by the planting selection unit is constructed in the construction area.

[0010] The AI-based garden design system according to the present invention, which takes into account sunlight, climate, and feature information, sets a construction zone where planting can be constructed among the construction target areas based on sunlight and feature information, recommends the types of plantings that can be constructed in the construction target areas based on climate information, and determines the quantity of plantings of which types are determined based on the recommendation according to the area of ​​the construction target area, and then creates a virtual construction image in which the plantings of which types and quantities are determined are constructed in the construction target area, thereby allowing a garden with unique characteristics to be constructed by breaking away from a uniform structure and conveniently and effectively designing a garden that meets the needs of the client while considering the characteristics of the construction target area.

[0011] Figure 1 is a diagram illustrating an AI-based garden design system that takes into account sunlight, climate, and property information according to a preferred embodiment of the present invention.

[0012] FIG. 2 is an exemplary diagram showing a state in which a construction target area is divided into a plurality of first unit zones by a sunlight collection unit of an AI-based garden design system that takes into account sunlight, climate, and property information according to a preferred embodiment of the present invention.

[0013] FIG. 3 is an exemplary diagram showing a state in which a construction target area is divided into a plurality of second unit areas by a construction area determination unit of an AI-based garden design system that takes into account sunlight, climate, and property information according to a preferred embodiment of the present invention.

[0014] FIG. 4 is an exemplary diagram illustrating a construction area determined by a construction area determination unit of an AI-based garden design system that takes into account sunlight, climate, and property information according to a preferred embodiment of the present invention.

[0015] In order to achieve the above object, the present invention provides an AI-based garden design system that considers sunlight, climate, and feature information, for designing a customized garden in a construction area requested by a client, and may be configured with: a sunlight information collection unit that collects sunlight information according to changes in shadows throughout the day in the construction area; a climate information collection unit that collects climate information based on location information about the construction area; a feature information collection unit that collects feature information existing in the construction area; a construction area determination unit that sets a construction area in the construction area where planting can be constructed based on the sunlight information and the feature information; a planting recommendation unit that recommends a type of planting that can be constructed in the construction area from among a plurality of types of plantings that can be constructed for a garden, taking into account the climate information and the sunlight information; a planting selection unit that selects a planting to be constructed in the construction area from among the plantings recommended by the planting recommendation unit, according to an input from the client; and a virtual construction image generation unit that generates a virtual image of the construction area in which the planting selected by the planting selection unit is constructed in the construction area.

[0016] The present invention relates to an AI-based garden design system that takes into account sunlight, climate, and property information, which can conveniently design a garden provided for the purposes of environmental improvement, visual enhancement, quality of life enhancement, health promotion, and environmental protection, etc., in the yard of a multi-family house or a country house, as necessary or in accordance with building laws.

[0017] In particular, the AI-based garden design system according to the present invention, which takes into account sunlight, climate, and feature information, is characterized by being able to design a garden by taking into account the type of planting selected by the client along with sunlight information, climate information, and feature information based on the location information of the construction target area requested by the client.

[0018]

[0019] Hereinafter, an AI-based garden design system that takes into account sunlight, climate, and property information according to a preferred embodiment of the present invention will be described in detail with reference to the attached drawings.

[0020] An AI-based garden design system (100) considering sunlight, climate, and feature information according to a preferred embodiment of the present invention is for automatically designing a customized garden in a construction target area (10) requested by a client, and as illustrated in FIG. 1, may be composed of a sunlight information collection unit (200), a climate information collection unit (300), a feature information collection unit (400), a construction area determination unit (500), a planting recommendation unit (600), a planting selection unit (700), and a virtual construction image generation unit (800).

[0021]

[0022] Here, the sunlight information collection unit (200), climate information collection unit (300), property information collection unit (400), construction area determination unit (500), planting recommendation unit (600), planting selection unit (700), and virtual construction image generation unit (800) may be included in a management server (not shown) managed by the construction company to automatically design a customized garden.

[0023] And the management server can communicate with the terminal (not shown) of the client who wants to use the customized garden design service through a wired or wireless communication network, and can also receive the client's personal information, location information of the construction area, and selection information on the planting to be constructed in the construction area, depending on the client's input operation through the terminal.

[0024]

[0025] First, the above-mentioned sunlight information collection unit (200) can collect sunlight information of the construction target area (10).

[0026] That is, the sunlight information collection unit (200) can collect sunlight information according to changes in shadows during the day in the construction target area (10) based on the height of surrounding terrain features (50), including buildings and mountains existing around the construction target area (10), centered on the location information of the construction target area (10).

[0027] To this end, the sunlight information collection unit (200) may be composed of a surrounding terrain feature search unit (210), a surrounding terrain feature height information collection unit (220), a first unit area division unit (230), a sunlight simulation unit (240), and a sunlight information production unit (250), as illustrated in FIG. 1.

[0028] The above-mentioned surrounding terrain feature search unit (210) can search for surrounding terrain features (50) that cast shadows on the construction target area (10), such as buildings or mountains existing in the vicinity, based on the location information of the construction target area (10).

[0029] At this time, the surrounding terrain feature exploration unit (210) can explore surrounding terrain features (50) that cast shadows on the construction target area (10) around the construction target area (10) by using an online map including Naver Map, Daum Map, Google Map, etc. that can be accessed online through the web on the Internet.

[0030] The above-mentioned surrounding terrain feature height information collection unit (220) can collect height information on surrounding terrain features (50) collected by the surrounding terrain feature information collection unit (210).

[0031] At this time, the surrounding terrain feature height information collection unit (220) can collect height information of surrounding terrain features (50) collected by the surrounding terrain feature information collection unit (210) using an online map including Naver Map, Daum Map, Google Map, etc., which can be accessed online through the web on the Internet.

[0032] The first unit area division part (230) can divide the construction target area (10) into a plurality of first unit areas as illustrated in FIG. 2. However, the first unit area division part (230) can divide the plurality of first unit areas (20) into areas of the same size or into areas of different or partially different sizes, depending on the planar shape of the construction target area (10).

[0033] The above-mentioned sunlight simulation unit (240) can perform sunlight simulation through a sunlight simulation model to determine whether a shadow is created and its time and area based on the location information of the construction target area (10) and the height information of the surrounding terrain features (50).

[0034] However, the sunlight simulation unit (240) can perform sunlight simulation based on the spring or fall season for the first unit area (20) of the construction target area (10) so as to meet the growing conditions of the planting material.

[0035] The above-mentioned sunlight information generating unit (250) can generate individual sunlight information for each of the first unit areas (20) based on the presence or absence of shadows and the time and area of ​​the plurality of first unit areas (20) forming the construction target area (10) according to the sunlight simulation performed by the sunlight simulation unit (240).

[0036] That is, the sunlight information generating unit (250) can generate individual sunlight information within the range of '0' to '10' in inverse proportion to the presence or absence of a shadow and the time and area for each first unit area (20).

[0037] For example, if the first unit area (20) of No. 1 is in spring (average day length of 12 hours) and no shadow is formed, the individual sunlight information can be calculated as '10'; if the first unit area (20) of No. 2 is in spring, a shadow is formed, the time for which the shadow is formed is 6 hours, and the average area of ​​the shadow is 1 / 2 of the total area, the individual sunlight information can be calculated as '3'; and if the first unit area (20) of No. 3 is in spring, a shadow is formed, the time for which the shadow is formed is 3 hours, and the average area of ​​the shadow is equal to the total area, the sunlight information can be calculated as '6'.

[0038] And the sunlight information generating unit (250) can calculate the average value of individual sunlight information within the range of '0' to '10' for each first unit area (20) and output it as the final sunlight information.

[0039] However, when calculating the average value for individual sunlight information, the sunlight information calculation unit (250) can calculate the average value excluding the first unit area (20) where the individual sunlight information is '0'.

[0040]

[0041] Next, the climate information collection unit (300) can collect climate information for the construction target area (10).

[0042] At this time, the climate information collection unit (300) can collect climate information including average temperature, minimum temperature, maximum temperature, average precipitation, and average humidity that affect the growing environment of plants through a climate information provision site that can be accessed online via the web on the Internet based on the location information of the construction target area (10).

[0043] That is, the climate information collection unit (300) can collect climate information including average temperature, minimum temperature, maximum temperature, average precipitation, and average humidity for each administrative district for the past 10 years, as shown in Table 1 below.

[0044]

[0045] Regional average temperature (℃) Highest temperature (℃) Lowest temperature (℃) Average precipitation (mm) Average humidity (%) Daegwallyeong 7.1 12.22.3 1695.173.3 Sokcho 12.5 16.68.7 1407.265.0 Ganghwa 11.3 16.36.6 1266.269.2 Bonghwa 10.03.7 17.21 175.669.5 Uljin 12.88.7 17.5 1181.767.2 Miryang 13.6 20.37.9 1294.766.4 Namhae 14.3 19.310.1 1921.265.4 Haenam 13.5 19.08.4 1282.073.1 Seogwipo 16.9 20.313.9 1989.669.8

[0046]

[0047] Therefore, by collecting climate information of the relevant administrative district including location information of the construction target area (10), it can be used as climate information of the construction target area (10).

[0048]

[0049] Next, the above-mentioned property information collection unit (400) can collect property information existing in the construction target area (10).

[0050] That is, the feature information collection unit (400) can collect feature information existing on the ground within the construction target area (10) so as to effectively determine where in the construction target area (10) there is a possible area where planting is possible.

[0051] To this end, the feature information collection unit (400) may be composed of a construction target area image acquisition unit (410), a second unit area division unit (420), and a unit area-specific feature information collection unit (430), as illustrated in FIG. 1.

[0052] The above construction target area image acquisition unit (410) can acquire a flat image of the construction target area (10) through an online map including Naver Map, Daum Map, Google Map, etc., which can be accessed online through the web on the Internet.

[0053] The second unit zone division part (420) above can divide the construction target area (10) into a first unit zone (20) divided by the first unit zone division part (230) of the sunlight information collection (200) as shown in FIGS. 2 and 3, and a plurality of second unit zones (30) having the same area according to their locations.

[0054] The above unit area feature information collection unit (430) can collect feature information by identifying objects that can be identified as features appearing on pixels of a flat image acquired by the construction target area image acquisition unit (410) through an object analysis technique using image processing.

[0055] At this time, the unit area-specific line information collection unit (430) can determine whether the feature appearing in the flat image of the construction target area (10) is a feature on which planting can be constructed or a feature on which planting cannot be constructed.

[0056] That is, the unit area-specific ground line information collection unit (430) can compare the feature information representing the dirt floor on a pixel with the feature information of an object extracted from a planar image of a construction target area (10) to determine the object extracted from the planar image of the construction target area (10) as one of a constructible feature and a non-constructible feature.

[0057]

[0058] Next, the construction-available area determination unit (500) can determine an area in the construction target area (10) where planting can be performed based on the sunlight information and property information of the construction target area (10).

[0059] To this end, the construction-possible area determination unit (500) may be composed of a unit area overlapping unit (510) and a construction-possible area determination unit (520), as illustrated in FIG. 1.

[0060] The above unit area overlapping section (510) can overlap the first unit area (20) divided by the first unit area division section (240) of the sunlight information collection section (200) and the second unit area (30) divided by the second unit area division section (420) of the property information collection section (400) at corresponding positions, as shown in FIG. 3.

[0061] The above construction-capable area determination unit (520) can determine a construction-capable area (40) based on the sunlight information for the first unit area (20) and the object information of the second unit area (30) that are each overlapped by the unit area overlapping unit (510) at each location, as illustrated in FIG. 4.

[0062] That is, the construction-available area determination unit (520) can determine an area as a construction-available area (40) if the sunlight information of the overlapping areas is not '0' and the feature information is a feature that can be used for planting construction.

[0063] In other words, the construction-available area determination unit (520) can exclude an area from the construction-available area (40) if the sunlight information of an overlapping area is '0' or the information on the object is such that planting construction is impossible.

[0064]

[0065] Next, the planting recommendation unit (600) can recommend planting materials to be constructed in the construction area (40) determined by the construction area determination unit (400) based on the climate information of the construction target area (10) collected by the climate information collection unit (300).

[0066] That is, the planting recommendation unit (600) can recommend to the client the type of planting that is most suitable for the climate information of the construction target area (10) from among a group of plantings that have been pre-selected from among multiple types of plantings that are relatively frequently used when constructing a garden.

[0067] To this end, the planting recommendation unit (600) may be composed of a planting information storage unit (610), a growth information matching unit (620), and a recommended planting decision unit (630), as illustrated in FIG. 1.

[0068] The above planting information storage unit (610) can select in advance multiple types of plants that can be installed as ornamental plants in a garden and store them together with growth information.

[0069] That is, the planting information storage unit (610) can store, based on the landscape plant material guide, etc., the growth information including temperature conditions, sunlight conditions, and water supply conditions suitable for growth for each type of planting material, as shown in Table 2 below.

[0070]

[0071] Planting type Temperature condition (℃) Sunlight condition (hours) Humidity condition (%) Crape myrtle 10~356~830~55 Rhododendron 0~303~640~70 Quince 15~356~835~65 Hydrangea 10~353~650~65 Thuja 15~256~840~55 Boxwood-20~353~640~65 Pine-20~353~630~60 Juniper 5~356~820~50 Maple 0~353~635~55 Cherry tree-20~406~820~80

[0072]

[0073] The above growth information matching unit (620) compares the climate information of the construction target area (10) collected by the climate information collection unit (300) and the sunlight information of the construction target area (10) collected by the sunlight information collection unit (200) with the growth information of the plant stored in the plant information storage unit (610), and can match the type of plant that satisfies the climate information of the construction target area (10) collected by the climate information collection unit (300) and the sunlight information of the construction target area (10) collected by the sunlight information collection unit (200) among the multiple types of plant stored in the plant information storage unit (610).

[0074] The above recommended planting determination unit (630) can determine the type of planting material matched by the growth information matching unit (620) as a recommended planting material that can be constructed in the construction area (40) of the construction target area (10).

[0075]

[0076] Next, the planting selection unit (700) can select the type of planting that the client wants to construct in the construction target area (10) from among the recommended plants recommended by the planting recommendation unit (600).

[0077] To this end, the planting selection unit (700) may be composed of a recommended planting information transmission unit (710), a planting type determination unit (720), and a planting quantity determination unit (730), as illustrated in FIG. 1.

[0078] The above recommended food information transmission unit (710) can transmit related information including images, growing environments, and prices of recommended food recommended by the food recommendation unit (600) to a terminal so that the requester can confirm them.

[0079] The above-mentioned planting type determination unit (720) can determine the type of planting to be constructed in the construction-available area (40) of the construction target area (10) from among the recommended plants based on input by the requester through the terminal after the requester confirms the related information on the recommended plants transmitted by the recommended planting information transmission unit (710).

[0080] The above planting quantity determination unit (730) can determine the quantity of planting materials, the type of which has been determined by the planting type determination unit (720), to correspond to the area of ​​the construction-available area (40). At this time, the planting quantity determination unit (730) can determine the quantity of planting materials to correspond to the area of ​​the construction-available area (40) by considering the area occupied by the determined planting materials.

[0081]

[0082] Lastly, the virtual construction image generation unit (800) can generate a virtual image of the state in which the planting material selected by the planting material selection unit (700) has been constructed in the construction target area (10) and transmit it to the client's terminal so that the client can confirm it.

[0083] That is, the virtual construction image generation unit (800) can generate a construction virtual image in which an image of a plant that has been decided to be constructed in a construction-available area (40) of a construction target area (10) is placed in a construction-available area (40) on a plane image of the construction target area (10) and transmit the image to the terminal of the requester.

[0084] Then, the client can check the virtual construction image of the type of planting material he / she selected being virtually constructed in the construction area (40) of the construction target area (10) through the terminal, thereby checking the garden atmosphere in advance before constructing the garden.

[0085]

[0086] The above-described embodiments are merely exemplary, and those skilled in the art may devise other embodiments with various modifications therefrom.

[0087] Therefore, the true technical protection scope of the present invention should include not only the above-described embodiments but also other embodiments modified in various ways by the technical idea of ​​the invention described in the following patent claims.

[0088] The present invention relates to an AI-based garden design system that takes into account sunlight, climate, and feature information, which can design a garden by taking into account sunlight information, climate information, and feature information according to location information of a construction site requested by a client, as well as the type, color, and quantity of planting materials selected by the client.

Claims

1. To design a customized garden in the construction area requested by the client. A sunlight information collection unit that collects sunlight information according to changes in shadows throughout the day in the above construction target area; A climate information collection unit that collects climate information based on location information for the above construction target area; A property information collection unit that collects property information existing in the above construction target area; A construction area determination unit that sets a construction area where planting can be constructed among the construction target areas based on the above sunlight information and the above property information; A planting recommendation section that recommends the type of planting that can be constructed in the construction area among multiple types of planting that can be constructed in the garden, taking into consideration the climate information and the sunlight information; A planting selection unit that selects plants to be constructed in the construction area according to the input of the requester among the plants recommended by the planting recommendation unit; and An AI-based garden design system that takes into account sunlight, climate, and property information, characterized by comprising a virtual construction image generation unit that generates a virtual image of the construction target area in which the planting material selected by the planting selection unit is constructed in the construction-available area.

2. In paragraph 1, The above sunlight information collection department A surrounding terrain feature search unit that searches for surrounding terrain features that exist around the construction target area and cause shadows in the construction target area; A surrounding terrain feature height information collection unit that collects height information on the explored surrounding terrain features; A first unit area division section that divides the above construction target area into multiple first unit areas; A sunlight simulation unit that simulates sunlight to determine whether shadows are created, and the time and area, throughout the day based on the location information of the construction target area and the height information of the surrounding terrain features; and An AI-based garden design system that takes into account sunlight, climate, and object information, characterized by comprising: a sunlight information output unit that calculates individual sunlight information for each of the first unit areas based on the occurrence, time, and area of ​​shadows during the day according to the sunlight simulation, and outputs the average value of the calculated individual sunlight information as sunlight information.

3. In paragraph 2, The above property information collection department An image acquisition unit that acquires a flat image of the above construction target area; A second unit zone division section that divides the above construction target area into a plurality of second unit zones on the plane image; and An AI-based garden design system that takes into account sunlight, climate, and feature information, characterized by comprising: a unit area feature information collection unit that collects feature information for each second unit area by identifying an object that can be identified as a feature appearing on the pixels of the above-mentioned flat image through an object analysis technique using image processing; 4. In paragraph 3, The above construction possible area determination section A unit area overlapping portion in which the first unit area and the second unit area overlap each other at corresponding locations; and An AI-based garden design system that takes into account sunlight, climate, and feature information, characterized by comprising: a construction-available area determination unit that determines, on a zone-by-zone basis, the construction-available area in which planting can be constructed among the construction target areas based on the sunlight information of the first unit area overlapped by the unit area overlapping unit and the feature information in the second unit area.

5. In paragraph 4, The above food recommendation section A planting information storage unit that stores growth information on multiple types of plants that can be planted for gardening; A growth information matching unit that matches the type of plant among the multiple types of plants stored in the plant information storage unit with the type of plant whose growth information corresponds to the climate information; A recommended planting material determination unit that determines the type of planting material matched by the above growth information matching unit as a recommended planting material; and An AI-based garden design system that takes into account sunlight, climate, and property information, characterized by comprising: a quantity determination unit that determines the quantity of the recommended planting material determined by the recommended planting determination unit to correspond to the area of ​​the construction area.

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