Ai-based garden design system having company recommendation function

Abstract

The present invention relates to an AI-based garden design system having a company recommendation function, whereby a garden can be designed in consideration of the type, color, and quantity of plantings selected by a client, and sunlight information, climate information, and feature information dependent on location information of a construction target area requested by the client, an estimate for construction costs dependent on the garden design can be calculated, and a company required for garden construction can be recommended.

Description

AI-based garden design system with business recommendation features

[0001] The present invention relates to an AI-based garden design system having a company recommendation function that can design a garden by considering the type, color, and quantity of plants 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, calculate an estimate for the construction costs associated with the garden design, and recommend companies required for garden construction.

[0002] Generally, gardens (landscapes) are created in the yards of multi-family houses or country houses as needed or in accordance with building codes to achieve purposes such as environmental improvement, visual enhancement, improvement of quality of life, health promotion, and environmental protection.

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

[0004] Meanwhile, it is desirable for a garden to be designed so that the most suitable types of plants are selected and planted in the most suitable locations, taking into account the amount of sunlight, climate, and topography of the construction site to be built, in order to improve life expectancy, reduce costs, and facilitate maintenance, while also meeting the client's requirements.

[0005] However, due to the lack of proper technology for designing gardens while considering the aforementioned factors, the reality is that only standardized gardens can be designed and constructed. Furthermore, there are limitations in accurately predicting construction costs, making it difficult to determine if the costs are reasonable. Additionally, it is difficult to find construction companies that offer reasonable non-construction costs.

[0006] Therefore, in order to break away from standardized structures and construct gardens with unique characteristics at a reasonable cost, it is necessary to research and develop technology that can conveniently and effectively design a garden that meets the client's requirements while considering the characteristics of the construction site, provide an estimate for construction costs, and recommend contractors needed for garden construction.

[0007] The present invention was developed to resolve the aforementioned problems, and aims to provide an AI-based garden design system that can conveniently and effectively design a garden that meets the client's requirements while considering the characteristics of the construction area to enable the construction of a garden with unique characteristics by breaking away from a standardized structure, calculate an estimate of the construction costs associated with the garden design, and recommend a company needed for the garden construction.

[0008] The objectives of the present invention are not limited to those mentioned above, and other unmentioned objectives may be clearly understood from the descriptions below and may be sufficiently included in the objectives of the present invention.

[0009] The AI-based garden design system having a company recommendation function according to the present invention for achieving the above objective is intended to design a customized garden for a construction target area requested by a client, and comprises: a sunlight information collection unit that collects sunlight information based on shadow changes over a day in the construction target area; a climate information collection unit that collects climate information based on location information regarding the construction target area; a feature information collection unit that collects feature information existing in the construction target area; a construction possible area determination unit that sets a construction possible area where planting can be installed within the construction target area based on the sunlight information and the feature information; a planting recommendation unit that recommends the type and quantity of planting that can be installed in the construction possible area by considering the climate information and the sunlight information among a plurality of types of planting that can be installed for a garden; a planting selection unit that selects the type and quantity of planting to be installed in the construction possible area according to the client's input from among the planting recommended by the planting recommendation unit; and a virtual construction image generation unit that generates a virtual construction image of the construction target area in which the planting selected by the planting selection unit is installed in the construction possible area. It may be composed of: an estimate calculation unit that estimates and provides the construction cost required to construct the planting in the construction-possible area according to the type and quantity of planting selected by the planting selection unit; and a company recommendation unit that recommends a company required to construct a garden in the construction-possible area using the planting selected by the planting selection unit.

[0010] The AI-based garden design system with a company recommendation function according to the present invention, based on the above-described configuration, sets a construction zone where planting can be done within a construction target area based on sunlight information and feature information, recommends the types of plants that can be done in the construction target area based on climate information, determines the quantity of plants determined by the type according to the recommendation according to the area of ​​the construction zone, generates and provides a virtual construction image of the state in which the plants with the determined type and quantity are installed in the construction zone of the construction target area, and estimates and provides the construction costs required for planting. By doing so, it is possible to conveniently and effectively design a garden that meets the client's requirements while considering the characteristics of the construction target area, by breaking away from a standardized structure, and not only can the construction costs associated with garden construction be checked in advance and the feasibility of the construction costs be assessed beforehand, but also conveniently recommends suitable companies required for garden construction.

[0011] FIG. 1 is a configuration diagram illustrating an AI-based garden design system with a company recommendation function according to a preferred embodiment of the present invention.

[0012] FIG. 2 is an example diagram illustrating the state in which a construction target area is divided into a plurality of first unit zones by the sunlight collection unit of an AI-based garden design system having a company recommendation function according to a preferred embodiment of the present invention.

[0013] FIG. 3 is an example diagram illustrating a state in which a construction target area is divided into a plurality of second unit zones by a construction-possible zone determination unit of an AI-based garden design system having a company recommendation function according to a preferred embodiment of the present invention.

[0014] FIG. 4 is an example diagram illustrating a constructionable area determined by the constructionable area determination unit of an AI-based garden design system having a company recommendation function according to a preferred embodiment of the present invention.

[0015] The AI-based garden design system having a company recommendation function according to the present invention for achieving the above objective is intended to design a customized garden for a construction target area requested by a client, and comprises: a sunlight information collection unit that collects sunlight information based on shadow changes over a day in the construction target area; a climate information collection unit that collects climate information based on location information regarding the construction target area; a feature information collection unit that collects feature information existing in the construction target area; a construction possible area determination unit that sets a construction possible area where planting can be installed within the construction target area based on the sunlight information and the feature information; a planting recommendation unit that recommends the type and quantity of planting that can be installed in the construction possible area by considering the climate information and the sunlight information among a plurality of types of planting that can be installed for a garden; a planting selection unit that selects the type and quantity of planting to be installed in the construction possible area according to the client's input from among the planting recommended by the planting recommendation unit; and a virtual construction image generation unit that generates a virtual construction image of the construction target area in which the planting selected by the planting selection unit is installed in the construction possible area. It may be composed of: an estimate calculation unit that estimates and provides the construction cost required to construct the planting in the construction-possible area according to the type and quantity of planting selected by the planting selection unit; and a company recommendation unit that recommends a company required to construct a garden in the construction-possible area using the planting selected by the planting selection unit.

[0016] The present invention relates to an AI-based garden design system having a company recommendation function that can conveniently design a garden provided for purposes such as environmental improvement, visual enhancement, improvement of quality of life, health promotion, and environmental protection in the yard of a multi-family house or country house, or in accordance with building codes.

[0017] In particular, the AI-based garden design system with a company recommendation function according to the present invention is characterized by being able to design a garden by considering sunlight information, climate information, and geographical information based on the location information of the construction target area requested by the client, as well as the type, color, and quantity of plants selected by the client, calculate an estimate for the construction costs associated with the garden design, and recommend companies necessary for the garden construction.

[0018]

[0019] Hereinafter, an AI-based garden design system with a company recommendation function 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 with a company recommendation function according to a preferred embodiment of the present invention is designed to automatically design a customized garden for a construction target area (10) requested by a client, and as shown in FIG. 1, it may be composed of a sunlight information collection unit (200), a climate information collection unit (300), a geographical information collection unit (400), a construction feasible area determination unit (500), a planting recommendation unit (600), a planting selection unit (700), a virtual construction image generation unit (800), an estimate calculation unit (900), and a company recommendation unit (100).

[0021]

[0022] Here, the sunlight information collection unit (200), climate information collection unit (300), feature information collection unit (400), construction feasible area determination unit (500), planting recommendation unit (600), planting selection unit (700), virtual construction image generation unit (800), and estimate calculation unit (900) may be included in a management server (not shown) managed by the contractor to automatically design a customized garden.

[0023] In addition, the management server can communicate via wired or wireless communication with a client's terminal (not shown) who wishes to use the customized garden design service, and can also receive input such as location information of the construction target area and selection information regarding planting to be installed in the construction target area, along with the client's personal information, based on the client's input operations through the client's terminal.

[0024]

[0025] First, the above 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 based on the change in shadows during the day in the construction target area (10) based on the height of surrounding topographic features (50), including buildings or mountains, existing in the surrounding area, 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 calculation unit (250), as shown in FIG. 1.

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

[0029] At this time, the surrounding terrain feature search unit (210) can search for surrounding terrain features (50) that cause shadows on the construction target area (10) in the surrounding area of ​​the construction target area (10) using an online map including Naver Map, Daum Map, Google Map, etc., which is accessible online via the web on the internet.

[0030] The above surrounding terrain feature height information collection unit (220) can collect height information for surrounding terrain features (50) collected from the surrounding terrain feature information collection unit (210).

[0031] Even 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) by using an online map including Naver Map, Daum Map, Google Map, etc., which is accessible online via the web on the internet.

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

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

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

[0035] The above-mentioned sunlight information calculation unit (250) can calculate individual sunlight information for each of the first unit zones (20) based on whether shadows are formed, time, and area for the plurality of first unit zones (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 calculation unit (250) can calculate individual sunlight information within the range of '0' to '10' in inverse proportion to the time and area of ​​whether a shadow is formed for each first unit area (20).

[0037] For example, if the first unit zone (20) is in the season of spring (average day length 12 hours) and no shadows are formed, the individual sunlight information can be calculated as '10', and if the second unit zone (20) is in the season of spring and shadows are formed and the time of shadowing is 6 hours and the average area of ​​shadowing corresponds to 1 / 2 of the total area, the individual sunlight information can be calculated as '3', and if the third unit zone (20) is in the season of spring and shadows are formed and the time of shadowing is 3 hours and the average area of ​​shadowing is equal to the total area, the sunlight information can be calculated as '6'.

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

[0039] However, when the sunlight information calculation unit (250) calculates the average value for individual sunlight information, it may 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 growth environment of the planting area (10) based on the location information of the construction area (10) through a climate information provision site that is accessible online via the web on the internet.

[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 the past 10 years by administrative district unit as shown in Table 1 below.

[0044]

[0045] Regional Average Temperature (°C) Maximum Temperature (°C) Minimum Temperature (°C) Average Precipitation (mm) Average Humidity (%) Daegwallyeong 7.1 12.2 2.3 169 5.1 73.3 Sokcho 12.5 16.6 8.7 140 7.2 65.0 Ganghwa 11.3 16.3 6.6 126 6.2 69.2 Bonghwa 10.0 3.7 17.2 117 5.6 69.5 Uljin 12.8 8.7 17.5 118 1.7 67.2 Miryang 13.6 20.3 7.9 129 4.7 66.4 Namhae 14.3 19.3 10.1 19 21.2 65.4 Haenam 13.5 19.0 8.4 128 2.0 73.1 Seogwipo 16.9 20.3 13.9 198 9.6 69.8

[0046] Therefore, by collecting climate information of the administrative district including location information of the construction target area (10), it can be used as climate information for the construction target area (10).

[0047] Next, the above-mentioned feature information collection unit (400) can collect feature information existing on the construction target area (10).

[0048] That is, the land information collection unit (400) can collect land information existing on the ground within the construction target area (10) so as to effectively identify where in the construction target area (10) the area where planting can be done is partially possible.

[0049] 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 feature information collection unit (430) for each unit area, as shown in FIG. 1.

[0050] The above construction target area image acquisition unit (410) can acquire a planar image of the construction target area (10) through an online map including Naver Map, Daum Map, Google Map, etc., which can be accessed online via the web on the internet.

[0051] As shown in FIGS. 2 and 3, the second unit area division unit (420) can divide the construction target area (10) into a first unit area (20) divided by the first unit area division unit (230) of the sunlight information collection (200) and a plurality of second unit areas (30) having the same area according to their locations.

[0052] 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 planar image acquired by the construction target area image acquisition unit (410) through an object analysis technique using image processing.

[0053] At this time, the unit area-specific ground information collection unit (430) can determine whether the ground appearing in the planar image of the construction target area (10) is a ground that can be planted or a ground that cannot be planted.

[0054] That is, the unit area-specific ground information collection unit (430) can compare feature information representing the ground on the pixel with feature information of an object extracted from a planar image of the construction target area (10) to determine whether the object extracted from the planar image of the construction target area (10) is a constructible object or a planting-unconstructible object.

[0055]

[0056] Next, the above constructionable area determination unit (500) can determine an area where planting can be constructed within the construction target area (10) based on sunlight information and feature information of the construction target area (10).

[0057] To this end, the constructionable area determination unit (500) may be composed of a unit area overlap unit (510) and a constructionable area determination unit (520) as shown in FIG. 1.

[0058] As shown in FIG. 3, 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 feature information collection section (400) at corresponding locations.

[0059] The above constructionable area determination unit (520) can determine a constructionable area (40) based on sunlight information for a first unit area (20) and feature information for a second unit area (30) that are overlapped by each other by location by the unit area overlap unit (510) as shown in FIG. 4.

[0060] That is, the construction-possible area determination unit (520) can determine that a corresponding area is a construction-possible area (40) if the sunlight information of the overlapping areas is not '0' and the feature information is a feature that can be planted.

[0061] In other words, the construction-possible area determination unit (520) can exclude a corresponding area from the construction-possible area (40) if the sunlight information of the overlapping areas is '0' or if the feature information is that planting construction is impossible.

[0062]

[0063] Next, the planting recommendation unit (600) can recommend planting to be constructed in the construction-possible area (40) determined by the construction-possible area determination unit (400) based on the climate information of the construction target area (10) collected by the climate information collection unit (300).

[0064] 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 the planting groups selected in advance of the multiple types of plants that are relatively frequently used when constructing a garden.

[0065] 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 shown in FIG. 1.

[0066] The above planting information storage unit (610) can pre-select multiple types of plants that can be installed for ornamental purposes in a garden and store them along with growth information.

[0067] That is, the planting information storage unit (610) can store growth information including temperature conditions, sunlight conditions, and water supply conditions suitable for growth for each type of planting, based on the landscaping plant material guide, etc., as shown in Table 2 below.

[0068]

[0069] Planting Type Temperature Condition (°C) Sunlight Condition (Hour) Humidity Condition (%) Crape Myrtle 10~356~830~55 Red-flowered Photinia 0~303~640~70 Ilex crenata 15~356~835~65 Hydrangea 10~353~650~65 Thuja 15~256~840~55 Boxwood 20~353~640~65 Pinus 20~353~630~60 Juniperus 5~356~820~50 Maple 0~353~635~55 Cherry 20~406~820~80

[0070] The above growth information matching unit (620) can compare 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 planting material stored in the planting information storage unit (610), and match the type of planting material 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 planting materials stored in the planting information storage unit (610). 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 possible zone (40) of the construction target area (10).

[0071]

[0072] Next, the plant selection unit (700) can select the type of plant that the client wants to plant in the construction target area (10) from among the recommended plants recommended by the plant recommendation unit (600).

[0073] To this end, the plant selection unit (700) may be composed of a recommended plant information transmission unit (710), a plant type determination unit (720), and a plant quantity determination unit (730), as shown in FIG. 1.

[0074] The above recommended planting information transmission unit (710) can transmit related information, including images, growth environment, and price of the recommended planting recommended by the planting recommendation unit (600), to a terminal so that the client can check it.

[0075] The above planting type determination unit (720) can determine the type of planting to be constructed in the construction possible area (40) of the construction target area (10) among the recommended plants, based on the input of the client through the terminal after the client checks the relevant information regarding the recommended plants transmitted by the recommended planting information transmission unit (710).

[0076] The above planting quantity determining unit (730) can determine the quantity of planting, whose type is determined by the planting type determining unit (720), to correspond to the area of ​​the construction possible zone (40). At this time, the planting quantity determining unit (730) can determine the quantity of planting to correspond to the area of ​​the construction possible zone (40) by considering the area occupied by the determined planting.

[0077]

[0078] Next, the virtual construction image generation unit (800) can generate an image of the state in which the plant selected by the plant selection unit (700) is constructed in the construction target area (10) and transmit it to the client's terminal so that the client can verify it.

[0079] That is, the virtual construction image generation unit (800) can generate a virtual construction image in which an image of a planting decided to be constructed in a construction-possible area (40) of a construction target area (10) is placed in a construction-possible area (40) on a planar image of the construction target area (10), and transmit it to the client's terminal.

[0080] Then, the client can check the virtual construction image of the type of planting they selected being virtually constructed in the construction-possible area (40) of the construction target area (10) through the terminal, and check the garden atmosphere in advance before constructing the garden.

[0081]

[0082] Next, the above-mentioned estimate calculation unit (900) can estimate the construction cost required to plant in the construction-possible area (40) according to the type and quantity of planting selected by the client by the planting selection unit (700) and transmit it to the client's terminal.

[0083] To this end, the estimate calculation unit (900) may be composed of: a type-specific total unit price calculation unit (910) that calculates the total unit price of each type of planting based on predetermined type-specific unit price information according to the type-specific unit price and quantity of each type of planting; a material cost calculation unit (920) that calculates the material cost by summing all the type-specific total unit prices of the planting and then adding up the cost of auxiliary materials required for the construction of the planting; a construction cost calculation unit (930) that calculates the construction cost based on predetermined construction cost information according to the number of personnel, working time, and construction equipment required to construct the planting in the construction-possible area (40) according to the type and quantity of the planting; and a construction cost estimation unit (940) that estimates the construction cost by summing the material cost calculated in the planting cost calculation unit (920) and the construction cost calculated in the construction cost calculation unit (930) and transmits it to the client's terminal.

[0084] However, the construction cost estimate section (940) can estimate construction costs including only material costs when the client directly constructs the garden, can estimate construction costs including material costs and construction costs based on the construction ratio when a construction company constructs part of the garden, and can estimate construction costs including material costs and construction costs in full when a construction company constructs the entire garden.

[0085] Therefore, the client can receive and verify the construction cost according to the type and quantity of planting materials selected by the client through the estimate calculation unit (900) on their terminal, so they can be helped to determine whether the construction cost is reasonable.

[0086]

[0087] Finally, the above-mentioned company recommendation unit (1000) can recommend to the client a company needed to construct a garden in the construction area (40) of the construction target area (10).

[0088] That is, the company recommendation section (1000) can select and recommend to the client the design company, material supplier, and construction company required for constructing the garden, respectively, according to the type and quantity of planting materials selected by the client.

[0089] To this end, the company recommendation section (1000) may be composed of a design company recommendation section (1010), a material supplier recommendation section (1020), and a construction company recommendation section (1030).

[0090] The above design firm recommendation unit (1010) can recommend at least one design firm suitable for the garden construction scale determined by the type and quantity of the planting materials from a list of design firms that have been classified and databased according to the construction scale.

[0091] The above material supplier recommendation unit (1020) can recommend at least one material supplier capable of supplying the corresponding planting material and auxiliary materials from a list of material suppliers that is databased by classifying material suppliers capable of supplying according to the type of planting material and the type of auxiliary materials required when constructing the planting material.

[0092] The above construction company recommendation unit (1030) can recommend at least one construction company that possesses the input and construction equipment capable of performing the construction of the corresponding planting material and auxiliary material from a list of construction companies that have been databased by classifying the manpower and construction equipment of the construction companies according to the planting material and auxiliary material.

[0093] Then, the client can select one of each of the design company, material supplier, and construction company that is deemed most suitable among at least one recommended by the company recommendation department (1000).

[0094]

[0095] The above-described embodiments are merely exemplary, and various other embodiments modified therefrom are possible for those skilled in the art.

[0096] Therefore, the true technical scope of protection of the present invention should include not only the above embodiments but also other embodiments that are variously modified according to the technical concept of the invention described in the following claims.

[0097]

[0098] The present invention relates to an AI-based garden design system having a company recommendation function that can design a garden by considering the type, color, and quantity of plants 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, calculate an estimate for the construction costs associated with the garden design, and recommend companies required for garden construction.

Claims

1. For the purpose of designing a customized garden for the construction site commissioned by the client, A sunlight information collection unit that collects sunlight information based on shadow changes over a day in the above-mentioned construction target area; A climate information collection unit that collects climate information based on location information regarding the above-mentioned construction target area; A feature information collection unit that collects feature information existing in the above-mentioned construction target area; A constructionable zone determination unit that sets a constructionable zone where planting can be carried out among the construction target area based on the above sunlight information and above feature information; A planting recommendation unit that recommends the type and quantity of planting suitable for construction in the construction-possible area, taking into account the climate information and sunlight information among multiple types of planting suitable for construction in a garden; A plant selection unit that selects the type and quantity of plants to be constructed in the construction-possible area according to the client's input from among the plants recommended by the plant recommendation unit; A virtual construction image generation unit that generates a virtual construction image of the construction target area in which the plant selected by the plant selection unit is constructed in the construction possible area; An estimate calculation unit that estimates and provides the construction cost required to install planting in the construction-possible area according to the type and quantity of planting selected by the planting selection unit; and An AI-based garden design system having a company recommendation function, characterized by comprising: a company recommendation unit that recommends a company needed when constructing a garden in the construction-possible area using a plant selected by the plant selection unit.

2. In Paragraph 1, The above company recommendation department A design firm recommendation unit that recommends a design firm to design a garden according to the type and quantity of plants selected by the above-mentioned plant selection unit; A material supplier recommendation unit that recommends a material supplier supplying the above-mentioned planting material and auxiliary materials required for the construction of the above-mentioned planting material; and An AI-based garden design system having a company recommendation function, characterized by comprising: a construction company recommendation unit that recommends a construction company possessing the manpower and construction equipment necessary for the construction of the above-mentioned planting materials and above-mentioned auxiliary materials.

3. In Paragraph 2, The above estimate calculation unit A unit price calculation unit by type that calculates the total unit price by type of the above-mentioned food materials according to the unit price by type and the quantity by type of the above-mentioned food materials; A material cost calculation unit that calculates material costs by adding up all the combined unit prices by type of the above-mentioned planting materials and then adding up the costs for auxiliary materials required for the construction of the planting materials; A construction cost calculation unit that calculates the construction cost based on the number of personnel, working hours, and construction equipment required to construct the above-mentioned planting according to the type and quantity of the above-mentioned planting; and An AI-based garden design system having an estimate calculation function comprising: a construction cost estimation unit that estimates and provides construction costs based on the above material costs and above construction costs.

4. In Paragraph 3, The above sunlight information collection unit A surrounding terrain feature search unit that searches for surrounding terrain features existing around the above-mentioned construction target area and causing shadows on the above-mentioned construction target area; A surrounding terrain feature height information collection unit that collects height information for the above-mentioned surrounding terrain features; A first unit zone division unit that divides the above construction target area into a plurality of first unit zones; A sunlight simulation unit that performs a sunlight simulation to determine whether shadows are formed, the time, and the area based on location information of the construction target area and height information of the surrounding topographic features during the day; and An AI-based garden design system with a company recommendation function, characterized by comprising: a sunlight information output unit that calculates individual sunlight information for each of the first unit zones based on whether shadows are formed, time, and area during the day according to the sunlight simulation, and outputs the average value of the calculated individual sunlight information as sunlight information.

5. In Paragraph 4, The above-mentioned property information collection department An image acquisition unit for acquiring a planar image of the above-mentioned construction target area; A second unit zone division unit that divides the above construction target area into a plurality of second unit zones on the above planar image; and An AI-based garden design system with a company recommendation function, characterized by comprising: a unit area feature information collection unit that collects feature information for each second unit area by identifying objects identifiable as features appearing on the pixels of the above-mentioned planar image through an object analysis technique using image processing.

6. In Paragraph 5, The above constructionable area determination unit A unit area overlapping section that overlaps the first unit area and the second unit area at corresponding locations; and An AI-based garden design system with a company recommendation function, characterized by comprising: a construction-possible area determination unit that determines, on a zone basis, the construction-possible area where planting can be constructed within the construction target area based on the sunlight information of the first unit area superimposed by the unit area superimposition unit and the feature information of the second unit area.

7. In Paragraph 6, The above-mentioned planting recommendation section A planting information storage unit that stores growth information for multiple types of planting materials suitable for garden construction; A growth information matching unit that matches the type of plant material whose growth information corresponds to the climate information among the plurality of types of plant materials stored in the plant material information storage unit; A recommended planting determination unit that determines the type of planting matched by the growth information matching unit as a recommended planting unit; and An AI-based garden design system with a company recommendation function, characterized by comprising: a quantity determination unit that determines the quantity of the recommended planting determined by the recommended planting determination unit to correspond to the area of ​​the construction-possible zone.

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