Landscaping engineering project intelligent management system

Abstract

The invention belongs to the technical field of intelligent management of landscaping, and discloses an intelligent management system for a landscaping engineering project. An original garden data set is collected and preprocessed, an initial garden data set is obtained, original garden data comprises a greening environment data set and a plant growth data set, and the greening environment data set comprises environment temperature, environment humidity, illumination intensity and soil humidity; the plant growth data set comprises plant growth duration, a plant growth state and a plant health state; analyzing the initial garden data set to obtain a greening reference value and a plant reference value, and performing classification to obtain a classification result; adjusting equipment in the garden according to a classification result; in general, the method has the remarkable advantages of being good in auxiliary operation effect, high in operation reference degree and excellent in project asset previewing capacity.

Description

Technical Field

[0001] The present invention relates to the technical field of garden greening intelligent management, and more specifically, to an intelligent management system for garden greening engineering projects. Background Art

[0002] Gardening and greening projects are projects for building landscape gardens and green spaces. Gardening and greening provides people with a good place to rest, culturally entertain, get close to nature, and satisfy people's desire to return to nature. It is an important measure to protect the ecological environment and improve the urban living environment. Gardening and greening generally refers to environmental construction projects including garden construction projects in garden city green spaces and scenic spots. It uses engineering technology to express garden art, integrating ground engineering structures and garden landscapes. With the rapid economic take-off in recent years, people's standards for living environment are also increasing. Gardening and greening can not only enhance people's daily life comfort, but also greatly guarantee people's health. However, in the experimental cultivation process of gardening and greening, there are still low production efficiency, difficulty in collecting plant status data, and complex processing of plant-related data.

[0003] The patent application with the publication number CN116757510A discloses an intelligent management system for landscaping engineering projects. The data analysis module performs regional analysis on the collected plant-related data to obtain the inclination, extension value and deformation index of the plant. By comparing and analyzing the inclination coefficient and the preset threshold, the staff is reminded to perform timely maintenance. The safety index is obtained by associating the inclination coefficient and the extension coefficient. The safety index and the deformation index are associated and fitted through the notification management module to obtain the maintenance factor, which is matched with the hierarchical strategy plan to improve management efficiency.

[0004] However, although the above-mentioned intelligent management system can obtain a certain degree of plant status data by analyzing and calculating the inclination, extension value and deformation index of the plants, the growth status of the plants is closely related to environmental factors. During the experimental cultivation stage of green plants, how to improve production efficiency, quickly collect plant status data and quickly process plant-related data are still problems that staff need to face directly.

[0005] In view of this, the present invention proposes an intelligent management system for landscaping engineering projects to solve the above problems. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solutions: comprising:

[0007] The data acquisition module is used to collect the original garden data set and perform preprocessing to obtain the initial garden data set. The original garden data set includes a green environment data set and a plant growth data set. The green environment data set includes ambient temperature, ambient humidity, light intensity and soil moisture. The plant growth data set includes plant growth time, plant growth status and plant health status.

[0008] Furthermore, the methods for collecting the original garden dataset include:

[0009] By installing temperature and humidity sensors, light sensors and soil moisture monitoring sensors in the garden, the ambient temperature, ambient humidity, light intensity and soil moisture are collected;

[0010] By installing plant monitoring equipment in the garden, data on plant growth duration, plant growth status and plant health status can be collected;

[0011] The preprocessing methods include data cleaning and data denoising to obtain the initial garden data set;

[0012] The data processing module is used to analyze the initial garden data set, obtain greening reference values ​​and plant reference values, and classify them to obtain classification results;

[0013] Further, the initial garden dataset was analyzed by:

[0014] Obtain the green environment dataset from the initial garden dataset;

[0015] Preset the ambient temperature threshold interval (A1, A2), substitute the ambient temperature into the ambient temperature threshold interval for comparison, and obtain the temperature state value H1;

[0016] Preset the ambient humidity threshold interval (B1, B2), substitute the ambient humidity into the ambient humidity threshold interval for comparison, and obtain the humidity state value H2;

[0017] Preset the light intensity threshold interval (C1, C2), substitute the light intensity into the light intensity threshold interval for comparison, and obtain the light state value H3;

[0018] Preset the soil moisture threshold interval (D1, D2), substitute the soil moisture into the soil moisture threshold interval for comparison, and obtain the soil state value H4;

[0019] The greening reference value is obtained by substituting into the calculation formula: La = H1 × E1 + H2 × E2 + H3 × E3 + H4 × E4, where E1, E2, E3 and E4 are respectively the preset weight factors;

[0020] Obtain the plant growth dataset from the initial garden dataset;

[0021] Obtain the growth state of the plant, preset the growth state threshold interval (seedling, growth, maturity), bring the plant growth state into the growth state threshold interval for comparison, and obtain the growth state value J2;

[0022] Identify the health status of the plant. When the health status of the plant is dead, the value is 1; when the health status of the plant is insect pests, the value is 2; when the health status of the plant is healthy, the value is 3;

[0023] By substituting into the calculation formula: Get plant reference values, where J1 is plant growth duration, J3 is total plant growth duration, J4 is optimal growth state value, and J5 is plant health state value;

[0024] Further, the classification methods include:

[0025] The preset environmental threshold F1, when the greening reference value is less than F1, a warning SMS is sent to the staff through the communication unit, when the greening reference value is greater than F1, no processing is done;

[0026] A health threshold interval (G1, G2) is preset. When the plant health status value is less than G1, a serious notification SMS is sent to the staff through the communication unit. When the plant health status value is greater than G1 and less than G2, a general notification SMS is sent to the staff through the communication unit. When the plant health status value is greater than G2, a notification SMS is sent to the staff through the communication unit.

[0027] Serious warning SMS includes information indicating that the plant growth environment is bad and requiring staff to enter the site for management; serious notification SMS includes information indicating that the plant growth status is seriously inconsistent with expectations and requiring staff to enter the site as soon as possible for treatment; general notification SMS includes information indicating that the plant growth status is poor and requiring staff to enter the site in the near future for treatment; notification SMS includes information indicating that the plant growth status is mature and requiring staff to enter the site for collection;

[0028] Pack the serious warning SMS, serious notification SMS, general notification SMS and notification SMS to obtain classification results;

[0029] A control execution module is used to adjust the equipment in the garden according to the classification results;

[0030] Further, the adjustment methods include:

[0031] According to the classification results, when a serious warning message appears, the green environment data set is read;

[0032] When the ambient temperature is too high or too low, the temperature in the garden is increased or decreased by controlling the temperature regulating device; when the ambient humidity is too high or too low, the humidity in the garden is increased or decreased by controlling the humidity regulating device; when the light intensity is too high or too low, the light intensity in the garden is increased or decreased by controlling the lighting system; when the soil humidity is too high or too low, the irrigation system is controlled to extend or immediately irrigate the garden soil;

[0033] The asset management module is used to count the plants in the garden and obtain the garden asset value;

[0034] Furthermore, the steps of performing statistics include:

[0035] Q1: Connect to the garden plant management platform to obtain the plant species in the garden, the number of plants of each species and the value of a single plant;

[0036] Q2: Read the staff work log to obtain information about the removed plants, including the number of removed plants and the total value of the removed plants;

[0037] Q3: Obtain the garden asset value by substituting into the calculation formula: Ya = N1 × N2 × N3-N4, where N1 is the plant species in the garden, N2 is the number of plants of each species, N3 is the value of a single plant, and N4 is the total value of the removed plants;

[0038] Further, S1: collecting the original garden data set and preprocessing it to obtain the initial garden data set, the original garden data includes a green environment data set and a plant growth data set, the green environment data set includes environmental temperature, environmental humidity, light intensity and soil moisture, and the plant growth data set includes plant growth time, plant growth status and plant health status;

[0039] S2: Analyze the initial garden data set, obtain greening reference values ​​and plant reference values, and classify them to obtain classification results;

[0040] S3: Adjust the equipment in the garden according to the classification results;

[0041] S4: Count the plants in the garden and obtain the garden asset value.

[0042] The technical effects and advantages of the present invention are as follows:

[0043] The present invention obtains an initial garden data set by preprocessing the original garden data set, so that the complex data about plants can be better normalized, which is convenient for subsequent data analysis and calculation. The greening reference value and plant reference value obtained by analyzing the initial garden data set can intuitively present the environmental status and plant health status in the garden to the staff, greatly reducing the work intensity and complexity of the staff. The classification results obtained after classification can make corresponding adjustments to the regulating equipment in the garden, so that the plants can obtain a better growth environment, reduce the damage rate of plants, and greatly reduce the cultivation cost of plants. Through the garden asset value, the staff can quickly obtain an intuitive understanding of the total value of the plants in the garden. Generally speaking, the present invention has the significant characteristics of good auxiliary operation effect, high operation reference degree and excellent preview project asset ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of an intelligent management system for landscaping engineering projects according to the present invention;

[0045] Figure 2 It is a schematic diagram of an intelligent management method for landscaping engineering projects according to the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Example 1

[0048] See also Figure 1 As shown, the intelligent management system for landscaping engineering projects described in this embodiment includes:

[0049] The data acquisition module is used to collect the original garden data set and perform preprocessing to obtain the initial garden data set. The original garden data set includes a green environment data set and a plant growth data set. The green environment data set includes ambient temperature, ambient humidity, light intensity and soil moisture. The plant growth data set includes plant growth time, plant growth status and plant health status.

[0050] Furthermore, the methods for collecting the original garden dataset include:

[0051] By installing temperature and humidity sensors, light sensors and soil moisture monitoring sensors in the garden, the ambient temperature, ambient humidity, light intensity and soil moisture are collected;

[0052] By installing plant monitoring equipment in the garden, the plant growth time, plant growth status and plant health status are collected;

[0053] It should be explained that the monitoring equipment includes high-definition cameras, pest detection lights and growth parameter monitors installed in the garden;

[0054] The preprocessing methods include data cleaning and data denoising to obtain the initial garden data set;

[0055] The data processing module is used to analyze the initial garden data set, obtain greening reference values ​​and plant reference values, and classify them to obtain classification results;

[0056] Further, the methods for analyzing the initial garden dataset include:

[0057] Obtain the green environment dataset from the initial garden dataset;

[0058] Preset the ambient temperature threshold interval (A1, A2), substitute the ambient temperature into the ambient temperature threshold interval for comparison, and obtain the temperature state value H1;

[0059] It should be explained that the temperature state value is 1 and 2. When the ambient temperature is less than A1 or greater than A2, the value is 1. When the ambient temperature is greater than A1 and less than A2, the value is 2.

[0060] Preset the ambient humidity threshold interval (B1, B2), substitute the ambient humidity into the ambient humidity threshold interval for comparison, and obtain the humidity state value H2;

[0061] It should be explained that the humidity state value is 1 and 2. When the ambient humidity is less than B1 or greater than B2, the value is 1. When the ambient temperature is greater than B1 and less than B2, the value is 2.

[0062] Preset the light intensity threshold interval (C1, C2), substitute the light intensity into the light intensity threshold interval for comparison, and obtain the light state value H3;

[0063] It should be explained that the light state value is 1 and 2. When the light intensity is less than C1 or greater than C2, the value is 1. When the light intensity is greater than C1 and less than C2, the value is 2.

[0064] Preset the soil moisture threshold interval (D1, D2), substitute the soil moisture into the soil moisture threshold interval for comparison, and obtain the soil state value H4;

[0065] It should be explained that the soil state value is 1 and 2. When the soil moisture is less than D1 or greater than D2, the value is 1. When the soil moisture is greater than D1 and less than D2, the value is 2.

[0066] The greening reference value is obtained by substituting into the calculation formula: La = H1 × E1 + H2 × E2 + H3 × E3 + H4 × E4, where E1, E2, E3 and E4 are respectively the preset weight factors;

[0067] Obtain the plant growth dataset from the initial garden dataset;

[0068] Obtain the growth state of the plant, preset the growth state threshold interval (seedling, growth, maturity), bring the plant growth state into the growth state threshold interval for comparison, and obtain the growth state value J2;

[0069] It should be explained that the growth state value is a natural number between 1 and 4. When the plant growth state is less than the seedling, the value is 1; when the plant growth state is greater than the seedling but less than the growth, the value is 2; when the plant growth state is greater than the growth but less than the maturity, the value is 3; when the plant growth state is greater than the maturity, the value is 4;

[0070] Identify the health status of the plant. When the health status of the plant is dead, the value is 1; when the health status of the plant is insect pests, the value is 2; when the health status of the plant is healthy, the value is 3;

[0071] By substituting into the calculation formula: Get plant reference values, where J1 is plant growth duration, J3 is total plant growth duration, J4 is optimal growth state value, and J5 is plant health state value;

[0072] It needs to be explained that the optimal growth state value is when the plant growth state value is 4;

[0073] Further classification methods include:

[0074] The preset environmental threshold F1, when the greening reference value is less than F1, a warning SMS is sent to the staff through the communication unit, when the greening reference value is greater than F1, no processing is done;

[0075] A health threshold interval (G1, G2) is preset. When the plant health status value is less than G1, a serious notification SMS is sent to the staff through the communication unit. When the plant health status value is greater than G1 and less than G2, a general notification SMS is sent to the staff through the communication unit. When the plant health status value is greater than G2, a notification SMS is sent to the staff through the communication unit.

[0076] Serious warning SMS includes information indicating that the plant growth environment is bad and requiring staff to enter the site for management; serious notification SMS includes information indicating that the plant growth status is seriously inconsistent with expectations and requiring staff to enter the site as soon as possible for treatment; general notification SMS includes information indicating that the plant growth status is poor and requiring staff to enter the site in the near future for treatment; notification SMS includes information indicating that the plant growth status is mature and requiring staff to enter the site for collection;

[0077] Pack the serious warning SMS, serious notification SMS, general notification SMS and notification SMS to obtain classification results;

[0078] A control execution module is used to adjust the equipment in the garden according to the classification results;

[0079] Further, the adjustment methods include:

[0080] According to the classification results, when a serious warning message appears, the green environment data set is read;

[0081] When the ambient temperature is too high or too low, the temperature in the garden is increased or decreased by controlling the temperature regulating device; when the ambient humidity is too high or too low, the humidity in the garden is increased or decreased by controlling the humidity regulating device; when the light intensity is too high or too low, the light intensity in the garden is increased or decreased by controlling the lighting system; when the soil humidity is too high or too low, the irrigation system is controlled to extend or immediately irrigate the garden soil;

[0082] The asset management module is used to count the plants in the garden and obtain the garden asset value;

[0083] Furthermore, the steps of performing statistics include:

[0084] Q1: Connect to the garden plant management platform to obtain the plant species in the garden, the number of plants of each species and the value of a single plant;

[0085] Q2: Read the staff work log to obtain information about the removed plants, including the number of removed plants and the total value of the removed plants;

[0086] Q3: By substituting the calculation formula: Ya = N1 × N2 × N3-N4, we can get the garden asset value, where N 1 is the plant species in the garden, N2 is the number of plants of each species, N3 is the value of a single plant, and N4 is the total value of the removed plants;

[0087] This embodiment has the beneficial effect of obtaining an initial garden data set by preprocessing the original garden data set, so that the complex data about plants can be better normalized, which is convenient for subsequent data analysis and calculation. The greening reference value and plant reference value obtained by analyzing the initial garden data set can intuitively present the environmental status and plant health status in the garden to the staff, greatly reducing the work intensity and complexity of the staff. The classification results obtained after classification can make corresponding adjustments to the regulating equipment in the garden, so that the plants can obtain a better growth environment, reduce the damage rate of plants, and greatly reduce the cultivation cost of plants. Through the garden asset value, the staff can quickly obtain an intuitive understanding of the total value of the plants in the garden. Generally speaking, the present invention has the significant characteristics of good auxiliary operation effect, high operation reference degree and excellent preview project asset ability.

[0088] Example 2

[0089] See also Figure 2 As shown, the part not described in detail in this embodiment is described in Example 1, which provides an intelligent management method for a garden greening project, including: S1: collecting an original garden data set, and preprocessing it to obtain an initial garden data set, the original garden data includes a greening environment data set and a plant growth data set, the greening environment data set includes ambient temperature, ambient humidity, light intensity and soil humidity, and the plant growth data set includes plant growth time, plant growth status and plant health status;

[0090] S2: Analyze the initial garden data set, obtain greening reference values ​​and plant reference values, and classify them to obtain classification results;

[0091] S3: Adjust the equipment in the garden according to the classification results;

[0092] S4: Count the plants in the garden and obtain the garden asset value.

[0093] Example 3

[0094] This embodiment discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the operation mode of the intelligent management method for landscaping engineering projects provided above is implemented.

[0095] Since the electronic device introduced in this embodiment is an electronic device used to implement a landscaping project intelligent management method in the embodiment of this application, based on the landscaping project intelligent management method introduced in the embodiment of this application, the technical personnel of this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application is not described in detail here. As long as the technical personnel of this field implement the electronic device used in the landscaping project intelligent management method in the embodiment of this application, it belongs to the scope of protection of this application.

[0096] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0097] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technical users in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. An intelligent management system for landscaping projects, characterized in that: include: The data acquisition module is used to collect the original garden data set and perform preprocessing to obtain the initial garden data set. The original garden data set includes a green environment data set and a plant growth data set. The green environment data set includes ambient temperature, ambient humidity, light intensity and soil moisture. The plant growth data set includes plant growth time, plant growth status and plant health status. The data processing module is used to analyze the initial garden data set, obtain greening reference values ​​and plant reference values, and classify them to obtain classification results; A control execution module is used to adjust the equipment in the garden according to the classification results; The asset management module is used to count the plants in the garden and obtain the garden asset value.

2. According to claim 1, the intelligent management system for landscaping projects is characterized in that: The methods for collecting original garden datasets include: By installing temperature and humidity sensors, light sensors and soil moisture monitoring sensors in the garden, the ambient temperature, ambient humidity, light intensity and soil moisture are collected; By installing plant monitoring equipment in the garden, the plant growth time, plant growth status and plant health status are collected; The preprocessing methods include data cleaning and data denoising to obtain the initial garden data set.

3. The intelligent management system for landscaping projects according to claim 2 is characterized in that: The initial garden dataset was analyzed by: Obtain the green environment dataset from the initial garden dataset; Preset the ambient temperature threshold interval (A1, A2), substitute the ambient temperature into the ambient temperature threshold interval for comparison, and obtain the temperature state value H1; Preset the ambient humidity threshold interval (B1, B2), substitute the ambient humidity into the ambient humidity threshold interval for comparison, and obtain the humidity state value H2; Preset the light intensity threshold interval (C1, C2), substitute the light intensity into the light intensity threshold interval for comparison, and obtain the light state value H3; Preset the soil moisture threshold interval (D1, D2), substitute the soil moisture into the soil moisture threshold interval for comparison, and obtain the soil state value H4; The greening reference value is obtained by substituting into the calculation formula: La = H1 × E1 + H2 × E2 + H3 × E3 + H4 × E4, where E1, E2, E3 and E4 are respectively the preset weight factors; Obtain the plant growth dataset from the initial garden dataset; Obtain the growth state of the plant, preset the growth state threshold interval (seedling, growth, maturity), bring the plant growth state into the growth state threshold interval for comparison, and obtain the growth state value J2; Identify the health status of the plant. When the health status of the plant is dead, the value is 1; when the health status of the plant is insect pests, the value is 2; when the health status of the plant is healthy, the value is 3; By substituting into the calculation formula: The plant reference values ​​are obtained, where J1 is the plant growth duration, J3 is the total plant growth duration, J4 is the optimal growth state value, and J5 is the plant health state value.

4. The intelligent management system for landscaping projects according to claim 3 is characterized in that: The classification methods include: The preset environmental threshold F1, when the greening reference value is less than F1, a warning SMS is sent to the staff through the communication unit, when the greening reference value is greater than F1, no processing is done; A health threshold interval (G1, G2) is preset. When the plant health status value is less than G1, a serious notification SMS is sent to the staff through the communication unit. When the plant health status value is greater than G1 and less than G2, a general notification SMS is sent to the staff through the communication unit. When the plant health status value is greater than G2, a notification SMS is sent to the staff through the communication unit. Serious warning SMS includes information indicating that the plant growth environment is bad and requiring staff to enter the site for management; serious notification SMS includes information indicating that the plant growth status is seriously inconsistent with expectations and requiring staff to enter the site as soon as possible for treatment; general notification SMS includes information indicating that the plant growth status is poor and requiring staff to enter the site in the near future for treatment; notification SMS includes information indicating that the plant growth status is mature and requiring staff to enter the site for collection; The serious warning text messages, serious notification text messages, general notification text messages and notification text messages are packaged to obtain classification results.

5. The intelligent management system for landscaping projects according to claim 4 is characterized in that: Ways to make adjustments include: According to the classification results, when a serious warning message appears, the green environment data set is read; When the ambient temperature is too high or too low, the temperature in the garden can be increased or decreased by controlling the temperature regulating equipment. When the ambient humidity is too high or too low, the humidity in the garden can be increased or decreased by controlling the humidity regulating equipment. When the light intensity is too high or too low, the light intensity in the garden can be increased or decreased by controlling the lighting system. When the soil humidity is too high or too low, the irrigation system can be controlled to extend or immediately irrigate the garden soil.

6. The intelligent management system for landscaping projects according to claim 5 is characterized in that: The steps to perform statistics include: Q1: Connect to the garden plant management platform to obtain the plant species in the garden, the number of plants of each species and the value of a single plant; Q2: Read the staff work log to obtain information about the removed plants, including the number of removed plants and the total value of the removed plants; Q3: The garden asset value is obtained by substituting the calculation formula: Ya=N1×N2×N3-N4, where N1 is the type of plants in the garden, N2 is the number of plants of each type, N3 is the value of a single plant, and N4 is the total value of the removed plants.

7. A method for intelligent management of landscaping projects, implemented according to the intelligent management system for landscaping projects according to claims 1-6, characterized in that: S1: Collect the original garden data set and preprocess it to obtain the initial garden data set. The original garden data includes the green environment data set and the plant growth data set. The green environment data set includes the ambient temperature, ambient humidity, light intensity and soil moisture. The plant growth data set includes the plant growth time, plant growth status and plant health status. S2: Analyze the initial garden data set, obtain greening reference values ​​and plant reference values, and classify them to obtain classification results; S3: Adjust the equipment in the garden according to the classification results; S4: Count the plants in the garden and obtain the garden asset value.

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