An intelligent landscaping management system based on the Internet of Things

Abstract

The present invention discloses an intelligent landscaping management system based on the Internet of Things, which belongs to the field of garden management technology, and includes: an image acquisition module, which is used to obtain image information in a landscaping area; a data acquisition module, which is used to obtain associated parameter information in the landscaping area; an analysis management platform, which is used to process and analyze the acquired image information and associated parameter information to generate a demand value, and judge whether the water demand in the landscaping area is normal according to the demand value status, and generate an execution strategy when the water demand is abnormal; a strategy execution module, which is used to adjust the watering time of the watering module according to the generated execution strategy; and a watering module, which is provided with a preset watering time, which is used to water the vegetation in the landscaping area. The present invention can adjust the watering time accordingly according to the size of the acquired demand value, and can accurately control the water demand of the vegetation to ensure the normal growth of the vegetation.

Description

Technical Field

[0001] The invention belongs to the technical field of garden management, and in particular relates to an intelligent garden greening management system based on the Internet of Things. Background Art

[0002] Landscaping is a comprehensive project that creates a beautiful natural environment and recreational space by transforming the terrain (or further building mountains, stacking stones, and managing water), planting trees and flowers, constructing buildings, and arranging garden paths, thereby providing people with a comfortable, healthy, and beautiful living environment.

[0003] With the acceleration of urbanization, gardening and greening have played an increasingly important role in urban construction. Since there are a large number of green plants in the garden, in order to ensure the normal growth of the green plants, special management personnel are needed to irrigate the garden. Existing management is mostly manual, and the green plants in the garden area are inspected manually to determine the degree of water shortage and open the irrigation system to irrigate the green plants in the garden; since manual operation can only adjust the irrigation time based on experience and is easily affected by the weather, the amount of water for each irrigation cannot be accurately adjusted, resulting in the required water volume not being the optimal water requirement for the green plants, thus affecting the normal growth of the green plants. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent landscaping management system based on the Internet of Things to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent landscaping management system based on the Internet of Things, the management system comprising:

[0007] An image acquisition module, the image acquisition module is used to obtain image information in the garden greening area, the image acquisition module includes a plurality of cameras;

[0008] A data acquisition module, the data acquisition module is used to acquire associated parameter information within the garden greening area;

[0009] An analysis and management platform, which is used to process and analyze the acquired image information and associated parameter information to generate a demand value, and to determine whether the water demand in the garden greening area is normal according to the demand value status, and to generate an execution strategy when the water demand is abnormal;

[0010] A strategy execution module, wherein the strategy execution module is used to adjust the watering duration of the watering module according to the generated execution strategy;

[0011] A watering module is provided with a preset watering duration for watering the vegetation in the garden greening area.

[0012] Furthermore, the associated parameter information includes soil moisture information in the gardening area and weather information before and after watering, and the weather information includes temperature information and light information.

[0013] Furthermore, the analysis management platform performs processing in the following manner:

[0014] The gardening area is divided into multiple sub-areas according to the area, and a camera, an irrigation device and multiple moisture sensors buried in the soil are installed in each sub-area;

[0015] Analyze and process the images obtained by the camera to obtain the vegetation status value of the sub-area ;

[0016] Analyze and process the humidity information obtained by the temperature sensor to obtain the soil humidity value of the sub-area ;

[0017] Analyze and process the acquired temperature and light information to obtain the overall environmental value of the garden greening area. ;

[0018] By formula Get the demand value of this sub-area ;

[0019] The required value will be obtained The threshold range of standard requirements preset by the system To compare:

[0020] when When , the water demand is considered normal;

[0021] Otherwise, the water demand is considered abnormal and an execution strategy is generated;

[0022] in, as well as is the proportionality coefficient.

[0023] Furthermore, the vegetation condition value The acquisition method is:

[0024] Collect a large amount of vegetation image data, the image data should include vegetation with different water shortage levels, and use image recognition technology to extract features related to the water shortage status of vegetation from the collected image data;

[0025] According to the degree of vegetation water shortage, multiple vegetation status value labels of different sizes are determined, and a classification model based on deep learning convolutional neural network is trained using the extracted features and the corresponding vegetation status value labels of different sizes;

[0026] Extract features from the vegetation image captured by the camera to obtain the current features, and use the current features as the input of the convolutional neural network classification model to obtain the vegetation status value of the sub-area .

[0027] Furthermore, the soil moisture value The acquisition method is:

[0028] Get the humidity value obtained by each humidity sensor in the sub-area , so that through the formula Get the average humidity value ,in is the number of humidity sensors, and ;

[0029] Get the humidity value change curve over time between the last watering and the current watering ;

[0030] By formula Get soil moisture value ;

[0031] in, as well as is the proportionality coefficient, The time point after the last watering was completed. The time node for this watering.

[0032] Furthermore, the overall environmental value The acquisition method is:

[0033] Get the average temperature of the landscaping area from the weather bureau between the last watering and the current watering , Maximum temperature And the average light , Highest Illumination At the same time, the average temperature of the landscaping area between this irrigation and the next irrigation is obtained from the Meteorological Bureau. , Maximum temperature And the average light , Highest Illumination ;

[0034] The overall environmental value is obtained by the following formula ;

[0035] ;

[0036] in, as well as , as well as , as well as All are proportional coefficients.

[0037] Further, the execution strategy includes an increase strategy and a decrease strategy;

[0038] when When , an increase strategy is generated;

[0039] when , a reduction strategy is generated.

[0040] Furthermore, the method for the strategy execution module to adjust the watering duration is:

[0041] When generating an increase strategy, the formula Adjust the watering time to ;

[0042] When generating a reduction strategy, the formula ;

[0043] in, To preset the watering time, is the maximum time allowed for adjustment, is the time conversion factor.

[0044] Beneficial effects of the present invention:

[0045] The present invention determines an irrigation time for irrigation equipment in a garden greening area according to historical experience data and experimental simulation data, collects image information of vegetation in the garden greening area through an image acquisition module, obtains soil moisture information in the garden greening area and weather information before and after irrigation through a data acquisition module, and then uploads the information to an analysis management platform for processing and analysis through the Internet of Things technology, obtains vegetation status values ​​according to image information, obtains soil moisture values ​​according to humidity information, obtains overall environmental values ​​according to weather information, and thus obtains demand values ​​through comprehensive analysis, and judges whether the water demand in the garden greening area is normal according to the condition of the demand value. When the water demand is abnormal, an execution strategy is generated to timely adjust the irrigation time to ensure that the water demand in the garden greening area just meets its own required amount, thereby ensuring the normal growth of vegetation.

[0046] The present invention can adjust the irrigation time accordingly according to the acquired demand value, and can accurately control the water demand of vegetation to ensure the normal growth of vegetation.

[0047] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0049] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0050] 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.

[0051] In one embodiment, an intelligent landscaping management system based on the Internet of Things is disclosed, such as Figure 1 As shown, the management system includes:

[0052] An image acquisition module, which is used to acquire image information within the garden greening area, and includes multiple cameras;

[0053] A data acquisition module is used to acquire associated parameter information in the garden greening area, wherein the associated parameter information includes soil moisture information in the garden greening area and weather information before and after watering, wherein the weather information includes temperature information and light information;

[0054] The analysis and management platform is used to process and analyze the acquired image information and related parameter information to generate demand values, and judge whether the water demand in the garden greening area is normal according to the demand value status. When the water demand is abnormal, an execution strategy is generated;

[0055] A strategy execution module, which is used to adjust the watering duration of the watering module according to the generated execution strategy;

[0056] The watering module has a preset watering duration and is used to water the vegetation in the garden greening area.

[0057] Through the above technical scheme, this application determines a watering time for the irrigation equipment in the garden greening area based on empirical data and experimental simulation data, collects image information of vegetation in the garden greening area through the image acquisition module, obtains soil moisture information in the garden greening area and weather information before and after watering through the data acquisition module, and uploads it to the analysis and management platform for processing and analysis through the Internet of Things technology, obtains vegetation status values ​​according to image information, obtains soil moisture values ​​according to humidity information, and obtains overall environmental values ​​according to weather information, so as to obtain demand values ​​through comprehensive analysis, and judges whether the water demand in the garden greening area is normal according to the demand value. When the water demand is abnormal, an execution strategy is generated to adjust the watering time in time to ensure that the water demand of the garden greening area just meets its own requirements, thereby ensuring normal growth of vegetation.

[0058] As a preferred solution of the present invention, the method for processing by the analysis management platform is:

[0059] The gardening area is divided into multiple sub-areas according to the area, and a camera, an irrigation device and multiple moisture sensors buried in the soil are installed in each sub-area;

[0060] Analyze and process the images obtained by the camera to obtain the vegetation status value of the sub-area ;

[0061] Analyze and process the humidity information obtained by the temperature sensor to obtain the soil humidity value of the sub-area ;

[0062] Analyze and process the acquired temperature and light information to obtain the overall environmental value of the garden greening area. ;

[0063] By formula Get the demand value of this sub-area ;

[0064] The required value will be obtained The threshold range of standard requirements preset by the system To compare:

[0065] when When , the water demand is considered normal;

[0066] Otherwise, the water demand is considered abnormal and an execution strategy is generated;

[0067] in, as well as is the proportionality coefficient.

[0068] Through the above technical solution, this embodiment provides a method for analyzing and managing the platform to generate water demand and a method for generating an execution strategy. First, the garden greening area is divided into multiple sub-areas according to the area. Each sub-area is equipped with a camera, an irrigation device, and multiple humidity sensors buried in the soil. One irrigation device can just perform full coverage irrigation on the sub-area. The camera is used to obtain image information of the vegetation in the sub-area, so as to analyze and process the image to obtain the vegetation status value of the sub-area. The vegetation status value can show the water shortage state of the vegetation from the appearance of the vegetation. The larger the status value of the vegetation, the more serious its water shortage is. Then, the humidity information obtained by the temperature sensor is analyzed and processed to obtain the soil humidity value of the sub-area. The soil humidity value can obtain the water shortage state of the vegetation soil. The larger the humidity value, the less water shortage the vegetation is. Then, the obtained temperature information and light information are analyzed and processed to obtain the overall environmental value of the garden greening area. The overall environmental value can show the influence of environmental factors on the water demand of vegetation. The larger the overall environmental value, the drier the environment and the greater the water demand of vegetation. Then, through the formula Get the demand value of this sub-area ; From the formula, it can be seen that when the vegetation condition value The larger the overall environment value The larger the soil moisture value The smaller the demand value The larger the value, the more water the vegetation needs, so the required value will be The threshold range of standard requirements preset by the system Compare the system preset standard requirement threshold range Just corresponds to the system preset watering time, when If the water requirement is normal, the current watering time can be maintained; otherwise, it means that the water requirement of the vegetation is abnormal and the watering time needs to be adjusted. Then an execution strategy is generated to automatically adjust the watering time to ensure that the watering amount just meets the water requirement of the vegetation and ensures the normal growth of the vegetation.

[0069] In the above technical solution, the system presets the standard demand threshold interval The preset watering time and proportional coefficient can be obtained based on empirical data and will not be described in detail here.

[0070] As a preferred embodiment of the present invention, the vegetation status value The acquisition method is: collect a large amount of vegetation image data, the image data should include vegetation with different water shortage levels, and use image recognition technology to extract features related to vegetation water shortage conditions from the collected image data;

[0071] According to the degree of vegetation water shortage, multiple vegetation status value labels of different sizes are determined, and a classification model based on deep learning convolutional neural network is trained using the extracted features and the corresponding vegetation status value labels of different sizes;

[0072] Extract features from the vegetation image captured by the camera to obtain the current features, and use the current features as the input of the convolutional neural network classification model to obtain the vegetation status value of the sub-area .

[0073] Through the above technical solution, this embodiment provides a vegetation status value The specific method of obtaining the water requirement of vegetation is as follows: since the water requirement of vegetation can generally be seen from the performance characteristics of vegetation, for example, drooping, dull, and loss of vitality of vegetation leaves may be a manifestation of water shortage, curling of leaf edges or curling of the entire leaf or darkening or lightening of color may also be a sign of water shortage, and for example, premature withering of plant flowers or poor development of fruits may also be a sign of water shortage. Therefore, this embodiment collects a large amount of vegetation image data, and the image data should include vegetation with different degrees of water shortage. Image recognition technology is used to extract features related to the water shortage status of vegetation from the collected image data, and multiple vegetation status value labels of different sizes are determined according to the degree of water shortage of vegetation. The extracted features and the corresponding vegetation status value labels of different sizes are used to train a classification model based on deep learning convolutional neural network, and then the vegetation image acquired by the camera is subjected to feature extraction to obtain the current features, and the obtained current features are used as the input of the convolutional neural network classification model to obtain the vegetation status value of the sub-area. In this way, when the system receives a new vegetation image, it will automatically extract features and input them into the classification model to predict the water shortage status of green plants and obtain the vegetation status value. , which facilitates subsequent analysis.

[0074] As a preferred embodiment of the present invention, the soil moisture value The acquisition method is:

[0075] Get the humidity value obtained by each humidity sensor in the sub-area , so that through the formula Get the average humidity value ,in is the number of humidity sensors, and ;

[0076] Get the humidity value change curve over time between the last watering and the current watering ;

[0077] By formula Get soil moisture value ;

[0078] in, as well as is the proportionality coefficient, The time point after the last watering was completed. The time node for this watering.

[0079] Through the above technical solution, this embodiment provides soil moisture value The specific method of obtaining the moisture content is as follows: since the intuitive expression of whether the vegetation is lacking water is the moisture content, the present embodiment obtains the humidity value obtained by each humidity sensor in the sub-area. Since there is an error in the judgment of a single humidity value, the formula Get the average humidity value , get the humidity value change curve between the last watering and this watering over time , so that through the formula Get soil moisture value ;formula It indicates the change of soil moisture between the last irrigation and the current irrigation. The smaller the value, the greater the change of soil moisture and the more water is needed. The formula It shows the soil moisture at the current watering time. The smaller the value, the more water is needed. Therefore, the formula Based on a comprehensive analysis of historical soil moisture changes combined with current humidity, the soil moisture value is obtained, which can more accurately determine the soil water storage capacity and facilitate subsequent analysis.

[0080] In the above technical solution, the proportionality coefficient as well as Can be obtained based on empirical data.

[0081] As a preferred solution of the present invention, the overall environmental value The acquisition method is:

[0082] Get the average temperature of the landscaping area from the weather bureau between the last watering and the current watering , Maximum temperature And the average light , Highest Illumination At the same time, the average temperature of the landscaping area between this irrigation and the next irrigation is obtained from the Meteorological Bureau. , Maximum temperature And the average light , Highest Illumination ;

[0083] The overall environmental value is obtained by the following formula ;

[0084] ;

[0085] in, as well as , as well as , as well as All are proportional coefficients.

[0086] Through the above technical solution, this embodiment provides the overall environmental value The specific method of obtaining the water consumption is as follows: Generally speaking, when the weather temperature is higher and the light intensity is higher, the water consumption is greater. Therefore, this embodiment obtains the temperature and light intensity of the garden greening area between the last watering and the current watering, and the temperature and light intensity of the garden greening area between the current watering and the next watering from the meteorological bureau, and obtains the temperature and light intensity of the garden greening area between the current watering and the next watering through the formula Get the overall environmental value ,in Indicates the environmental value of the landscaping area between the last watering and the current watering. It indicates the environmental value of the garden greening area between the current watering and the next watering. By combining the average temperature, maximum temperature, average light and maximum light for comprehensive analysis, the overall environmental value of the garden greening area can be accurately obtained. , for subsequent analysis.

[0087] In the above technical solution, the proportionality coefficient as well as , as well as , as well as All can be obtained based on empirical data.

[0088] As a preferred solution of the present invention, the execution strategy includes an increase strategy and a decrease strategy;

[0089] when When , an increase strategy is generated, at this time, the formula Adjust the watering time to ;

[0090] when When , a reduction strategy is generated, at this time, the formula ;

[0091] in, To preset the watering time, is the maximum time allowed for adjustment, is the time conversion factor.

[0092] Through the above technical solution, this embodiment provides a method for the strategy execution module to adjust the irrigation time according to the execution strategy. When the water demand is abnormal, it may be due to excessive or insufficient water demand, so specific analysis is required. , it means that the water demand needs to increase to meet the normal demand of vegetation. Then, through the formula Adjust the watering time to , it can be seen from the formula that when The larger the value is, the greater the demand is, and the more adjustment time is required. Since the watering time cannot be adjusted indefinitely, if it is adjusted too much, it may affect other ecosystems in the area. Therefore, the maximum adjustment time allowed by a system is set. Limit it so that it can be set according to the demand value The watering time is adjusted accordingly to ; Similarly when When , it means that the water demand is small at this time. If the original watering time is used, there will be too much water, which is not conducive to the growth of vegetation. Therefore, it is necessary to reduce the watering time. The specific formula is , it can be seen from the formula that when The larger the value is, the smaller the demand value is, and the more watering time needs to be adjusted to reduce the demand value. The watering time is reduced accordingly. In this way, the watering time can be adjusted accordingly according to the acquired demand value, and the water demand of the vegetation can be accurately controlled to ensure the normal growth of the vegetation.

[0093] In the above technical solution, the maximum time allowed by the system to adjust The watering time can be preset according to the specific conditions of the landscaping area. And the time conversion factor It can be determined based on empirical data and experimental simulation data, which will not be described in detail here.

[0094] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent landscaping management system based on the Internet of Things, characterized in that: The management system comprises: An image acquisition module, the image acquisition module is used to obtain image information in the garden greening area, the image acquisition module includes a plurality of cameras; A data acquisition module, the data acquisition module is used to acquire associated parameter information in the garden greening area, the associated parameter information includes soil moisture information in the garden greening area and weather information before and after watering, the weather information includes temperature information and light information; An analysis and management platform, which is used to process and analyze the acquired image information and associated parameter information to generate a demand value, and to determine whether the water demand in the garden greening area is normal according to the demand value status, and to generate an execution strategy when the water demand is abnormal; A strategy execution module, wherein the strategy execution module is used to adjust the watering duration of the watering module according to the generated execution strategy; A watering module, wherein a preset watering duration is set in the watering module and is used to water the vegetation in the garden greening area; The processing method of the analysis and management platform is as follows: the garden greening area is divided into a plurality of sub-areas according to the area, and a camera, an irrigation device and a plurality of humidity sensors buried in the soil are installed in each sub-area; Analyze and process the images obtained by the camera to obtain the vegetation status value of the sub-area ; Analyze and process the humidity information obtained by the temperature sensor to obtain the soil humidity value of the sub-area ; Analyze and process the acquired temperature and light information to obtain the overall environmental value of the garden greening area. ; By formula Get the demand value of this sub-area ; The required value will be obtained The threshold range of standard requirements preset by the system To compare: when When , the water demand is considered normal; Otherwise, the water demand is considered abnormal and an execution strategy is generated; in, as well as is the proportionality coefficient; The vegetation condition value The acquisition method is: collecting a large amount of vegetation image data, the image data including vegetation with different water shortage levels, and using image recognition technology to extract features related to the water shortage status of the vegetation from the collected image data; According to the degree of vegetation water shortage, multiple vegetation status value labels of different sizes are determined, and a classification model based on deep learning convolutional neural network is trained using the extracted features and the corresponding vegetation status value labels of different sizes; Extract features from the vegetation image captured by the camera to obtain the current features, and use the current features as the input of the convolutional neural network classification model to obtain the vegetation status value of the sub-area ; The soil moisture value The acquisition method is: Get the humidity value obtained by each humidity sensor in the sub-area , so that through the formula Get the average humidity value ,in is the number of humidity sensors, and ; Get the humidity value change curve between the last watering and the current watering over time ; By formula Get soil moisture value ; in, as well as is the proportionality coefficient, The time point after the last watering was completed. The time node for this watering; The overall environmental value The acquisition method is: Get the average temperature of the landscaping area between the last watering and the current watering from the Meteorological Bureau , Maximum temperature And the average light , Highest Illumination At the same time, the average temperature of the landscaping area between this irrigation and the next irrigation is obtained from the Meteorological Bureau. , Maximum temperature And the average light , Highest Illumination ; The overall environmental value is obtained by the following formula ; ； in, as well as , as well as , as well as All are proportionality coefficients; The execution strategy includes an increase strategy and a decrease strategy: When , an increase strategy is generated; when When , a reduction strategy is generated; The strategy execution module adjusts the watering duration by: when generating an increase strategy, the formula Adjust the watering time to ; When generating a reduction strategy, the formula in, To preset the watering time, is the maximum time allowed for adjustment, is the time conversion factor.

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