Plant maintenance and growth monitoring method for landscaping engineering

Abstract

A plant maintenance and growth monitoring method for landscaping engineering comprises the following steps: by deploying a sensor for detecting growth conditions around garden plants and an image acquisition device, establishing corresponding growth information bases for the garden plants one by one according to growth data detected by the sensor and acquired image data; the growth condition of the garden plant is clearly known through the data content in the growth information base; the data collected in real time is processed by the data processing center and then stored in the growth information base, and the growth evaluation condition of the plant is analyzed through the data, so that a one-to-one adaptive maintenance decision is made, maintenance measures are continuously optimized through feedback in the maintenance process, and the maintenance efficiency is improved. According to the invention, the problems of low plant growth monitoring efficiency, poor accuracy, lack of comprehensive analysis and the like in the prior art are solved, efficient, accurate and comprehensive monitoring of the plant growth state in the landscaping engineering is realized, and a one-to-one maintenance decision is provided for plant maintenance.

Description

Technical Field

[0001] This invention relates to the field of plant maintenance technology in landscaping projects, and in particular to a method for monitoring plant growth in landscaping projects. Background Technology

[0002] In landscaping projects, the growth status of plants directly affects the effect of the landscape and its ecological benefits. Timely and accurate monitoring of plant growth is crucial for taking appropriate maintenance measures to ensure healthy plant growth.

[0003] Currently, traditional plant growth monitoring methods mainly rely on manual inspections. Workers visually observe the plant's appearance, such as leaf color and signs of pests and diseases, and use simple tools to measure indicators like height and crown width. This method has several drawbacks: First, manual inspections are inefficient, making it difficult to conduct timely and comprehensive monitoring of large-scale landscaping areas. Second, monitoring results are significantly affected by human factors; different workers may have different judgment standards, leading to insufficient accuracy and reliability of the monitoring data. Furthermore, manual inspections cannot achieve real-time, continuous monitoring of plant growth, making it difficult to capture subtle changes during the growth process and hindering the timely detection of potential growth problems and the implementation of effective maintenance measures.

[0004] With the development of technology, although some monitoring methods based on sensor technology have emerged, existing technologies often only monitor a single indicator of plant growth, lacking comprehensive integration and analysis of plant growth information, and thus failing to provide a scientific and comprehensive basis for plant care decisions. Therefore, there is an urgent need for a more efficient, accurate, and comprehensive method for monitoring plant growth. Summary of the Invention

[0005] In view of the above-mentioned technical problems, the present invention provides a plant maintenance and growth monitoring method for landscaping projects, which solves the problems of low efficiency, poor accuracy and lack of comprehensive analysis in the existing technology of plant growth monitoring, and realizes efficient, accurate and comprehensive monitoring of plant growth status in landscaping projects, providing one-to-one maintenance decision-making for plant maintenance.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] A method for monitoring plant growth and maintenance in landscaping projects, comprising the following steps:

[0008] Step 1: Deploy sensors and image acquisition devices around the garden plants to detect their growth. Use the growth data detected by the sensors and the image data collected to establish a corresponding growth information database for each garden plant. The growth status of the garden plants can be clearly understood through the data in the growth information database.

[0009] Step 2: The data and image data collected by each sensor in Step 1 are transmitted to the data processing center. During the transmission process, encryption algorithms are used to encrypt the data to ensure its security and integrity.

[0010] Step 3: After passing through the data processing center, the data is stored in the growth information database of each garden plant, and the plant growth status is assessed through data analysis.

[0011] Step 4: Based on the plant growth status assessment results obtained in Step 3, and in combination with the plant species and growth stage, formulate corresponding maintenance decisions.

[0012] Step 5: After the maintenance personnel implement the maintenance decisions in Step 4, the data collected from the growth information database is used to record the implementation feedback of plant maintenance measures, thereby comparing the changes in plant growth status before and after maintenance and analyzing the effectiveness of the maintenance decisions.

[0013] Furthermore, the sensors in step 1 include a soil moisture sensor, a soil nutrient sensor, a light intensity sensor, an air temperature and humidity sensor, a carbon dioxide concentration sensor, and a plant stem flow sensor. The soil moisture sensor and soil nutrient sensor are buried in the soil near the plant roots to monitor soil moisture and nutrient content in real time. The light intensity sensor, air temperature and humidity sensor, and carbon dioxide concentration sensor are mounted on fixed supports at a height of 1.5–2 meters above the ground to acquire data on light, temperature, humidity, and carbon dioxide concentration in the plant's growth environment. The plant stem flow sensor is installed on the plant stem to monitor water transport within the plant.

[0014] Furthermore, the image acquisition device in step 1 includes a wide-angle camera for comprehensively capturing the overall shape of the plant and a macro dual-mode camera for periodically capturing the front and back of the plant leaves, thereby obtaining the plant's growth morphology and capturing the condition of the plant leaves to detect whether the plant has pests or diseases as early as possible.

[0015] Furthermore, in step 2, after the data processing center receives the data transmitted from the sensor and the image acquisition device, it performs noise reduction processing on the numerical data acquired by the sensor, using a median filtering algorithm to remove outliers and noise from the data; and it performs image enhancement processing on the image data, using a histogram equalization algorithm to improve the contrast of the image so as to more clearly observe the morphological characteristics of the plant.

[0016] Furthermore, the data processing center performs time synchronization processing on all data during processing to ensure consistency of different types of data in the time dimension.

[0017] Furthermore, the specific content of the plant growth status assessment in step 3 is as follows:

[0018] The assessment based on sensor data is as follows: Soil moisture is analyzed based on data monitored by soil moisture sensors and compared with the standard value required by the plant. If the moisture is too high or too low, a risk score is assigned based on the proportion exceeding the standard value. Soil nutrient content is monitored based on soil nutrient sensors, and a corresponding risk score is assigned based on the type and degree of nutrient deficiency. Combined with data from plant stem flow sensors, the plant's water absorption and transport are analyzed. If the stem flow rate is abnormally reduced, it indicates that the plant may have water stress or physiological problems, and the corresponding risk score is increased. Finally, the risk scores of each sensor data are weighted and summed to obtain a plant growth environment risk score based on sensor data.

[0019] Image-based assessment: This involves extracting leaf quantity, leaf area, leaf color characteristics, branch morphology, and visible lesions on the leaf surface from image data. The extracted morphological parameters are compared with preset ranges of normal growth morphological parameters to calculate the degree of deviation for each parameter and assign corresponding morphological scores. For example, if the leaf color deviates from the normal green range, a certain number of points are deducted based on the degree of deviation; similarly, significant differences in leaf area or quantity compared to normal growth conditions also result in point deductions; and significant differences in the area of ​​lesions shown in leaf imaging also result in point deductions. Finally, all morphological scores are summarized to obtain a plant morphological score based on image data.

[0020] Comprehensive assessment: The plant growth environment risk score based on sensor data and the plant morphology score based on image data are weighted and calculated with the growth environment risk score accounting for 60% and the morphology score accounting for 40% respectively, to obtain a comprehensive assessment score of plant growth status.

[0021] Furthermore, in step 4, when making corresponding maintenance decisions, the factors leading to poor plant growth should be analyzed based on the plant growth status assessment score, combined with monitoring data and image data from the growth information database. For example, humidity and temperature should be used to formulate plant irrigation plans, nutrient issues should be used to formulate fertilization schemes, and pest and disease control measures should be implemented based on leaf morphology and lesion conditions.

[0022] The beneficial effects of this invention are:

[0023] This invention records the growth process of garden plants by establishing a one-to-one growth information database and deploying various types of monitoring sensors and image acquisition devices around the plants. This enables real-time monitoring of the plant growth environment and comprehensive monitoring of plant growth morphology and the presence of pests and diseases. The collected data is processed and stored in the plant growth information database for recording. Compared with traditional manual inspection and single-indicator monitoring methods, this invention can obtain richer and more accurate plant growth information.

[0024] This invention scientifically evaluates and comprehensively analyzes the collected data to accurately assess the plant's growth status, reduce human interference, and improve the reliability and accuracy of monitoring results. Furthermore, it formulates corresponding maintenance decisions based on the plant assessment structure, implementing one-to-one maintenance, and recording maintenance data in real time. Feedback is obtained through data comparison, and maintenance measures are optimized based on the feedback results. This achieves intelligent and scientific management of plant maintenance, improves the efficiency and quality of garden maintenance work, reduces maintenance costs, and helps ensure the healthy growth of plants in garden greening projects, enhancing the garden landscape effect and ecological benefits. Detailed Implementation

[0025] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1

[0027] A method for monitoring plant growth and maintenance in landscaping projects, comprising the following steps:

[0028] Step 1: Deploy sensors and image acquisition devices around the garden plants to detect their growth. Use the growth data detected by the sensors and the image data collected to establish a corresponding growth information database for each garden plant. The growth status of the garden plants can be clearly understood through the data in the growth information database.

[0029] Step 2: The data and image data collected by each sensor in Step 1 are transmitted to the data processing center. During the transmission process, encryption algorithms are used to encrypt the data to ensure its security and integrity.

[0030] Step 3: After passing through the data processing center, the data is stored in the growth information database of each garden plant, and the plant growth status is assessed through data analysis.

[0031] Step 4: Based on the plant growth status assessment results obtained in Step 3, and in combination with the plant species and growth stage, formulate corresponding maintenance decisions.

[0032] Step 5: After the maintenance personnel implement the maintenance decisions in Step 4, the data collected from the growth information database is used to record the implementation feedback of plant maintenance measures, thereby comparing the changes in plant growth status before and after maintenance and analyzing the effectiveness of the maintenance decisions.

[0033] Furthermore, the sensors in step 1 include a soil moisture sensor, a soil nutrient sensor, a light intensity sensor, an air temperature and humidity sensor, a carbon dioxide concentration sensor, and a plant stem flow sensor. The soil moisture sensor and soil nutrient sensor are buried in the soil near the plant roots to monitor soil moisture and nutrient content in real time. The light intensity sensor, air temperature and humidity sensor, and carbon dioxide concentration sensor are mounted on fixed supports at a height of 1.5–2 meters above the ground to acquire data on light, temperature, humidity, and carbon dioxide concentration in the plant's growth environment. The plant stem flow sensor is installed on the plant stem to monitor water transport within the plant.

[0034] Furthermore, the image acquisition device in step 1 includes a wide-angle camera for comprehensively capturing the overall shape of the plant and a macro dual-mode camera for periodically capturing the front and back of the plant leaves, thereby obtaining the plant's growth morphology and capturing the condition of the plant leaves to detect whether the plant has pests or diseases as early as possible.

[0035] Furthermore, in step 2, after the data processing center receives the data transmitted from the sensor and the image acquisition device, it performs noise reduction processing on the numerical data acquired by the sensor, using a median filtering algorithm to remove outliers and noise from the data; and it performs image enhancement processing on the image data, using a histogram equalization algorithm to improve the contrast of the image so as to more clearly observe the morphological characteristics of the plant.

[0036] Furthermore, the data processing center performs time synchronization processing on all data during processing to ensure consistency of different types of data in the time dimension.

[0037] Furthermore, the specific content of the plant growth status assessment in step 3 is as follows:

[0038] The assessment based on sensor data is as follows: Soil moisture is analyzed based on data monitored by soil moisture sensors and compared with the standard value required by the plant. If the moisture is too high or too low, a risk score is assigned based on the proportion exceeding the standard value. Soil nutrient content is monitored based on soil nutrient sensors, and a corresponding risk score is assigned based on the type and degree of nutrient deficiency. Combined with data from plant stem flow sensors, the plant's water absorption and transport are analyzed. If the stem flow rate is abnormally reduced, it indicates that the plant may have water stress or physiological problems, and the corresponding risk score is increased. Finally, the risk scores of each sensor data are weighted and summed to obtain a plant growth environment risk score based on sensor data.

[0039] Image-based assessment: This involves extracting leaf quantity, leaf area, leaf color characteristics, branch morphology, and visible lesions on the leaf surface from image data. The extracted morphological parameters are compared with preset ranges of normal growth morphological parameters to calculate the degree of deviation for each parameter and assign corresponding morphological scores. For example, if the leaf color deviates from the normal green range, a certain number of points are deducted based on the degree of deviation; similarly, significant differences in leaf area or quantity compared to normal growth conditions also result in point deductions; and significant differences in the area of ​​lesions shown in leaf imaging also result in point deductions. Finally, all morphological scores are summarized to obtain a plant morphological score based on image data.

[0040] Comprehensive assessment: The plant growth environment risk score based on sensor data and the plant morphology score based on image data are weighted and calculated with the growth environment risk score accounting for 60% and the morphology score accounting for 40% respectively, to obtain a comprehensive assessment score of plant growth status.

[0041] Furthermore, in step 4, when making corresponding maintenance decisions, the factors leading to poor plant growth should be analyzed based on the plant growth status assessment score, combined with monitoring data and image data from the growth information database. For example, humidity and temperature should be used to formulate plant irrigation plans, nutrient issues should be used to formulate fertilization schemes, and pest and disease control measures should be implemented based on leaf morphology and lesion conditions.

[0042] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring plant growth and maintenance in landscaping projects, comprising the following steps: Step 1: Deploy sensors and image acquisition devices around the garden plants to detect their growth. Use the growth data detected by the sensors and the image data collected to establish a corresponding growth information database for each garden plant. The growth status of the garden plants can be clearly understood through the data in the growth information database. Step 2: The data and image data collected by each sensor in Step 1 are transmitted to the data processing center. During the transmission process, encryption algorithms are used to encrypt the data to ensure its security and integrity. Step 3: After passing through the data processing center, the data is stored in the growth information database of each garden plant, and the plant growth status is assessed through data analysis. Step 4: Based on the plant growth status assessment results obtained in Step 3, and in combination with the plant species and growth stage, formulate corresponding maintenance decisions. Step 5: After the maintenance personnel implement the maintenance decisions in Step 4, the data collected from the growth information database is used to record the implementation feedback of plant maintenance measures, thereby comparing the changes in plant growth status before and after maintenance and analyzing the effectiveness of the maintenance decisions.

2. The method for monitoring plant maintenance and growth in landscaping projects according to claim 1, characterized in that... The sensors in step 1 include a soil moisture sensor, a soil nutrient sensor, a light intensity sensor, an air temperature and humidity sensor, a carbon dioxide concentration sensor, and a plant stem flow sensor. The soil moisture sensor and the soil nutrient sensor are buried in the soil near the plant roots to monitor the soil moisture and nutrient content in real time. The light intensity sensor, the air temperature and humidity sensor, and the carbon dioxide concentration sensor are installed on fixed supports at a height of 1.5 to 2 meters above the ground to obtain data on light, temperature, humidity, and carbon dioxide concentration in the plant's growth environment. The plant stem flow sensor is installed on the plant stem to monitor the plant's water transport.

3. The method for monitoring plant maintenance and growth in landscaping projects according to claim 1, characterized in that... The image acquisition device in step 1 includes a high-angle camera for capturing the overall shape of the plant and a macro dual-mode camera for periodically capturing the front and back of the plant leaves, thereby obtaining the plant's growth pattern and capturing the condition of the plant leaves to detect whether the plant has pests or diseases as early as possible.

4. The method for monitoring plant maintenance and growth in landscaping projects according to claim 1, characterized in that... In step 2, after the data processing center receives the data transmitted from the sensor and the image acquisition device, it performs noise reduction processing on the numerical data acquired by the sensor, using a median filtering algorithm to remove outliers and noise from the data; and it performs image enhancement processing on the image data, using a histogram equalization algorithm to improve the contrast of the image so as to more clearly observe the morphological characteristics of the plant.

5. A method for monitoring plant growth and maintenance in landscaping projects according to claim 4, characterized in that... The data processing center performs time synchronization processing on all data during processing to ensure consistency of different types of data in the time dimension.

6. A method for monitoring plant growth and maintenance in landscaping projects according to claim 1, characterized in that... The specific content of the plant growth status assessment in step 3 is as follows: Sensor-based assessment: Soil moisture is analyzed based on data monitored by soil moisture sensors and compared with the standard value required by the plant. If the moisture is too high or too low, a risk score is given according to the proportion of the value exceeding the standard. Soil nutrient content is monitored using soil nutrient sensors, and risk scores are assigned based on the type and degree of nutrient deficiency. Combined with plant stem flow sensor data, the water absorption and transport of plants are analyzed. If the stem flow rate is abnormally reduced, it indicates that the plant may have water stress or physiological problems, and the corresponding risk score is increased. Finally, the risk scores of each sensor data are weighted and summed to obtain a plant growth environment risk score based on sensor data. Image-based assessment: This involves extracting leaf quantity, leaf area, leaf color characteristics, branch morphology, and visible lesions on the leaf surface from image data. The extracted morphological parameters are compared with preset ranges of normal growth morphological parameters to calculate the degree of deviation for each parameter and assign corresponding morphological scores. For example, if the leaf color deviates from the normal green range, a certain number of points are deducted based on the degree of deviation; similarly, significant differences in leaf area or quantity compared to normal growth conditions also result in point deductions; and significant differences in the area of ​​lesions shown in leaf imaging also result in point deductions. Finally, all morphological scores are summarized to obtain a plant morphological score based on image data. Comprehensive assessment: The plant growth environment risk score based on sensor data and the plant morphology score based on image data are weighted and calculated with the growth environment risk score accounting for 60% and the morphology score accounting for 40% respectively, to obtain a comprehensive assessment score of plant growth status.

7. A method for monitoring plant maintenance and growth in landscaping projects according to claim 1, characterized in that... In step 4, when making corresponding maintenance decisions, the factors leading to poor plant growth status should be analyzed based on the plant growth status assessment score, combined with monitoring data and image data in the growth information database.