CN113469068B - Growth monitoring method for large-area planting of camellia oleifera - Google Patents
Growth monitoring method for large-area planting of camellia oleifera Download PDFInfo
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Abstract
The invention discloses a growth monitoring method for planting oil tea in a large area, which is applied to a growth monitoring system for planting the oil tea in the large area, wherein the growth monitoring system comprises an administrator terminal, a data management server, a data acquisition console, a first data acquisition end and a second data acquisition end, the administrator terminal, the data management server and the data acquisition console are sequentially connected, the first data acquisition end and the second data acquisition end are both connected with the data acquisition console, the first data acquisition end is connected with a plurality of first cameras, and the second data acquisition end is connected with a plurality of second cameras; the invention also discloses a specific process of the method for monitoring the growth of the large-area planted oil tea. The method can realize monitoring of the growth vigor of the oil-tea trees planted in large areas, is low in cost and more accurate in monitoring, realizes grouping collection, and enables growth monitoring to be more scientific and effective.
Description
Technical Field
The invention belongs to the technical field of automatic monitoring of plant growth vigor, and particularly relates to a growth vigor monitoring method for large-area planting of oil tea.
Background
The camellia oleifera is one of the main woody oil plants in the world, grows in mountains and hilly lands in subtropical regions in south China, is a pure natural high-grade oil plant specific to China, and is widely distributed in Zhejiang, jiangxi, henan, hunan, guangxi and other provinces in China.
As the camellia oleifera grows in mountains and hilly lands, the management difficulty is high when the camellia oleifera is planted in a large area, and the growth of the camellia oleifera is monitored manually, so that a large amount of manpower is consumed inevitably. Among the prior art, there is the intelligent system who monitors plant growth, but when using the long trend control of planting tea-oil camellia in large tracts of land, still there are a great deal of problems: firstly, when image acquisition data is used, the acquisition range of image acquisition equipment is limited, and for large-area planted oil-tea trees, a large amount of image acquisition equipment is needed, so that the cost is high; secondly, the growth vigor of the camellia oleifera trees is different due to the difference of weather conditions or management in the current year, and the difference of specific conditions is not considered when the growth vigor of the camellia oleifera trees is judged, so that the judgment result is not accurate enough; thirdly, for monitoring large-area planting, in scientific research, different areas cannot be independently monitored, specific research requirements such as comparison tests cannot be met, and data cannot be collected in groups; fourth, the prior art cannot realize the comprehensive consideration of the horizontal comparison of the regions and the vertical comparison of different time periods, and the accuracy of the long-term judgment is low, and most of the long-term judgment still needs to be carried out manually.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a growth monitoring method for planting the camellia oleifera in a large area.
The invention provides a growth monitoring method for planting tea-oil trees in a large area, which is applied to a growth monitoring system for planting the tea-oil trees in the large area, wherein the growth monitoring system comprises an administrator terminal, a data management server, a data acquisition console, a first data acquisition end and a second data acquisition end, the administrator terminal, the data management server and the data acquisition console are sequentially connected, the first data acquisition end and the second data acquisition end are both connected with the data acquisition console, the first data acquisition end is connected with a plurality of first cameras, and the second data acquisition end is connected with a plurality of second cameras;
the method for monitoring the growth of the large-area planted oil tea comprises the following steps:
step 1: dividing large-area planted oil tea into a plurality of areas ZkThe method comprises the following steps of calculating the area size of each area, wherein k is the number of the areas, each area is provided with a plurality of tea-oil trees, each area is provided with a first camera and at least one second camera, and the area size of each area is set to be the area of the tea-oil trees which can be monitored by the first camera;
step 2: storing camellia oleifera growth trend images in different growth periods in the past year in a data management server, wherein the camellia oleifera growth trend images are image information of conventional growth trends acquired in corresponding growth periods;
and step 3: a first data acquisition end acquires first image information acquired by a plurality of first cameras and sends the first image information to a data management server through a data acquisition console;
and 4, step 4: the data management server carries out data analysis on first image information acquired by the first camera, wherein the data analysis comprises space anomaly analysis and time anomaly analysis;
in the spatial anomaly analysis, images of different areas are compared to find out an abnormal area;
in the time anomaly analysis, a time translation constant MOV is calculated according to planting data information of the current year, and then first image information acquired at the current time in each area is compared with a corresponding growth period camellia oleifera growth image obtained by adding the time translation constant MOV to the current time in the data management server, so that an abnormal area is found out;
the time translation constant MOV is a parameter adjustment amount which is carried out by a manager according to the current annual weather condition and management information;
and 5: if the space anomaly analysis result is abnormal, a second camera in an abnormal area carries out image acquisition, and a second data acquisition end acquires second image information acquired by the second camera and sends the second image information to a data management server through a data acquisition console; the second image information is a plurality of images; the data management server specifically positions and analyzes the abnormal growth condition according to a plurality of images in the second image information;
if the time anomaly analysis result is abnormal, the second camera is used for collecting second image information in any area, and the second image information and the anomaly result are sent to the data management server through the data collection console;
if no growth abnormality is found in the spatial abnormality analysis and the time abnormality analysis, the second camera is not started to collect images, the abnormality analysis count value ABN is increased by one, and if the growth abnormality is found in the spatial abnormality analysis or the time abnormality analysis, the abnormality analysis count value ABN is reset;
step 6: if the abnormal analysis count value ABN>KABNIf so, starting a second camera to collect images at any position, and sending the images to a data management server; wherein, KABNSetting the time interval of image acquisition when the growth condition is normal;
and 7: and the data management server generates a camellia oleifera growth analysis report according to the first image information, the second image information and the abnormal analysis result, and sends the camellia oleifera growth analysis report to the administrator terminal.
Preferably, the data management server comprises a data analysis module, a communication module and a database, wherein the database is used for storing the first image information, the second image information, the growth images of the tea-oil trees in different growth periods in the past year and analysis results.
Preferably, the data management server further comprises a human-computer interaction module, and a user can query and count data in the data management server.
Preferably, the first camera is a wide-angle camera, and the second camera is a telephoto camera.
Preferably, the first camera is at least 3.2 meters from the ground.
Preferably, the range of the first camera for collecting the camellia oleifera trees is larger than that of the second camera, and the definition of the collected images of the second camera is larger than that of the first camera.
Compared with the prior art, the method can monitor the growth vigor of the oil-tea trees planted in a large area, and the system cost is low; the growth vigor of the camellia oleifera trees is comprehensively judged according to the current annual weather condition and the difference of management, and the judgment result is more accurate; by monitoring the large-area planted oil tea in different areas, specific research requirements such as comparison tests in scientific research and the like can be realized, and data can be collected in groups; through the comprehensive consideration of transverse comparison of the planting area and longitudinal comparison of different time periods, the growth judgment accuracy is improved, and the growth monitoring is more scientific and effective.
Drawings
Fig. 1 is a schematic structural diagram of a growth monitoring system for planting large-area camellia oleifera.
Detailed Description
The invention is further illustrated by the following figures and examples.
The first embodiment is as follows:
as shown in fig. 1, the invention provides a growth monitoring method for planting camellia oleifera in a large area, which is applied to a growth monitoring system for planting camellia oleifera in a large area, wherein the growth monitoring system comprises an administrator terminal, a data management server, a data acquisition console, a first data acquisition end and a second data acquisition end, the administrator terminal, the data management server and the data acquisition console are sequentially connected, the first data acquisition end and the second data acquisition end are both connected with the data acquisition console, the first data acquisition end is connected with a plurality of first cameras, and the second data acquisition end is connected with a plurality of second cameras;
the method for monitoring the growth of the large-area planted oil tea comprises the following steps:
step 1: dividing large-area planted oil tea into a plurality of areas ZkThe method comprises the following steps that k is the number of regions, each region is provided with a plurality of oil-tea trees, each region is provided with a first camera and at least one second camera, and the area size of each region is set to be the area of the oil-tea trees which can be monitored by the first camera;
step 2: storing camellia oleifera growth trend images in different growth periods in the past year in a data management server, wherein the camellia oleifera growth trend images are image information of conventional growth trends acquired in corresponding growth periods;
and 3, step 3: a first data acquisition end acquires first image information acquired by a plurality of first cameras and sends the first image information to a data management server through a data acquisition console;
and 4, step 4: the data management server performs data analysis on first image information acquired by the first camera, wherein the data analysis comprises space anomaly analysis and time anomaly analysis;
in the spatial anomaly analysis, images in different areas are compared to find out an abnormal area;
for the spatial anomaly analysis, the method specifically comprises the following steps: by comparing the growth image information of different areas, if the difference degree of the images among the different areas exceeds a set threshold value, the growth abnormity is considered to occur. The different regions are adjacent different regions (gradual anomalies) or non-adjacent different regions (jump anomalies).
And for the gradual change type abnormity, further acquiring growth data, environment data and other information of more adjacent regions according to user setting. For a jump-type anomaly, only the data information of the region contrasting the anomaly may be saved.
In the time anomaly analysis, a time translation constant MOV is calculated according to planting data information of the current year, and then first image information acquired at the current time in each area is compared with a corresponding growth period camellia oleifera growth image obtained by adding the time translation constant MOV to the current time in the data management server, so that an abnormal area is found out;
the time translation constant MOV is a parameter adjustment amount which is carried out by a manager according to the current annual weather condition and management information;
and 5: if the space anomaly analysis result is abnormal, a second camera in an abnormal area carries out image acquisition, and a second data acquisition end acquires second image information acquired by the second camera and sends the second image information to a data management server through a data acquisition console; the second image information is a plurality of images; the data management server specifically positions and analyzes the abnormal growth condition according to a plurality of images in the second image information;
if the time anomaly analysis result is abnormal, the second camera is used for collecting second image information in any area, and the second image information and the anomaly result are sent to the data management server through the data collection console;
if no growth abnormality is found in the spatial abnormality analysis and the time abnormality analysis, the second camera is not started to collect images, the abnormality analysis count value ABN is increased by one, and if the growth abnormality is found in the spatial abnormality analysis or the time abnormality analysis, the abnormality analysis count value ABN is reset;
step 6: if the abnormal analysis count value ABN>KABNIf so, starting a second camera to collect images at any position, and sending the images to a data management server; wherein, KABNSetting the time interval of image acquisition when the growth condition is normal;
and 7: and the data management server generates a camellia oleifera growth analysis report according to the first image information, the second image information and the abnormal analysis result, and sends the camellia oleifera growth analysis report to the administrator terminal.
The data management server comprises a data analysis module, a communication module and a database, wherein the database is used for storing first image information, second image information, camellia oleifera growth images in different growth periods in the past year and analysis results.
The data management server also comprises a man-machine interaction module, and a user can inquire and count data in the data management server.
The first camera is a wide-angle camera, and the second camera is a long-focus camera.
The first camera is at least 3.2 meters away from the ground.
The range of the first camera for collecting the oil-tea trees is larger than that of the second camera, and the definition of the collected images of the second camera is larger than that of the first camera.
The above description is only exemplary of the present invention and should not be taken as limiting, and any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. The growth monitoring method for the large-area planting of the oil tea is characterized by being applied to a growth monitoring system for the large-area planting of the oil tea, wherein the growth monitoring system comprises an administrator terminal, a data management server, a data acquisition control console, a first data acquisition end and a second data acquisition end, the administrator terminal, the data management server and the data acquisition control console are sequentially connected, the first data acquisition end and the second data acquisition end are both connected with the data acquisition control console, the first data acquisition end is connected with a plurality of first cameras, and the second data acquisition end is connected with a plurality of second cameras;
the method for monitoring the growth of the large-area planted oil tea comprises the following steps:
step 1: dividing large-area planted oil tea into a plurality of areas ZkWherein k is the number of regions, each region is provided with a plurality of oil-tea trees, each region is provided with a first camera and at least one second camera, and the area size of each region is setSetting the area of the camellia oleifera trees which can be monitored by the first camera;
step 2: storing camellia oleifera growth trend images in different growth periods in the past year in a data management server, wherein the camellia oleifera growth trend images are image information of conventional growth trends acquired in corresponding growth periods;
and 3, step 3: a first data acquisition end acquires first image information acquired by a plurality of first cameras and sends the first image information to a data management server through a data acquisition console;
and 4, step 4: the data management server performs data analysis on first image information acquired by the first camera, wherein the data analysis comprises space anomaly analysis and time anomaly analysis;
in the spatial anomaly analysis, images of different areas are compared to find out an abnormal area;
in the time anomaly analysis, a time translation constant MOV is calculated according to planting data information of the current year, and then first image information acquired at the current time in each area is compared with a corresponding growth period camellia oleifera growth image obtained by adding the time translation constant MOV to the current time in the data management server, so that an abnormal area is found out;
the time translation constant MOV is a parameter adjustment amount which is carried out by a manager according to the current annual weather condition and management information;
and 5: if the space abnormity analysis result is abnormal, a second camera in the abnormal area carries out image acquisition, and a second data acquisition end acquires second image information acquired by the second camera and sends the second image information to a data management server through a data acquisition console; the second image information is a plurality of images; the data management server specifically positions and analyzes the abnormal growth condition according to a plurality of images in the second image information;
if the time anomaly analysis result is abnormal, the second camera is used for collecting second image information in any area, and the second image information and the anomaly result are sent to the data management server through the data collection console;
if no growth abnormality is found in the spatial abnormality analysis and the time abnormality analysis, the second camera is not started to collect images, the abnormality analysis count value ABN is increased by one, and if the growth abnormality is found in the spatial abnormality analysis or the time abnormality analysis, the abnormality analysis count value ABN is reset;
step 6: if the abnormal analysis count value ABN>KABNIf the first camera is started, the second camera is started to collect images at any position, and the images are sent to a data management server; wherein, KABNSetting the time interval of image acquisition when the growth is normal;
and 7: and the data management server generates a camellia oleifera growth analysis report according to the first image information, the second image information and the abnormal analysis result, and sends the camellia oleifera growth analysis report to the administrator terminal.
2. The method for monitoring the growth of the large-area planted camellia oleifera according to claim 1, wherein the data management server comprises a data analysis module, a communication module and a database, and the database is used for storing the first image information, the second image information, the camellia oleifera growth images in different growth periods in the past year and analysis results.
3. The growth monitoring method for the camellia oleifera planted in a large area according to claim 2, wherein the data management server further comprises a human-computer interaction module, and a user can inquire and count data in the data management server.
4. The method for monitoring the growth of the large-area planted camellia oleifera according to claim 1, wherein the first camera is a wide-angle camera, and the second camera is a long-focus camera.
5. The growth monitoring method for the large-area planted camellia oleifera according to claim 4, wherein the distance between the first camera and the ground is at least 3.2 meters.
6. The method for monitoring the growth of the large-area planted camellia oleifera according to claim 4, wherein the range of the first camera for collecting the camellia oleifera is larger than that of the second camera, and the definition of the collected image of the second camera is larger than that of the first camera.
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