CN117876906A - Intelligent agricultural information management platform based on cloud computing - Google Patents
Intelligent agricultural information management platform based on cloud computing Download PDFInfo
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- CN117876906A CN117876906A CN202410086288.2A CN202410086288A CN117876906A CN 117876906 A CN117876906 A CN 117876906A CN 202410086288 A CN202410086288 A CN 202410086288A CN 117876906 A CN117876906 A CN 117876906A
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- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 2
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Abstract
The invention discloses a cloud computing-based intelligent agricultural information management platform, which belongs to the technical field of intelligent agriculture, wherein the intelligent agricultural information management platform firstly collects image information in a farmland through an unmanned aerial vehicle flying at high altitude, divides the farmland area into a plurality of divided areas, judges the position of an area possibly having abnormality according to the image chromatic aberration among the divided areas, realizes the rapid locking of an abnormal land block in a large-area farmland, and then further utilizes the unmanned aerial vehicle flying at low altitude, a wheeled robot and the like to carry a second high-definition camera to acquire a close-range clear image, thereby facilitating the accurate judgment of the problem in the abnormal land block by staff; compared with a manual inspection mode, the invention can reduce the labor cost, remarkably improve the inspection efficiency and accuracy, timely find out the land with abnormality, and pertinently process the problem, thereby being beneficial to the expansion of the inhibition loss.
Description
Technical Field
The invention belongs to the technical field of intelligent agriculture, and particularly relates to an intelligent agriculture information management platform based on cloud computing.
Background
The agricultural system is a multi-level large-scale production system, and the rapid development of the Internet of things technology also provides assistance for the development of modern intelligent agriculture, so that the large-scale agricultural production is facilitated, the planting cost is reduced, the planting efficiency is improved, and the agricultural system is a development trend in the current stage of agriculture.
In a large-scale farm, the condition of crops in the farmland is difficult to monitor by manpower due to large area, so that when local insect damage occurs or crops in local areas are abnormal in growth due to topography, water and soil and the like, management staff cannot discover timely, the abnormal risks such as insect damage are diffused, the problem of loss is further expanded, and in order to discover the abnormality in the farmland timely, the efficiency of farmland monitoring is improved, and the cost of farmland monitoring is reduced.
Disclosure of Invention
The invention aims to provide an intelligent agricultural information management platform based on cloud computing, which solves the problems of high monitoring cost and low efficiency of farmland crops in the prior art.
The aim of the invention can be achieved by the following technical scheme:
intelligent agriculture information management platform based on cloud calculates includes:
the first high-definition camera is used for collecting image information of farmlands and is carried by the high-altitude unmanned aerial vehicle;
the locator is arranged on the high-altitude unmanned aerial vehicle and the accurate acquisition equipment and is used for acquiring the position information of the high-altitude unmanned aerial vehicle and the accurate acquisition equipment;
the information transmission module is used for establishing communication connection among the first high-definition camera, the locator, the information processor and the memory;
the memory is used for storing information acquired by the first high-definition camera and the positioner;
the accurate acquisition equipment is provided with a second high-definition camera and is used for acquiring image information of a specific farmland position;
the information processor is used for identifying the abnormal land parcels in the monitored farmland, sending instructions to the accurate acquisition equipment according to the positions of the abnormal land parcels, and further acquiring image information of the abnormal land parcels.
Further, the method for identifying the abnormal land block by the information processor comprises the following steps:
s1, carrying a first high-definition camera by a high-altitude unmanned aerial vehicle to fly above a farmland, acquiring high-definition image information of the farmland through the first high-definition camera, and transmitting the acquired high-definition image information of the farmland to a memory and an information processor through an information transmission module;
s2, acquiring position information of an abnormal land block in a farmland, and specifically:
s21, uniformly dividing a piece of high-definition image information into a plurality of rectangular dividing areas, and positioning each dividing area;
s22, acquiring a plurality of segmentation areas corresponding to farmlands;
s23, classifying each segmented region, wherein the similarity between any two segmented regions in the same class is not smaller than a preset proportionality coefficient;
s24, marking the segmented regions with the largest quantity as standard regions, and marking the segmented regions of other classes as abnormal regions;
when the area proportion of the abnormal areas contained in the same continuous graph is not smaller than the preset proportion alpha, the farmland position covered by the corresponding continuous graph is considered to be an abnormal land block;
s3, the information processor gives an instruction, the accurate acquisition equipment enters the range of the abnormal land block, and the image information of the abnormal land block is acquired through the second high-definition camera;
and S4, the information processor sends the image information acquired by the second high-definition camera to terminal equipment of a corresponding worker.
Further, any rectangular area with the area being a preset value is taken in the abnormal land, and the area ratio occupied by the abnormal area in the rectangular area is not smaller than the preset ratio alpha 1, and alpha 1 is smaller than alpha.
Further, in step S21, when the segmented region is acquired, the image within the preset range of the edge of the high-definition image information is first cut off, and the segmented region is acquired with the remaining image portion.
Further, the intelligent agricultural information management platform also comprises a modeling module;
the modeling module is used for establishing a model of the monitored farmland, marking the position of the abnormal land in the model of the monitored farmland after determining the abnormal land, and checking the marked model by a staff through the terminal equipment.
Further, in step S3, when image information is collected by the second high-definition camera in an abnormal plot, a plurality of sample collection points are uniformly taken in the corresponding abnormal plot, and the second high-definition camera collects the image information when reaching the sample collection points.
Further, the intelligent agricultural information management platform also comprises a sensor module, wherein the sensor module is used for detecting soil related parameters of each place of a farmland;
when the sensor module is set, the sensor installation density of the abnormal land is greater than that of the standard area.
Further, a plurality of segmentation areas are randomly selected from the abnormal land, the similarity beta between the segmentation areas and the standard area is obtained, and then the typical value beta 1 of the similarity beta values is obtained;
the sensors are installed in different places according to the principle that the larger the corresponding beta 1 value is, the greater the installation density of the sensors is.
The invention has the beneficial effects that:
1. the invention firstly collects image information in the farmland through unmanned aerial vehicles flying at high altitude, utilizes high consistency of growth of the same crops planted in the same area, has the characteristics of meditation and chromatic aberration if lodging, leaf burning, dry out and different growth progress occur, divides the farmland area into a plurality of divided areas, judges the position of the area possibly having abnormality according to the image chromatic aberration among the divided areas, realizes quick locking of the abnormal land block in the farmland with large area, and then further utilizes unmanned aerial vehicles flying at low altitude, wheeled robots and the like to carry a second high-definition camera for acquiring close-range clear images, thereby facilitating accurate judgment of the problem existing in the abnormal land block by staff; compared with a manual inspection mode, the invention can reduce the labor cost, remarkably improve the inspection efficiency and accuracy, timely find out the land with abnormality, and pertinently process the problem, thereby being beneficial to the expansion of the inhibition loss.
2. According to the invention, the abnormal crop planting area can be identified by analyzing the crop growth state, and the mounting density of various sensors in the monitored farmland is adjusted accordingly, so that more dense information acquisition of abnormal plots is realized, the number of samples is favorably increased, and the accurate judgment of the abnormality and hidden trouble of the abnormal plots by staff is favorably realized.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of a framework structure of a smart agriculture information management platform in embodiment 1;
fig. 2 is a schematic workflow diagram of the intelligent agriculture information management platform in embodiment 1.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The intelligent agriculture information management platform based on cloud computing, as shown in fig. 1, comprises:
the first high-definition camera is used for collecting image information of farmlands and is carried by the high-altitude unmanned aerial vehicle;
the locator is arranged on the high-altitude unmanned aerial vehicle and the accurate acquisition equipment and is used for acquiring the position information of the high-altitude unmanned aerial vehicle and the accurate acquisition equipment;
the position information comprises the plane orthographic projection coordinate position of the high-altitude unmanned aerial vehicle in a coordinate system established for representing the coordinates of each point of a farmland, and the height of the high-altitude unmanned aerial vehicle;
the information transmission module is used for establishing communication connection between front-end equipment consisting of the high-altitude unmanned aerial vehicle, the first high-definition camera and the positioner and back-end equipment consisting of the information processor and the memory;
the memory is used for storing the information acquired by the first high-definition camera and the positioner;
the information processor is used for analyzing and processing the image information acquired by the first high-definition camera to identify an abnormal land block in the monitored farmland, and sending an instruction to the accurate acquisition equipment according to the position of the abnormal land block so as to further acquire the image information in a short distance through the accurate acquisition equipment;
the accurate acquisition equipment is carried with a second high-definition camera and is used for acquiring high-definition image information of a specific position of a farmland, and particularly, after an abnormal land block is determined, the accurate acquisition equipment is used for acquiring the image information of the abnormal land block which is closer and clearer in distance to the abnormal land block at the position of the abnormal land block;
the accurate acquisition equipment can be an unmanned aerial vehicle with lower flying height than that of the unmanned aerial vehicle and flying at low altitude, and also can be a wheeled robot carrying a second high-definition camera;
the working method of the intelligent agricultural information management platform based on cloud computing is shown in fig. 2, and comprises the following steps:
s1, flying over a farmland by using a high-altitude unmanned aerial vehicle carrying a first high-definition camera, acquiring high-definition image information of the farmland through the first high-definition camera, and transmitting the acquired high-definition image information of the farmland to a memory and an information processor through an information transmission module;
for ease of understanding, two methods for capturing high-definition image information for a first high-definition camera are provided in detail below:
first kind: the high-altitude unmanned aerial vehicle flies above farmlands according to a pre-planned flight path, the first high-definition camera collects high-definition image information of one farmland at intervals of preset time t1, and when the first high-definition camera collects the high-definition image information of the farmland, the position information of the high-altitude unmanned aerial vehicle is obtained through the positioner, namely, the high-definition image information of each farmland corresponds to one position information of the high-altitude unmanned aerial vehicle;
second kind: setting a plurality of mark points in a farmland, when the high-altitude unmanned aerial vehicle flies above the farmland, under the condition that the acquisition angle of the first high-definition camera is unchanged, if the plane orthographic projection coordinate of the Gao Kongmo man-machine coincides with the mark point coordinate or approaches to a certain range, acquiring high-definition image information once by the first high-definition camera, preferably limiting the acquisition times of the high-definition image information of the first high-definition camera corresponding to the same mark point at the moment, and limiting the acquisition times of the high-definition image information corresponding to the same point to be at most two times in one acquisition task of the high-altitude unmanned aerial vehicle;
it should be noted that, in the first or second method for acquiring high-definition image information, the flying height of the high-altitude unmanned aerial vehicle should be as stable as possible during the acquisition process, where the height refers to the difference between the high-altitude unmanned aerial vehicle and the ground.
S2, analyzing and processing the high-definition image information acquired by the first high-definition camera through the information processor to acquire the position information of the abnormal land block in the farmland;
specific:
s21, uniformly dividing the high-definition image information into a plurality of rectangular dividing regions, and acquiring the coordinates of four corners of each dividing region according to the high-altitude unmanned aerial vehicle position information corresponding to the high-definition image information and the position of each dividing region in a picture so as to realize the positioning of each dividing region;
s22, dividing each high-definition image information acquired by a first high-definition camera in the execution process of a flight task of the high-altitude unmanned aerial vehicle into a plurality of divided areas according to the rules, wherein all the acquired divided areas can be used for completing the coverage of the detected farmland area;
s23, classifying each segmented region according to the similarity of the corresponding images, wherein the similarity between any two segmented regions in the same class is not smaller than a preset proportionality coefficient;
s24, marking the type of the segmentation areas with the largest quantity as standard areas;
marking the abnormal areas of the other types of the divided areas;
when the area proportion of the abnormal areas contained in the same continuous graph is not smaller than the preset proportion alpha, the farmland position covered by the corresponding continuous graph is considered to be an abnormal land block;
preferably, in order to ensure the rationality of the division of the abnormal land, any rectangular area with the area of a preset value is taken in the abnormal land during the division, and the area ratio occupied by the abnormal area in the rectangular area is not less than the preset ratio alpha 1, and alpha 1 is smaller than alpha;
preferably, when dividing the high-definition image information into the divided areas, firstly cutting off the image within a certain range of the edge of the high-definition image information, and carrying out subsequent analysis by using the rest image part, so that the influence on a result caused by the fact that the color difference between the side image and the top image of the crop is larger under the condition that the flying height of the high-altitude unmanned aerial vehicle is lower and/or the crop planting density is smaller can be reduced;
it should be noted that if the high-definition image information needs to be partially cut off, the acquisition density of the high-definition image information needs to be planned in the acquisition stage, so that the high-definition image information which is finally analyzed can cover the whole monitored farmland area;
s3, after the position information of the abnormal land is acquired, the information processor gives an instruction to the accurate acquisition equipment, the accurate acquisition equipment enters the range of the abnormal land, and the image information of the abnormal land is acquired through the second high-definition camera;
specifically, when image information is acquired in an abnormal land block through the second high-definition camera, a plurality of sample acquisition points can be uniformly acquired in the corresponding abnormal land block, and the second high-definition camera acquires the image information when the second high-definition camera reaches the sample acquisition points;
s4, the information processor packages or randomly selects a plurality of pieces of image information acquired by the second high-definition camera to serve as samples to be sent to terminal equipment of corresponding staff, and the staff can intuitively judge the abnormal problem of the abnormal land.
The invention firstly collects image information in the farmland through unmanned aerial vehicles flying at high altitude, utilizes high consistency of growth of the same crops planted in the same area, has the characteristics of meditation and chromatic aberration if lodging, leaf burning, dry out and different growth progress occur, divides the farmland area into a plurality of divided areas, judges the position of the area possibly having abnormality according to the image chromatic aberration among the divided areas, realizes quick locking of the abnormal land block in the farmland with large area, and then further utilizes unmanned aerial vehicles flying at low altitude, wheeled robots and the like to carry a second high-definition camera for acquiring close-range clear images, thereby facilitating accurate judgment of the problem existing in the abnormal land block by staff; compared with a manual inspection mode, the invention can reduce the labor cost, remarkably improve the inspection efficiency and accuracy, timely find out the land with abnormality, and pertinently process the problem, thereby being beneficial to the expansion of the inhibition loss.
Example two
On the basis of embodiment 1, the intelligent agricultural information management platform based on cloud computing further comprises a modeling module, wherein the modeling module is used for building a model of a monitored farmland, and after abnormal plots are determined, the positions of the abnormal plots can be marked in the model of the monitored farmland, so that a worker can conveniently and accurately identify the sources of the image information when viewing the image information.
Example III
On the basis of embodiment 1, the present embodiment also discloses a method for designing the distribution of sensor modules, wherein the sensor modules are used for detecting soil related parameters of various places of farmlands, and the method comprises, but is not limited to, a soil humidity sensor, a nitrogen-phosphorus-potassium concentration sensor and the like;
when the sensor module is set, the sensors of the abnormal land block can be installed preferentially, specifically, the installation density of the sensors of the abnormal land block is improved, and the installation density of the sensors of the abnormal land block is enabled to be larger than that of the sensors of the standard area;
furthermore, a plurality of segmentation areas can be randomly selected from the abnormal land, the similarity beta between the segmentation areas and the standard area can be obtained, and the typical value beta 1 of the similarity beta can be obtained;
the typical value β1 may be an average value, a median value, an average value of remaining values after removing a plurality of extreme values, an average value of remaining values after removing a value with a larger deviation value, etc. of a plurality of corresponding similarity β values;
installing the sensors in different places according to the principle that the larger the corresponding beta 1 value is, the larger the installation density of the sensors is;
furthermore, the problems of crops can be analyzed and identified according to staff, and the installation density of various sensors can be adjusted in a targeted manner, for example, if the situation that crops in corresponding abnormal plots have phosphorus deficiency compared with the same crops in standard areas is judged through analysis, the installation density of phosphorus sensors can be adjusted in a targeted manner, and other sensors are installed according to the installation density of the standard areas;
according to the invention, the abnormal crop planting area is identified by analyzing the crop growth state, and the mounting density of various sensors in the monitored farmland is adjusted accordingly, so that more dense information acquisition of abnormal plots is realized, the number of samples is favorably increased, and the accurate judgment of the abnormality and hidden trouble of the abnormal plots by staff is favorably realized.
The foregoing is merely illustrative and explanatory of the invention, as various modifications and additions may be made to the particular embodiments described, or in a similar manner, by those skilled in the art, without departing from the scope of the invention or exceeding the scope of the invention as defined in the claims.
Claims (8)
1. Intelligent agriculture information management platform based on cloud calculates, its characterized in that includes:
the first high-definition camera is used for collecting image information of farmlands and is carried by the high-altitude unmanned aerial vehicle;
the locator is arranged on the high-altitude unmanned aerial vehicle and the accurate acquisition equipment and is used for acquiring the position information of the high-altitude unmanned aerial vehicle and the accurate acquisition equipment;
the information transmission module is used for establishing communication connection among the first high-definition camera, the locator, the information processor and the memory;
the memory is used for storing information acquired by the first high-definition camera and the positioner;
the accurate acquisition equipment is provided with a second high-definition camera and is used for acquiring image information of a specific farmland position;
the information processor is used for identifying the abnormal land parcels in the monitored farmland, sending instructions to the accurate acquisition equipment according to the positions of the abnormal land parcels, and further acquiring image information of the abnormal land parcels.
2. The intelligent agricultural information management platform based on cloud computing as claimed in claim 1, wherein the method for identifying the abnormal land parcel by the information processor comprises the following steps:
s1, carrying a first high-definition camera by a high-altitude unmanned aerial vehicle to fly above a farmland, acquiring high-definition image information of the farmland through the first high-definition camera, and transmitting the acquired high-definition image information of the farmland to a memory and an information processor through an information transmission module;
s2, acquiring position information of an abnormal land block in a farmland, and specifically:
s21, uniformly dividing a piece of high-definition image information into a plurality of rectangular dividing areas, and positioning each dividing area;
s22, acquiring a plurality of segmentation areas corresponding to farmlands;
s23, classifying each segmented region, wherein the similarity between any two segmented regions in the same class is not smaller than a preset proportionality coefficient;
s24, marking the segmented regions with the largest quantity as standard regions, and marking the segmented regions of other classes as abnormal regions;
when the area proportion of the abnormal areas contained in the same continuous graph is not smaller than the preset proportion alpha, the farmland position covered by the corresponding continuous graph is considered to be an abnormal land block;
s3, the information processor gives an instruction, the accurate acquisition equipment enters the range of the abnormal land block, and the image information of the abnormal land block is acquired through the second high-definition camera;
and S4, the information processor sends the image information acquired by the second high-definition camera to terminal equipment of a corresponding worker.
3. The cloud computing-based intelligent agricultural information management platform according to claim 2, wherein any rectangular area with an area of a preset value is taken in the abnormal land, and the area ratio occupied by the abnormal area in the rectangular area is not smaller than a preset ratio alpha 1, alpha 1 < alpha.
4. The cloud computing-based intelligent agricultural information management platform according to claim 2, wherein in step S21, when the segmented regions are acquired, the images within the preset range of the edges of the high-definition image information are first cut off, and the segmented regions are acquired with the remaining image portions.
5. The intelligent agricultural information management platform based on cloud computing as claimed in claim 2, further comprising a modeling module;
the modeling module is used for establishing a model of the monitored farmland, marking the position of the abnormal land in the model of the monitored farmland after determining the abnormal land, and checking the marked model by a staff through the terminal equipment.
6. The cloud computing-based intelligent agricultural information management platform according to claim 2, wherein in the step S3, when image information is collected in an abnormal land block by the second high-definition camera, a plurality of sample collection points are uniformly taken in the corresponding abnormal land block, and the second high-definition camera collects the image information when reaching the sample collection points.
7. The intelligent agricultural information management platform based on cloud computing as claimed in claim 2, further comprising a sensor module for detecting soil related parameters of each place of the farmland;
when the sensor module is set, the sensor installation density of the abnormal land is greater than that of the standard area.
8. The cloud computing-based intelligent agricultural information management platform according to claim 7, wherein a plurality of partitioned areas are randomly selected from an abnormal plot, and the similarity beta between the partitioned areas and a standard area is obtained, so that a typical value beta 1 of the plurality of similarity beta values is obtained;
the sensors are installed in different places according to the principle that the larger the corresponding beta 1 value is, the greater the installation density of the sensors is.
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