CN113191302B

CN113191302B - Method and system for monitoring grassland ecology

Info

Publication number: CN113191302B
Application number: CN202110530230.9A
Authority: CN
Inventors: 廖艳红
Original assignee: Chengdu Hongyu Network Technology Co ltd
Current assignee: Chengdu Hongyu Network Technology Co ltd
Priority date: 2021-05-14
Filing date: 2021-05-14
Publication date: 2022-11-01
Anticipated expiration: 2041-05-14
Also published as: CN113191302A

Abstract

The invention discloses a method and a system for monitoring grassland ecology.A monitoring parameter information set is obtained according to the geographical position characteristics of a first grassland and the area information of the first grassland; acquiring matched camera equipment according to the monitoring parameter information set and the camera device; obtaining first image information through a matching camera device; acquiring a preset partition standard; partitioning the first image information according to a preset partitioning standard to obtain a first grassland geographical position characteristic; acquiring parameter image characteristic information according to a first monitoring parameter of a first grassland; sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result; and judging whether the first comparison result meets a preset parameter threshold value or not, and obtaining first reminding information when the first comparison result does not meet the preset parameter threshold value. The method solves the technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time grassland monitoring and control in the prior art.

Description

Method and system for monitoring grassland ecology

Technical Field

The invention relates to the technical field of data analysis, in particular to a method and a system for monitoring grassland ecology.

Background

Grasslands are also one of the main natural ecosystem types in China. According to data statistics, the area of the grassland available in China is 3.365 hundred million hectares, and the grassland area accounts for about 7.1 percent of the total area of the grassland in the world. The types of grasslands in China are more, and the inner Mongolia grassland is dominated by perennial and xerophyte low-temperature herbaceous plants on the whole, and the group-building plants are mainly gramineae, wherein stipa capillata and leymus chinensis are the most representative. The former is a grass of fasciculate grass, the latter is a grass of rhizome, the rhizome is developed, plays an important role in wind prevention and sand fixation; the middle part of China is sparse grassland and takes stipa virgata as the main part; the west part is desert grassland and mainly comprises cluster gobi. The grassland plays a great role in protecting the nature, is not only an important geographical barrier, but also a natural defense line for preventing desert from spreading, and plays a role of an ecological barrier. In addition, it is a natural base for humans to develop animal husbandry. And the grassland ecology is damaged due to the lack of scientific and effective management measures for a long time in China. Most grasslands are in the lagging state of self-extinct of the pasture and daily animal feeding. The first problem to be considered in the strategy of protecting the grassland ecosystem is the enhancement of the grassland ecological basic theory, such as the study of animal carrying capacity, the best mode of animal husbandry production and the scientific management technology.

However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:

in the prior art, the technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time grassland monitoring and control is solved.

Disclosure of Invention

The embodiment of the application provides a method and a system for monitoring grassland ecology, and solves the technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time monitoring and control of the grassland in the prior art.

In view of the above problems, the present application provides a method and a system for monitoring grassland ecology.

In a first aspect, an embodiment of the present application provides a method for monitoring ecology of grassland, where the method is applied to an ecology monitoring system, the system includes a plurality of camera devices, and the method includes: obtaining a first grassland geographical position characteristic and first grassland area information; acquiring a monitoring parameter information set according to the geographical position characteristics of the first grassland and the area information of the first grassland; obtaining matched camera equipment according to the monitoring parameter information set and the camera device; acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland; acquiring a preset partition standard; partitioning the first image information according to the preset partitioning standard to obtain a first image partitioning set; obtaining parameter image characteristic information according to the first monitoring parameter of the first grassland; sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result; obtaining a preset parameter threshold according to the first monitoring parameter of the first grassland; and judging whether the first comparison result meets the preset parameter threshold value or not, and if not, obtaining first reminding information.

In another aspect, the present application further provides a system for monitoring ecology of grasses, the system comprising:

the first obtaining unit is used for obtaining the geographical position characteristics of a first grassland and the area information of the first grassland;

a second obtaining unit, configured to obtain a monitoring parameter information set according to the geographic position feature of the first grassland and the area information of the first grassland;

the first matching unit is used for obtaining matched camera equipment according to the monitoring parameter information set and the plurality of camera devices;

the first acquisition unit is used for acquiring first image information through the matched camera equipment, and the first image information comprises a first monitoring parameter of a first grassland;

a third obtaining unit, configured to obtain a preset partition standard;

a fourth obtaining unit, configured to partition the first image information according to the preset partition standard to obtain a first image partition set;

a fifth obtaining unit, configured to obtain parameter image feature information according to the first monitoring parameter of the first grassland;

a sixth obtaining unit, configured to perform feature traversal comparison on each image partition in the first image partition set in sequence according to the parameter image feature information, so as to obtain a first comparison result;

a seventh obtaining unit, configured to obtain a preset parameter threshold according to the first monitoring parameter of the first grassland;

and the first execution unit is used for judging whether the first comparison result meets the preset parameter threshold value or not, and when the first comparison result does not meet the preset parameter threshold value, acquiring first reminding information.

In a third aspect, the present invention provides a system for monitoring grassy ecology, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method of the first aspect.

One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

the embodiment of the application provides a method and a system for monitoring grassland ecology, wherein the method is applied to an ecological monitoring system, the system comprises a plurality of camera devices, and the method comprises the steps of obtaining geographical position characteristics of a first grassland and area information of the first grassland; acquiring a monitoring parameter information set according to the geographical position characteristics of the first grassland and the area information of the first grassland; obtaining matched camera equipment according to the monitoring parameter information set and the camera device; acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland; acquiring a preset partition standard; partitioning the first image information according to the preset partitioning standard to obtain a first image partitioning set; obtaining parameter image characteristic information according to the first monitoring parameter of the first grassland; sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result; obtaining a preset parameter threshold according to the first monitoring parameter of the first grassland; and judging whether the first comparison result meets the preset parameter threshold value or not, and if not, acquiring first reminding information. When the first comparison result exceeds the range of the preset parameter threshold, the parameter change condition is shown to exceed the normal range of ecological monitoring, attention needs to be paid when abnormality occurs, all monitoring parameters are respectively processed correspondingly to obtain the comprehensive monitoring result of the grassland ecology, parameter contents which do not meet requirements are reminded, managers can supervise the grassland ecology according to the monitoring result, intelligent image recognition is achieved through real-time image acquisition of the grassland and machine learning processing, scientific and effective grassland monitoring is achieved, the adaptive supervision means is determined by the grassland ecology monitoring result, the healthy development of the grassland can be facilitated, a series of ecological problems such as grassland degradation, alkalization and desertification, climate deterioration and serious rat damage are avoided as far as possible through scientific and effective monitoring and reasonable means are used for intervention and guidance, and the technical effect of the grassland ecological environment is maintained. The method solves the technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time grassland monitoring and control in the prior art.

The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.

Drawings

FIG. 1 is a schematic flow chart of a method for monitoring ecology of grasses according to an embodiment of the present disclosure;

FIG. 2 is a schematic structural diagram of a grassland ecology monitoring system according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.

Description of the reference numerals: the system comprises a first obtaining unit 11, a second obtaining unit 12, a first matching unit 13, a first acquiring unit 14, a third obtaining unit 15, a fourth obtaining unit 16, a fifth obtaining unit 17, a sixth obtaining unit 18, a seventh obtaining unit 19, a first executing unit 20, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304 and a bus interface 305.

Detailed Description

The embodiment of the application provides a method and a system for monitoring the ecology of the grassland, and solves the technical problems that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time monitoring and control of the grassland in the prior art. The intelligent image recognition is carried out by machine learning processing through real-time image acquisition of the grassland, scientific and effective grassland monitoring is realized, the determination of adaptive supervision means is carried out by using the grassland ecological monitoring result, the healthy development of the grassland can be facilitated, and the intervention and guidance are carried out by using reasonable means through scientific and effective monitoring, so that a series of ecological problems such as grassland degradation, alkalization and desertification, climate deterioration and serious rat damage are avoided as far as possible, and the technical effect of the grassland ecological environment is maintained. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only a few embodiments of the present application, and not all embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein.

Summary of the application

The grassland plays a great role in protecting the nature, is not only an important geographical barrier, but also a natural defense line for preventing desert from spreading, and plays a role of an ecological barrier. In addition, it is a natural base for humans to develop animal husbandry. And the grassland ecology is damaged due to the lack of scientific and effective management measures for a long time in China. Most grasslands are in the lagging state of self-extinct of the pasture and daily animal feeding. The enhancement of grassland ecological basic theories such as animal carrying capacity, the best mode of animal husbandry production and the research of scientific management technology is a problem which needs to be firstly emphasized in the protection strategy of the grassland ecological system. However, the prior art in the prior art is lack of scientific and effective real-time monitoring and control of the grassland, and the technical problem that the grassland is damaged and gradually reduced exists.

In view of the above technical problems, the technical solution provided by the present application has the following general idea:

acquiring a first grassland geographical position characteristic and first grassland area information; acquiring a monitoring parameter information set according to the geographical position characteristics of the first grassland and the area information of the first grassland; obtaining matched camera equipment according to the monitoring parameter information set and the camera device; acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland; obtaining a preset partition standard; partitioning the first image information according to the preset partitioning standard to obtain a first image partitioning set; acquiring parameter image characteristic information according to the first monitoring parameter of the first grassland; sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result; obtaining a preset parameter threshold according to the first monitoring parameter of the first grassland; and judging whether the first comparison result meets the preset parameter threshold value or not, and if not, acquiring first reminding information. The intelligent image recognition is carried out by machine learning processing through real-time image acquisition of the grassland, scientific and effective grassland monitoring is realized, the determination of adaptive supervision means is carried out by using the grassland ecological monitoring result, the healthy development of the grassland can be facilitated, and the intervention and guidance are carried out by using reasonable means through scientific and effective monitoring, so that a series of ecological problems such as grassland degradation, alkalization and desertification, climate deterioration and serious rat damage are avoided as far as possible, and the technical effect of the grassland ecological environment is maintained.

Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.

Example one

As shown in fig. 1, an embodiment of the present application provides a method for monitoring grassland ecology, which is applied to an ecology monitoring system, the system including a plurality of camera devices, and the method includes:

particularly, a plurality of camera device include a plurality of quantity, also include a plurality of kind, because the particularity of grassland carries out camera device's installation and distribution and has certain difficulty, can install ground camera device on the meadow, ground camera device can be close to the grassland meadow shoot with the monitoring but can't carry out the global shooting collection to situations such as whole face and the article distribution on the grassland of whole grassland, can carry out the image acquisition in a relatively large scale to the grassland through high altitude camera equipment, realize diversified grassland image acquisition through polytype camera device, realize the intelligent monitoring to grassland ecological environment through the analysis to the image, ensure monitoring degree and monitoring range.

Step S100: acquiring a first grassland geographical position characteristic and first grassland area information;

specifically, different grasslands have different differences due to different geographical positions, and mainly have different geographical climates and environments, and meanwhile, due to different geographical position environments, vegetation, animals, microorganisms and the like on the grasslands also have differences, so that when grassland ecological monitoring is carried out, the geographical positions of the monitored grasslands are firstly determined to carry out corresponding monitoring according to specific grassland characteristics, and the ecological characteristics of the grasslands are better met. The first grassland area information is the area of the monitoring grassland, because different grassland areas have differences of monitoring requirements, the depth and range requirements for the small-area grassland monitoring can be more detailed, and the corresponding is slightly loose for the grassland with a wide area, and the monitoring difficulty and the detail degree are influenced. Therefore, the grassland area should also be used as the corresponding standard set by the monitoring requirement.

Step S200: acquiring a monitoring parameter information set according to the first grassland geographical position characteristic and the first grassland area information;

further, the step S200 of obtaining a monitoring parameter information set according to the first grassland geographic location feature and the first grassland area information includes:

step S210: obtaining first position climate information according to the first grassland geographical position characteristics;

step S220: acquiring a grassland ecological control rule according to the first position climate information;

step S230: taking the grassland ecological control rule as first input information;

step S240: taking the first grassland area information as second input information;

step S250: inputting the first input information and the second input information into a monitoring parameter analysis model, wherein the monitoring parameter analysis model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying monitoring parameter information;

step S260: and obtaining output information of the monitoring parameter analysis model, wherein the output information comprises the monitoring parameter information.

Specifically, the geographic position characteristics and the grassland area information of the grassland are utilized to determine monitoring parameters, including ecological parameter requirements corresponding to the grass amount control, the animal raising period, the animal raising density, the animal quantity balance requirement and the like, which parameter indexes can influence the ecological environment of the grassland, such as excessive animal raising, mouse damage, climate drought influence and the like, and how to correspondingly monitor according to the grass amount is beneficial to maintaining the stability of the ecological environment of the grassland. In order to improve the accuracy of the analysis result of the physical therapy principle of the physical therapy scheme, the embodiment of the application constructs a deep Neural network model for processing, and utilizes a mathematical model for operation processing to improve the operation speed and improve the accuracy of the extraction result, the monitoring parameter analysis model is the deep Neural network model in machine learning, corresponding grassland ecological control rule setting is carried out according to the position climate information determined by the weather and climate of a grassland, different grassland climates correspond to different grass growth, different grass growth has different monitoring requirements and standards, corresponding ecological maintenance requirements set according to the characteristics of the grassland climate, the grass growth and vegetation characteristics are included in the grassland ecological control rule, namely, how to maintain the parameter conditions meet the requirement of ecological stability and not meet the requirement of ecological imbalance ecological damage, the grassland ecological control rule is used as first input information of the Neural network, meanwhile, the first grassland area information is second input information, the size of the grassland area determines the setting range of corresponding parameter values and the corresponding parameter requirements, the Neural network (Neurwork, NN) is a large number of simple Neural network processing units, and a brain network system with a large number of linear connection and a large number of non-linear learning and complicated brain power reflecting the basic characteristics of a human system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. And through training of a large amount of training data, inputting the first input information and the second input information into a neural network model, and outputting monitoring parameter information.

More specifically, the training process is essentially a supervised learning process, each group of supervised data includes the first input information, the second input information and identification information for identifying the monitoring parameter information, the first input information and the second input information are input into a neural network model, the neural network model is continuously self-corrected and adjusted according to the identification information for identifying the monitoring parameter information, and the group of supervised learning is ended until the obtained output result is consistent with the identification information, and the next group of supervised learning is carried out; when the output information of the neural network model reaches a preset accuracy rate/reaches a convergence state, the supervised learning process is ended. Through the supervision and learning of the neural network model, the neural network model is enabled to process the input information more accurately, more accurate and suitable monitoring parameter information is obtained, the area size of the grassland combined with the geographical environment and climate characteristics of the grassland is further utilized, the corresponding ecological parameter monitoring requirements are determined, corresponding monitoring is carried out according to the parameter monitoring requirements which accord with the characteristics of the grassland so as to ensure the stability of the ecological environment of the grassland, meanwhile, the neural network model is added, the efficiency and the accuracy of data operation processing results are improved, and a foundation is tamped for providing more accurate and reliable ecological monitoring of the grassland.

Step S300: obtaining matched camera equipment according to the monitoring parameter information set and the camera device;

step S400: acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland;

specifically, the monitoring parameter information set comprises all corresponding monitoring parameter contents in the grassland monitoring requirements, such as a series of ecological monitoring parameter requirements of grassland humidity, grass amount, grass density, grassland desertification proportion, livestock raising time density requirements, grassland growth range, mouse distribution density, mouse quantity and the like, matching of the camera equipment is carried out according to different requirements, because different parameters require different images and image data, some need dynamic image information of static images, some need near-distance image acquisition on grassland by the camera equipment on the ground of the grassland, and some need large-area wide integral image acquisition of the grassland by the high-altitude camera, matching of corresponding camera devices is carried out according to specific parameter requirements in the monitoring parameter information set, and corresponding image acquisition is carried out by the matched camera equipment. The first image information comprises a plurality of kinds of image information, corresponds to parameters in the monitoring parameter information set, and can obtain the requirements of each monitoring parameter in the monitoring parameter set through analysis and extraction of each image information. Each of the first image information corresponds to a monitoring parameter of the set of monitoring parameter information.

Step S500: acquiring a preset partition standard;

specifically, image information is partitioned according to analysis requirements, and convolution kernels are used for image processing and feature extraction, so that the identification and analysis requirements of corresponding features are achieved by using the image information. One property that convolution kernels have is locality. I.e. it only focuses on local features, the degree of locality depending on the size of the convolution kernel. The essence is to compare the similarity of neighboring pixels of the image. The convolution of the original image with the convolution kernel selects the frequency domain information. For example, the edge and contour in the image belong to high frequency information, and the comprehensive consideration of the intensity of a certain region in the image belongs to low frequency information. In conventional image processing, this is an important aspect of guided design of the convolution kernel.

Step S600: partitioning the first image information according to the preset partitioning standard to obtain a first image partitioning set;

step S700: obtaining parameter image characteristic information according to the first monitoring parameter of the first grassland;

step S800: sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result;

specifically, the first image information is partitioned according to a preset partitioning standard, namely the image information is divided into a plurality of blocks, each block is convoluted to obtain an output result, each partition is used for carrying out feature comparison to obtain an image processing result, the content identical to the feature information exists in the image is extracted, so that the image identification result is output, the image identification extraction result identical to the parameter image feature information requirement is obtained, for example, the monitoring parameter is rat damage monitoring, the parameter image feature information is the feature of a teacher and comprises integral and local features, the rat damage monitoring is carried out by utilizing ground monitoring equipment to carry out image acquisition, the acquired image information is partitioned, each partition is subjected to one-pass feature comparison according to the feature information, the image information is identified and extracted when the feature identical to the feature information exists, the result is output, and the first comparison result is the output result, wherein the identification result identical to the parameter feature is identified, and the monitoring requirement information content appearing in the image information can be reflected.

Step S900: obtaining a preset parameter threshold according to the first monitoring parameter of the first grassland;

specifically, setting a corresponding parameter threshold according to the requirement of a monitoring parameter, wherein the first monitoring parameter is one parameter in a monitoring parameter set, determining the requirement of monitoring the parameter according to different parameter contents and the combination of the geographic position of the grassland and the current ecological environment, indicating that the ecological requirement of the grassland is exceeded when the parameter threshold is exceeded, needing to pay attention, and meeting the balance requirement of the ecological environment if the parameter threshold is within the threshold range.

Step S1000: and judging whether the first comparison result meets the preset parameter threshold value or not, and if not, acquiring first reminding information.

Specifically, when the first comparison result exceeds the range of the preset parameter threshold, the parameter change condition is shown to exceed the normal range of ecological monitoring, attention needs to be paid when abnormality occurs, all monitoring parameters are respectively and correspondingly processed to obtain the comprehensive monitoring result of the grassland ecology, parameter contents which do not meet requirements are reminded, management personnel can supervise the grassland ecology according to the monitoring result, the healthy development of the grassland is realized through scientific and effective grassland monitoring and supervision, a series of ecological problems such as grassland degeneration, alkalization, desertification, climate deterioration, serious rat damage and the like are avoided as far as possible, intervention guidance is carried out through scientific and effective monitoring by using reasonable means, and the grassland ecological basic theory such as animal carrying capacity, optimal mode of animal husbandry production and scientific management are enhanced, so that the grassland ecological environment is maintained. Thereby the technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time grassland monitoring and control in the prior art is solved.

Further, the method comprises:

step S1110: when the first comparison result meets the preset parameter threshold, obtaining a first parameter historical record;

step S1120: acquiring a parameter development trend according to the first parameter historical record and the first comparison result;

step S1130: and when the parameter development trend does not meet a first preset condition, second reminding information is obtained.

Specifically, for the monitoring parameter results of which the first comparison results meet the preset parameter threshold, the results are continuously and synchronously stored, so that data analysis and comparison are facilitated in the later period, calculation and analysis of parameter development trends are performed by using historical monitoring data and the first comparison results, the development conditions of the parameters are reflected by using numerical value changes, and if the change trends exceed preset conditions, reminding is also performed, so that the technical effects of early warning and reminding in advance by using the change of the trends through data analysis are achieved.

Further, the method comprises:

step S1210: obtaining a first influence factor according to the geographical position characteristics of the first grassland;

step S1220: obtaining a first animal characteristic according to the first influence factor;

step S1230: obtaining first animal image characteristic information according to the first animal characteristics;

step S1240: according to the first image partition set and the first animal image feature information, animal identification area information is obtained;

step S1250: obtaining animal quantity information according to the animal identification area information;

step S1260: obtaining a preset area range according to the animal identification area information;

step S1270: obtaining a first animal region density according to the animal quantity information and the preset region range;

step S1280: and when the density of the first animal region exceeds a second preset condition, sending a third reminding message.

Specifically, the current main causes of the ecological damage of the grassland include a series of ecology such as grassland degradation, alkalization and desertification, climate deterioration and serious rat damage, wherein the grassland degradation, desertification, excessive animal husbandry and rat damage are all related, and the damage of the excessive animal husbandry and the ecological environment is caused artificially and is a factor capable of intervening, so that the ecological environment of the grassland can be effectively controlled by controlling the animal husbandry quantity and the number of rats on the grassland, and the monitoring of the animal husbandry quantity and the number of rats plays an important role in the ecological monitoring of the grassland. The method comprises the steps that different grasslands at different geographic positions correspond to influence factors and are different, livestock breeding in some regions is developed, and the livestock breeding in some grasslands is limited, so that the control requirements on the livestock breeding number are different, the number of mice is different for the grasslands at different geographic positions, the first influence factor is determined according to the characteristics of the grasslands, the first influence factor is any one of the influence factors, the first animal corresponds to the influence factors, the acquired image is subjected to partition processing through image acquisition on the grasslands, characteristic information matched with the characteristics of the animal is extracted when the characteristic information appears, real-time monitoring on the influence factors in the grasslands is realized, and when the monitored density of the influence animals exceeds a preset density range, reminding information is sent out, and intelligent monitoring on the grasslands is realized.

Further, the method comprises:

step S1310: obtaining a preset animal influence cycle;

step S1320: obtaining historical density information of a first animal according to the preset animal influence cycle and the first animal characteristics;

step S1330: obtaining the average density of the first animal according to the density of the first animal region and the historical density information of the first animal;

step S1340: obtaining a first animal average density threshold value according to the first grassland geographical position characteristic and the first grassland area information;

step S1350: determining whether the first animal average density exceeds the first animal average density threshold;

step S1360: and when the time exceeds the preset time, obtaining fourth reminding information.

Specifically, when the density of the rat reaches a preset density requirement, an early warning prompt is sent, for the control of animal husbandry, long-term density control is needed, the density at one time point cannot be monitored and prompted, therefore, through the influence period of the animal, if the number of animal husbandry reaches the density within a certain period, the ecological environment of the grassland is influenced, the density requirement within the period is utilized for monitoring, meanwhile, the density requirement of animal husbandry is matched with the area and the grass amount of the grassland, therefore, when the density threshold value is set, the corresponding setting is carried out by combining the characteristics of the area and the grass amount of the grassland, and when the density of the animal husbandry within a certain period exceeds the threshold value requirement, a prompt is sent. The method has the advantages that the corresponding parameter standard setting is carried out in combination with the specific characteristics of the monitoring parameters, so that the method is more in line with the characteristics of the grassland, intelligent monitoring and reminding are carried out according to the requirements of the monitoring parameters, real-time grassland monitoring is realized, and the monitoring level is improved by using scientific and real-time monitoring means.

Further, the method comprises:

step S1410: obtaining second location climate information;

step S1420: obtaining a climate influence grade according to the second location climate information and the geographical location characteristics of the first grassland;

step S1430: when the climate influence level reaches a preset condition, acquiring a grassland ecological updating rule according to the climate information of the second position;

step S1440: inputting the grassland ecological updating rule into the monitoring parameter analysis model for training to obtain monitoring parameter updating data;

step S1450: performing data loss analysis on the monitoring parameter information and the monitoring parameter updating data to obtain parameter loss data;

step S1460: and inputting the parameter loss data into the monitoring parameter analysis model to generate a second monitoring parameter model, wherein the second monitoring parameter model is a new model after incremental learning.

Specifically, when the second position climate information is the second climate when the climate of the grassland changes and affects the grassland, and the grade of the second position climate information is judged to affect the growth of the grassland, the second position climate information is determined as a new climate parameter, and the second position climate information is different from the first position climate information and changes, so that the second position climate information is added into the training of the monitoring parameter analysis model, incremental learning of the monitoring parameter analysis model is realized through the changed training data, and the relevant data processing is facilitated for a platform built by a computer. And inputting the parameter loss data into the monitoring parameter analysis model, constructing the model to further obtain the second monitoring parameter model, specifically, obtaining a predicted value of the old model to the grassland ecological updating rule, and further, completing construction of a new model by determining loss data, so that the problem that the performance of the new model is reduced due to the fact that the parameters of the monitoring parameter information are adjusted excessively by training of the second monitoring parameter model is solved. The learning training data is continuously updated through incremental learning of the model, monitoring parameter analysis is improved and adjusted at any time along with adjustment of the influence parameters, calculation efficiency is improved, the requirement of real-time intelligent and effective ecological monitoring is met, and meanwhile the storage space of the training data is reduced.

Further, the step S220 of obtaining a grassland ecological control rule according to the first location climate information includes:

step S221: obtaining grassland growth cycle information according to the first grassland geographical position characteristics and the first position climate information;

step S222: according to the grassland growth cycle information, obtaining the specific gravity of the grassland growth control time;

step S223: obtaining a period control rule according to the grassland generation period information and the grassland growth control time proportion;

step S224: obtaining grass amount prediction information according to the first grassland geographical position characteristics and the first position climate information;

step S225: obtaining a grass amount control threshold value according to the grass amount prediction information;

step S226: and obtaining the grassland ecological control rule according to the period control rule and the grass amount control threshold, wherein the grassland ecological control rule comprises period time information.

Specifically, the formulation of the grassland ecological control rule also needs to consider the problem of the time period, the growth period of the grassland and the important time in the growth process of the grassland, and the corresponding rule customization is carried out by integrating the monitored time points, the requirements of management should be strictly monitored in the important period of the growth of the grassland, the control requirements of the livestock raising quantity can be relaxed in the mature period of the growth of the grassland, and proper adjustment is carried out according to the monitored time and the growth period characteristics of the grassland so as to stabilize the normal growth and maintenance of the grassland, and meanwhile, the specific control rule and control threshold setting are set according to the specific actual conditions so as to carry out scientific and effective maintenance and monitoring so as to stabilize the ecology of the grassland, namely, avoid overuse and damage, ensure the maximum utilization of the grassland and maintain the development of the livestock raising industry. The intelligent image recognition is carried out by machine learning processing through real-time image acquisition of the grassland, scientific and effective grassland monitoring is realized, the determination of adaptive supervision means is carried out by using the grassland ecological monitoring result, the healthy development of the grassland can be facilitated, and the intervention and guidance are carried out by using reasonable means through scientific and effective monitoring, so that a series of ecological problems such as grassland degradation, alkalization and desertification, climate deterioration and serious rat damage are avoided as far as possible, and the technical effect of the grassland ecological environment is maintained. Further solves the technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time grassland monitoring and control in the prior art.

Example two

Based on the same inventive concept as the method for monitoring the ecology of grasses in the previous embodiment, the present invention further provides a system for monitoring the ecology of grasses, as shown in fig. 2, the system includes:

the first obtaining unit 11 is configured to obtain a first grassland geographical position feature and first grassland area information;

a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain a monitoring parameter information set according to the geographic position feature of the first grassland and the area information of the first grassland;

a first matching unit 13, where the first matching unit 13 is configured to obtain a matched image capturing apparatus according to the monitoring parameter information set and the image capturing device;

the first acquisition unit 14 is used for acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland;

a third obtaining unit 15, where the third obtaining unit 15 is configured to obtain a preset partition standard;

a fourth obtaining unit 16, where the fourth obtaining unit 16 is configured to partition the first image information according to the preset partition standard to obtain a first image partition set;

a fifth obtaining unit 17, where the fifth obtaining unit 17 is configured to obtain parameter image feature information according to the first monitoring parameter of the first grassland;

a sixth obtaining unit 18, where the sixth obtaining unit 18 is configured to perform feature traversal comparison on each image partition in the first image partition set in sequence according to the parameter image feature information, so as to obtain a first comparison result;

a seventh obtaining unit 19, where the seventh obtaining unit 19 is configured to obtain a preset parameter threshold according to the first monitoring parameter of the first grassland;

and the first execution unit 20 is configured to determine whether the first comparison result meets the preset parameter threshold, and obtain first reminding information when the first comparison result does not meet the preset parameter threshold.

Further, the system further comprises:

an eighth obtaining unit, configured to obtain a first parameter history record when the first comparison result meets the preset parameter threshold;

a ninth obtaining unit, configured to obtain a parameter development trend according to the first parameter history record and the first comparison result;

a tenth obtaining unit, configured to obtain second reminding information when the parameter development trend does not satisfy the first predetermined condition.

Further, the system further comprises:

an eleventh obtaining unit, configured to obtain a first influence factor according to the first grassland geographic location characteristic;

a twelfth obtaining unit, configured to obtain a first animal characteristic according to the first influence factor;

a thirteenth obtaining unit configured to obtain first animal image feature information from the first animal feature;

a fourteenth obtaining unit, configured to obtain animal identification area information according to the first image partition set and the first animal image feature information;

a fifteenth obtaining unit configured to obtain animal number information from the animal identification area information;

a sixteenth obtaining unit, configured to obtain a preset area range according to the animal identification area information;

a seventeenth obtaining unit, configured to obtain a density of the first animal region according to the animal quantity information and the preset region range;

the first sending unit is used for sending third reminding information when the density of the first animal region exceeds a second preset condition.

Further, the system further comprises:

an eighteenth obtaining unit for obtaining a preset animal influence cycle;

a nineteenth obtaining unit, configured to obtain first animal historical density information according to the preset animal influence cycle and the first animal characteristic;

a twentieth obtaining unit, configured to obtain a first animal average density according to the first animal region density and the first animal historical density information;

a twenty-first obtaining unit, configured to obtain a first animal average density threshold according to the first grassland geographical location feature and the first grassland area information;

a first judgment unit for judging whether the first animal average density exceeds the first animal average density threshold value;

a twenty-second obtaining unit, configured to obtain fourth reminding information when the second reminding information exceeds the first reminding information.

Further, the system further comprises:

a twenty-third obtaining unit, configured to obtain first location climate information according to the first grassland geographic location feature;

a twenty-fourth obtaining unit, configured to obtain a grassland ecological control rule according to the first location climate information;

the second execution unit is used for taking the grassland ecological control rule as first input information;

a third execution unit, configured to use the first grassland area information as second input information;

a first input unit, configured to input the first input information and the second input information into a monitoring parameter analysis model, where the monitoring parameter analysis model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information, and identification information identifying monitoring parameter information;

a twenty-fifth obtaining unit, configured to obtain output information of the monitoring parameter analysis model, where the output information includes the monitoring parameter information.

Further, the system further comprises:

a twenty-sixth obtaining unit configured to obtain second location climate information;

a twenty-seventh obtaining unit, configured to obtain a climate influence level according to the second location climate information and the geographical location characteristics of the first grassland;

a twenty-eighth obtaining unit, configured to obtain a grassland ecology update rule according to the second location climate information when the climate influence level reaches a predetermined condition;

a twenty-ninth obtaining unit, configured to input the grassland ecological update rule into the monitoring parameter analysis model for training, and obtain monitoring parameter update data;

a thirtieth obtaining unit, configured to obtain parameter loss data by performing data loss analysis on the monitoring parameter information and the monitoring parameter update data;

and the fourth execution unit is used for inputting the parameter loss data into the monitoring parameter analysis model to generate a second monitoring parameter model, and the second monitoring parameter model is a new model after incremental learning.

Further, the system further comprises:

a thirty-first obtaining unit, configured to obtain grassland growth cycle information according to the geographical location characteristics of the first grassland and the climate information of the first location;

a thirty-second obtaining unit, configured to obtain a specific gravity of the growth control time of the grassland according to the growth cycle information of the grassland;

a thirty-third obtaining unit, configured to obtain a period control rule according to the grassland generation period information and the grassland growth control time proportion;

a thirty-fourth obtaining unit, configured to obtain grass amount prediction information according to the geographical location characteristics of the first grassland and the climate information of the first location;

a thirty-fifth obtaining unit configured to obtain a grass amount control threshold value according to the grass amount prediction information;

a thirty-sixth obtaining unit, configured to obtain the grassland ecological control rule according to the period control rule and the grassland control threshold, where the grassland ecological control rule includes period time information.

Various changes and specific examples of a method for monitoring the ecology of grasses in the first embodiment of fig. 1 are also applicable to a system for monitoring the ecology of grasses in the first embodiment of the present invention, and the implementation method of a system for monitoring the ecology of grasses in the present embodiment is clear to those skilled in the art from the foregoing detailed description of a method for monitoring the ecology of grasses, and therefore, for the sake of brevity of description, detailed description thereof is omitted here.

Exemplary electronic device

An electronic apparatus of an embodiment of the present application is described below with reference to fig. 3.

Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.

Based on the inventive concept of a method for monitoring the ecology of grasses in the foregoing embodiment, the present invention further provides a system for monitoring the ecology of grasses, on which a computer program is stored, which, when executed by a processor, implements the steps of any one of the methods for monitoring the ecology of grasses as described above.

Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.

The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.

the embodiment of the application provides a method and a system for monitoring grassland ecology, wherein the method is applied to an ecological monitoring system, the system comprises a plurality of camera devices, and the geographical position characteristics of a first grassland and the area information of the first grassland are obtained; acquiring a monitoring parameter information set according to the geographical position characteristics of the first grassland and the area information of the first grassland; obtaining matched camera equipment according to the monitoring parameter information set and the camera device; acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland; acquiring a preset partition standard; partitioning the first image information according to the preset partitioning standard to obtain a first image partitioning set; acquiring parameter image characteristic information according to the first monitoring parameter of the first grassland; sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result; obtaining a preset parameter threshold according to the first monitoring parameter of the first grassland; and judging whether the first comparison result meets the preset parameter threshold value or not, and if not, acquiring first reminding information. When the first comparison result exceeds the range of the preset parameter threshold value, the parameter change condition is indicated to exceed the normal range of ecological monitoring, attention needs to be paid if abnormality occurs, all monitoring parameters are correspondingly processed respectively to obtain the comprehensive monitoring result of the grassland ecology, parameter contents which do not meet requirements are reminded, management personnel can supervise the grassland ecology according to the monitoring result, intelligent image recognition is achieved through real-time image acquisition of the grassland and machine learning processing, scientific and effective grassland monitoring is achieved, the adaptive supervision means is determined through the grassland ecology monitoring result, the healthy development of the grassland can be facilitated, and a series of ecological problems such as deterioration, alkalization, desertification, climate deterioration, serious rat damage and the like of the grassland are avoided as far as possible through scientific and effective monitoring and reasonable means for intervention and guidance, so that the technical effect of the grassland ecological environment is maintained. The technical problem that the grassland is damaged and gradually reduced due to the lack of scientific and effective real-time grassland monitoring and control in the prior art is solved.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. A method for monitoring grassland ecology, wherein the method is applied to an ecology monitoring system, the system comprises a plurality of camera devices, and the method comprises the following steps:

acquiring a first grassland geographical position characteristic and first grassland area information;

acquiring a monitoring parameter information set according to the geographical position characteristics of the first grassland and the area information of the first grassland;

obtaining matched camera equipment according to the monitoring parameter information set and the camera device;

acquiring first image information through the matched camera equipment, wherein the first image information comprises a first monitoring parameter of a first grassland;

obtaining a preset partition standard;

partitioning the first image information according to the preset partitioning standard to obtain a first image partitioning set;

acquiring parameter image characteristic information according to the first monitoring parameter of the first grassland;

sequentially carrying out feature traversal comparison on each image partition in the first image partition set according to the parameter image feature information to obtain a first comparison result;

obtaining a preset parameter threshold according to the first monitoring parameter of the first grassland;

and judging whether the first comparison result meets the preset parameter threshold value or not, and if not, obtaining first reminding information.

2. The method of claim 1, wherein the method comprises:

when the first comparison result meets the preset parameter threshold, obtaining a first parameter historical record;

acquiring a parameter development trend according to the first parameter historical record and the first comparison result;

and when the parameter development trend does not meet a first preset condition, second reminding information is obtained.

3. The method of claim 1, wherein the method comprises:

obtaining a first influence factor according to the geographical position characteristics of the first grassland;

obtaining a first animal characteristic according to the first influence factor;

obtaining first animal image characteristic information according to the first animal characteristics;

according to the first image partition set and the first animal image feature information, animal identification area information is obtained;

obtaining animal number information according to the animal identification area information;

obtaining a preset area range according to the animal identification area information;

obtaining the density of a first animal region according to the animal quantity information and the preset region range;

and when the density of the first animal region exceeds a second preset condition, sending a third reminding message.

4. The method of claim 3, wherein the method comprises:

obtaining a preset animal influence cycle;

obtaining historical density information of a first animal according to the preset animal influence cycle and the first animal characteristics;

obtaining the average density of the first animal according to the density of the first animal region and the historical density information of the first animal;

obtaining a first animal average density threshold value according to the first grassland geographical position characteristic and the first grassland area information;

determining whether the first animal average density exceeds the first animal average density threshold;

and when the time exceeds the preset time, obtaining fourth reminding information.

5. The method of claim 1, wherein said obtaining a set of monitoring parameter information based on said first grassland geographical location characteristic, said first grassland area information, comprises:

acquiring first position climate information according to the first grassland geographical position characteristics;

acquiring a grassland ecological control rule according to the first position climate information;

taking the grassland ecological control rule as first input information;

taking the first grassland area information as second input information;

inputting the first input information and the second input information into a monitoring parameter analysis model, wherein the monitoring parameter analysis model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information, and identification information identifying monitoring parameter information;

and obtaining output information of the monitoring parameter analysis model, wherein the output information comprises the monitoring parameter information.

6. The method of claim 5, wherein the method comprises:

obtaining second location climate information;

obtaining a climate influence grade according to the second location climate information and the geographical location characteristics of the first grassland;

when the climate influence level reaches a preset condition, acquiring a grassland ecological updating rule according to the climate information of the second position;

inputting the grassland ecological updating rule into the monitoring parameter analysis model for training to obtain monitoring parameter updating data;

performing data loss analysis on the monitoring parameter information and the monitoring parameter updating data to obtain parameter loss data;

and inputting the parameter loss data into the monitoring parameter analysis model to generate a second monitoring parameter model, wherein the second monitoring parameter model is a new model after incremental learning.

7. The method of claim 5, wherein the obtaining of grassland ecological control rules based on the first location climate information comprises:

according to the geographical position characteristics of the first grassland and the climate information of the first position, obtaining the growth cycle information of the grassland;

obtaining the specific gravity of the growth control time of the grassland according to the growth cycle information of the grassland;

obtaining a period control rule according to the grassland growth period information and the grassland growth control time proportion;

obtaining grass amount prediction information according to the first grassland geographical position characteristics and the first position climate information;

obtaining a grass amount control threshold value according to the grass amount prediction information;

and obtaining the grassland ecological control rule according to the period control rule and the grass amount control threshold, wherein the grassland ecological control rule comprises period time information.

8. A system for monitoring grassland ecology, applied to the method of any one of claims 1 to 7, wherein the system comprises a plurality of cameras, the system comprising:

the first matching unit is used for obtaining matched camera equipment according to the monitoring parameter information set and the camera device;

a third obtaining unit, configured to obtain a preset partition standard;

9. A system for monitoring grassland ecology comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the program.