CN111461117A - Yak calf growth environment monitoring system and method - Google Patents

Yak calf growth environment monitoring system and method Download PDF

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CN111461117A
CN111461117A CN202010238244.9A CN202010238244A CN111461117A CN 111461117 A CN111461117 A CN 111461117A CN 202010238244 A CN202010238244 A CN 202010238244A CN 111461117 A CN111461117 A CN 111461117A
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曹涵文
次旦央吉
洛桑顿珠
姜辉
孙光明
陈晓英
张强
朱勇
平措占堆
洛桑
信金伟
张成福
达娃央拉
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Abstract

The invention belongs to the technical field of yak calf growth environment monitoring, and discloses a yak calf growth environment monitoring system and a yak calf growth environment monitoring method, wherein the yak calf growth environment monitoring system comprises the following components: the environment monitoring system comprises an environment video acquisition module, an environment temperature acquisition module, an environment humidity acquisition module, an air quality monitoring module, a data transmission module, a main control module, a video enhancement module, a yak counting module, an environmental sanitation judgment module, a health evaluation module, a data storage module, a terminal module and a display module. According to the method, the brightness of the playing screen during watching is acquired in real time, and the intensity of image enhancement processing is adaptively adjusted in real time according to the brightness value of the playing screen, so that the video definition is greatly improved, and the yak growth environment is more conveniently monitored; meanwhile, after the yak counting module collects the image video data of the yak group, the number of the yaks can be effectively and accurately calculated, and a large number of human resources and equipment cost in a pasturing area are saved.

Description

Yak calf growth environment monitoring system and method
Technical Field
The invention belongs to the technical field of monitoring of the growth environment of yak calves, and particularly relates to a system and a method for monitoring the growth environment of yak calves.
Background
Yak (the name of Bos mutus or Bos grunniens, English name: world yak) belongs to the class of lactation, subclass of beast, order Artiodactyla, suborder ruminants, family Bovidae, subfamily Bovidae, and is one of the special rare cattle species centered on the Qinghai-Tibet plateau in China and adjacent to alpine and alpine regions in mountain, and herbivorous ruminant livestock. Yak can adapt to high and cold climate, is mammal (except human) living at highest altitude in the world, and is distributed in the region of Qinghai-Tibet plateau with altitude of more than 3000 m. The Tibetan language of the yak is called Yake, which is generally called 'yak' in the world, namely the Tibetan language translation. The yak is called sound image pig singing, so it is also called pig singing. The western countries are also known as tibetan cattle because they are produced mainly in tibetan regions of the Tibet plateau of China. Yak tail is like cauda equina, so it is also called cauda equina. However, the environment video acquired by the existing yak calf growth environment monitoring system is poor in definition; meanwhile, the number of yaks cannot be accurately calculated.
In summary, the problems of the prior art are as follows: the environment video definition collected by the existing yak calf growth environment monitoring system is poor; meanwhile, the number of yaks cannot be accurately calculated.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a yak calf growth environment monitoring system and a yak calf growth environment monitoring method.
The invention is realized in such a way that a method for monitoring the growth environment of yak calves comprises the following steps:
step one, monitoring the air quality of the growing environment of the yak calf through an air quality monitor:
(a) respectively acquiring indoor air quality parameters and outdoor air quality parameters for yak calf breeding through an indoor air quality sensor and an outdoor air quality sensor;
(b) converting the indoor air quality parameter and the outdoor air quality parameter into digital signals through an analog-to-digital conversion module, and comparing the indoor air quality with the outdoor air quality by using an intelligent comparison program;
(c) according to the comparison result, the window is controlled to be opened and closed through the intelligent window opener, the indoor air quality is monitored in real time through the intelligent adjusting program, and when the indoor air quality is lower than a preset threshold value, the indoor air is purified by opening the air purifier.
Step two, sending the collected data to a main control computer through communication equipment; enhancing the collected video data of the growth environment of the yak calf by a main control machine control video enhancement algorithm:
(I) decoding video coded data to be played received from a server end through an enhancement algorithm to obtain original playing data;
(II) carrying out video image enhancement and rendering processing on the original playing data to obtain terminal playing data; the video image enhancement and rendering processing process comprises the steps of carrying out image enhancement processing on original playing data according to an intensity parameter value Ecur;
(III) after the intensity parameter value Ecur is transmitted to an image enhancement algorithm program in the CPU, the CPU is used for realizing image enhancement processing, and data are played through a display.
Calculating the number of the yak calves according to the collected video data through a calculation program:
(1) acquiring image data of high-resolution yaks when the yaks enter and exit the colony house through camera equipment;
(2) carrying out mean filtering on the image, and adopting a pyramid construction structure;
(3) utilizing pyramid top layer image data as a data source, graying an image, and performing histogram equalization operation;
(4) carrying out convolution filtering on the image by using a sobel gradient operator, and carrying out binarization processing on the image;
(5) performing morphological operation filtering on the image by adopting a 7 × 7 template, performing connected domain marking on the filtered image, and extracting a suspected target area;
(6) extracting the characteristics of the region and establishing a characteristic space; meanwhile, a Bayes classifier based on a minimum error rate criterion is applied by an off-line learning method to divide the yak sample into a positive sample and a negative sample for training;
(7) predicting a shape index, a standard deviation of a regional gray value, a color mean value of the regional gray and a Bayes classifier based on a minimum classification error rate criterion on line to judge whether the yak region is present;
(8) if the yak area is the yak area, performing growth segmentation on the area based on the color characteristics, connecting the fractured yak areas, counting the target area, outputting the current number of the yaks, and returning to the step (1); if not, returning to the step (1) and restarting;
(9) and the region growing algorithm is used for compensating the region growing algorithm in the later stage of identification, so that the counting performance of the algorithm can be effectively improved.
Step four, judging the sanitary growth environment of the yak calf through a judging program; and evaluating the growth health of the yak calf according to the environmental sanitation judgment result through an evaluation program, and generating a health evaluation report.
Further, before the step one, the following steps are required: step I, acquiring growth environment video data of yak calves through a camera;
II, acquiring growth environment temperature data of the yak calf through a temperature sensor;
and III, acquiring growth environment humidity data of the yak calves through a humidity sensor.
After the fourth step, the following steps are required:
step 1, storing the collected growth environment video, temperature, humidity and yak number of yak calves, health judgment results and health evaluation reports through a memory;
step 2, receiving the growth environment monitoring data of the yak calf through the mobile terminal, and remotely controlling the monitoring system;
and 3, displaying the acquired growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the real-time data of the health evaluation report through a display.
Further, in the first step, the intelligent comparison program is used for comparing the received indoor air quality parameter with the outdoor air quality parameter; if the indoor air quality is poor, outputting a windowing signal to the intelligent window opener; if the outdoor air quality is poor, outputting a window closing signal to the intelligent window opener;
the intelligent adjusting program is used for analyzing the received indoor air quality parameters, and when the indoor air quality parameters are lower than a preset threshold value, the intelligent adjusting program outputs signals to control the air purifier to work.
Further, in step two, the intensity parameter value ecru in step (II) refers to a set of parameters, including one or more of a contrast intensity adjustment parameter, a brightness adjustment parameter, a saturation adjustment parameter, a sharpening intensity parameter, and a detail enhancement intensity parameter;
between step (I) and step (II) further comprising:
a, setting a theoretical maximum value Emax of an intensity parameter value and a theoretical minimum value Emin of the intensity parameter value, setting a subjective effective maximum value Smax of the intensity parameter value and a subjective effective minimum value Smin of the intensity parameter value, wherein the Emin is less than or equal to the Smin and is more than or equal to the Smax, and acquiring a screen brightness theoretical maximum value L max of a display and a screen brightness theoretical minimum value L min of the display;
step B, acquiring a current brightness value L cur of the display in real time;
step C, determining an intensity parameter value Ecur according to the current brightness value L cur of the display, and determining the intensity parameter value Ecur according to the following formula:
Figure BDA0002431728780000041
wherein b is an empirical coefficient;
step D, checking the validity of the intensity parameter value Ecur according to Smax and Smin and updating the intensity parameter value Ecur; wherein the content of the first and second substances,
Figure BDA0002431728780000042
further, in step three, in the step (2), in the process of down-sampling the image, a method of applying an average weighted average filter is as follows:
Figure BDA0002431728780000051
wherein n represents the nth layer of the image pyramid; f. ofn(x, y) represents the pixel value at the nth level position x, y of the image pyramid.
Further, in the third step, the probability density function for simulating the characteristics of the yaks and the non-yaks by adopting the normal distribution probability density of the multidimensional random variable in the step (6) is as follows:
Figure BDA0002431728780000052
in the formula, ωiRepresenting yak characteristic class or non-yak characteristic class, i is 0 representing yak class, i is 1 representing non-yak class; p (X | ω)i) Representing conditional probabilities, i.e. at ωiProbability density of occurrence of the feature vector X under class conditions; x represents a feature vector in the feature space, SiRepresented is a covariance matrix of class i;
the logarithmic form of the discriminant function is defined as:
Figure RE-GDA0002542382900000053
further, in the third step, in the step (8), the region is selected as an algorithm for image segmentation, and pixels are gathered into a larger region according to a predefined criterion; starting from a group of growing points, combining the adjacent pixels with similar properties to the growing points with the growing points to form new growing points, and repeating the process until the growing points cannot grow.
Another object of the present invention is to provide a yak calf growth environment monitoring system using the yak calf growth environment monitoring method, the yak calf growth environment monitoring system including:
the environment monitoring system comprises an environment video acquisition module, an environment temperature acquisition module, an environment humidity acquisition module, an air quality monitoring module, a data transmission module, a main control module, a video enhancement module, a yak counting module, an environmental sanitation judgment module, a health evaluation module, a data storage module, a terminal module and a display module.
The environment video acquisition module is connected with the data transmission module and used for acquiring the growth environment video data of the yak calf through the camera;
the environment temperature acquisition module is connected with the data transmission module and used for acquiring growth environment temperature data of the yak calves through the temperature sensor;
the environment humidity acquisition module is connected with the data transmission module and used for acquiring growth environment humidity data of the yak calves through the humidity sensor;
the air quality monitoring module is connected with the data transmission module and used for monitoring the air quality of the growing environment of the yak calf through the air quality monitor;
the data transmission module is connected with the environment video acquisition module, the environment temperature acquisition module, the environment humidity acquisition module, the air quality monitoring module and the main control module and is used for sending acquired data to the main control computer through communication equipment;
the main control module is connected with the data transmission module, the video enhancement module, the yak counting module, the environmental health judgment module, the health evaluation module, the data storage module, the terminal module and the display module and is used for controlling the modules to normally work through the main control computer;
the video enhancement module is connected with the main control module and is used for enhancing the collected video data of the growth environment of the yak calf through a video enhancement algorithm;
the yak calf counting module is connected with the main control module and used for calculating the number of yak calves according to the collected video data through a calculation program;
the environmental sanitation judging module is connected with the main control module and used for judging the growth environmental sanitation of the yak calf through a judging program;
the health evaluation module is connected with the main control module and used for evaluating the growth health of the yak calves according to the environmental sanitation judgment result through an evaluation program and generating a health evaluation report;
the data storage module is connected with the main control module and used for storing the collected growing environment video, temperature, humidity and yak number of yak calves, health judgment results and health evaluation reports through the storage;
the terminal module is connected with the main control module and used for receiving the growth environment monitoring data of the yak calf through the mobile terminal and remotely controlling the monitoring system;
the display module is connected with the main control module and used for displaying the collected growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the real-time data of the health evaluation report through the display.
Another object of the present invention is to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the method for monitoring the growth environment of yak calves when the computer program product is executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to execute the method for monitoring the growth environment of yak calves.
The invention has the advantages and positive effects that: according to the invention, two factors of real-time brightness and image enhancement processing effect of the playing screen are comprehensively considered through the video enhancement module, the brightness of the playing screen is obtained in real time when the user watches the video enhancement module, and the intensity of image enhancement processing is adaptively adjusted in real time according to the brightness value of the playing screen, so that the video definition is greatly improved, and the yak growth environment is more conveniently monitored; meanwhile, after the image video data of the yak group are collected through the yak counting module, the number of the yaks can be effectively and accurately calculated, and compared with the traditional method that after the herdsman is blocked through a fence or manpower, the number of the yaks is manually counted, the yaks belong to original wild type species, and a large amount of manpower resources in a herd area are saved; compared with the traditional method of installing an infrared signal sensor for each cow, the method saves a large amount of equipment cost.
According to the intelligent monitoring and regulating system, an indoor air quality parameter and an outdoor air quality parameter of growth of the yak calf are respectively acquired through an indoor air quality sensor and an outdoor air quality sensor, the indoor air quality parameter and the outdoor air quality parameter are converted into digital signals through an analog-to-digital conversion program, the indoor air quality and the outdoor air quality are compared through an intelligent comparison program, opening and closing of a window are controlled through an intelligent window opener according to a comparison result, the indoor air quality is monitored in real time through an intelligent regulating module, when the indoor air quality is lower than a preset threshold value, the indoor air is purified through opening an air purifier, intelligent monitoring and regulation of the indoor air quality are achieved, the intelligent monitoring and regulating system is convenient and practical, and growth environment conditions of the yak calf are greatly improved.
Drawings
Fig. 1 is a flow chart of a method for monitoring a growth environment of yak calves according to an embodiment of the present invention.
Fig. 2 is a block diagram of a system for monitoring the growth environment of yak calves according to an embodiment of the present invention;
in the figure: 1. an environment video acquisition module; 2. an ambient temperature acquisition module; 3. an ambient humidity acquisition module; 4. an air quality monitoring module; 5. a data transmission module; 6. a main control module; 7. a video enhancement module; 8. a yak counting module; 9. an environmental sanitation determination module; 10. a health evaluation module; 11. a data storage module; 12. a terminal module; 13. and a display module.
Fig. 3 is a flow chart of a method for monitoring the air quality of a growing environment of yak calves through an air quality monitor according to an embodiment of the invention.
Fig. 4 is a flowchart of a method for enhancing collected video data of a growth environment of yak calves by a video enhancement algorithm according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for calculating the number of yak calves according to collected video data through a calculation program according to an embodiment of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for monitoring the growth environment of yak calves provided by the embodiment of the invention comprises the following steps:
s101, acquiring growth environment video data of yak calves through a camera; the temperature sensor is used for collecting the temperature data of the growing environment of the yak calf.
S102, acquiring growth environment humidity data of yak calves through a humidity sensor; the air quality of the growing environment of the yak calf is monitored through an air quality monitor.
S103, sending the collected data to a main control computer through communication equipment; the normal work of a yak calf growth environment monitoring system is controlled through a main control machine.
S104, enhancing the collected video data of the growing environment of the yak calf through a video enhancement algorithm; and calculating the number of the yak calves according to the collected video data through a calculation program.
S105, judging the sanitary growth environment of the yak calf through a judging program; and evaluating the growth health of the yak calf according to the environmental sanitation judgment result through an evaluation program, and generating a health evaluation report.
And S106, storing the collected growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the health evaluation report through a memory.
S107, receiving the growth environment monitoring data of the yak calf through the mobile terminal, and remotely controlling the monitoring system; and displaying the acquired growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the real-time data of the health evaluation report through a display.
As shown in fig. 2, the system for monitoring the growth environment of yak calves provided by the embodiment of the present invention includes: the system comprises an environment video acquisition module 1, an environment temperature acquisition module 2, an environment humidity acquisition module 3, an air quality monitoring module 4, a data transmission module 5, a main control module 6, a video enhancement module 7, a yak counting module 8, an environmental sanitation judgment module 9, a health evaluation module 10, a data storage module 11, a terminal module 12 and a display module 13.
The environment video acquisition module 1 is connected with the data transmission module 5 and is used for acquiring the growth environment video data of the yak calf through the camera;
the environment temperature acquisition module 2 is connected with the data transmission module 5 and is used for acquiring growth environment temperature data of yak calves through a temperature sensor;
the environment humidity acquisition module 3 is connected with the data transmission module 5 and is used for acquiring growth environment humidity data of yak calves through a humidity sensor;
the air quality monitoring module 4 is connected with the data transmission module 5 and is used for monitoring the air quality of the growing environment of the yak calf through an air quality monitor;
the data transmission module 5 is connected with the environment video acquisition module 1, the environment temperature acquisition module 2, the environment humidity acquisition module 3, the air quality monitoring module 4 and the main control module 6 and is used for sending acquired data to the main control computer through communication equipment;
the main control module 6 is connected with the data transmission module 5, the video enhancement module 7, the yak counting module 8, the environmental sanitation judgment module 9, the health evaluation module 10, the data storage module 11, the terminal module 12 and the display module 13 and is used for controlling each module to normally work through the main control computer;
the video enhancement module 7 is connected with the main control module 6 and is used for enhancing the collected video data of the growth environment of the yak calf through a video enhancement algorithm;
the yak calf counting module 8 is connected with the main control module 6 and used for calculating the number of yak calves according to the collected video data through a calculation program;
the environmental sanitation judging module 9 is connected with the main control module 6 and used for judging the growth environmental sanitation of the yak calf through a judging program;
the health evaluation module 10 is connected with the main control module 6 and used for evaluating the growth health of the yak calves according to the environmental health judgment result through an evaluation program and generating a health evaluation report;
the data storage module 11 is connected with the main control module 6 and used for storing the collected growing environment video, temperature, humidity and yak number of yak calves, health judgment results and health evaluation reports through a memory;
the terminal module 12 is connected with the main control module 6 and used for receiving the growth environment monitoring data of the yak calf through the mobile terminal and remotely controlling the monitoring system;
and the display module 13 is connected with the main control module 6 and used for displaying the acquired growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the real-time data of the health evaluation report through a display.
The invention is further described with reference to specific examples.
Example 1
The method for monitoring the growth environment of the yak calf provided by the embodiment of the invention is shown in figure 1, as a preferred embodiment, as shown in figure 3, the method for monitoring the air quality of the growth environment of the yak calf through the air quality monitor provided by the embodiment of the invention comprises the following steps:
s201, collecting indoor air quality parameters and outdoor air quality parameters of yak calf breeding respectively through an indoor air quality sensor and an outdoor air quality sensor.
S202, converting the indoor air quality parameter and the outdoor air quality parameter into digital signals through an analog-to-digital conversion module, and comparing the indoor air quality with the outdoor air quality by using an intelligent comparison program.
S203, controlling the opening and closing of the window through the intelligent window opener according to the comparison result, monitoring the indoor air quality in real time by using an intelligent adjusting program, and purifying the indoor air by opening the air purifier when the indoor air quality is lower than a preset threshold value.
The intelligent comparison program provided by the embodiment of the invention is used for comparing the received indoor air quality parameter with the outdoor air quality parameter; if the indoor air quality is poor, outputting a windowing signal to the intelligent windowing device; if the outdoor air quality is poor, outputting a window closing signal to the intelligent window opener; and the intelligent adjusting program is used for analyzing the received indoor air quality parameters, and outputting a signal to control the air purifier to work when the indoor air quality parameters are lower than a preset threshold value.
Example 2
The method for monitoring the growth environment of the yak calf provided by the embodiment of the invention is shown in fig. 1 and fig. 4, and as a preferred embodiment, the method for enhancing the collected video data of the growth environment of the yak calf by a video enhancement algorithm comprises the following steps:
s301, decoding video coded data to be played received from a server end through an enhancement algorithm to obtain original playing data.
S302, video image enhancement and rendering processing are carried out on the original playing data to obtain terminal playing data; the video image enhancement and rendering processing process comprises the step of carrying out image enhancement processing on the original playing data according to the intensity parameter value Ecur.
S303, after the intensity parameter value Ecur is transmitted to an image enhancement algorithm program in the CPU, the CPU is used for realizing image enhancement processing, and data is played through a display.
The intensity parameter value ecru of step S302 provided in the embodiment of the present invention refers to a set of parameters, which includes one or more of a contrast intensity adjustment parameter, a brightness adjustment parameter, a saturation adjustment parameter, a sharpening intensity parameter, and a detail enhancement intensity parameter;
between step (I) and step (II) further comprising:
a, setting a theoretical maximum value Emax of an intensity parameter value and a theoretical minimum value Emin of the intensity parameter value, setting a subjective effective maximum value Smax of the intensity parameter value and a subjective effective minimum value Smin of the intensity parameter value, wherein the Emin is less than or equal to the Smin and is more than or equal to the Smax, and acquiring a screen brightness theoretical maximum value L max of a display and a screen brightness theoretical minimum value L min of the display;
step B, acquiring a current brightness value L cur of the display in real time;
step C, determining an intensity parameter value Ecur according to the current brightness value L cur of the display, and determining the intensity parameter value Ecur according to the following formula:
Figure BDA0002431728780000121
wherein b is an empirical coefficient;
step D, checking the validity of the intensity parameter value Ecur according to Smax and Smin and updating the intensity parameter value Ecur; wherein the content of the first and second substances,
Figure BDA0002431728780000122
example 3
The method for monitoring the growth environment of yak calves, provided by the embodiment of the invention, is shown in fig. 1 and fig. 5, and as a preferred embodiment, the method for calculating the number of yak calves according to collected video data through a calculation program, provided by the embodiment of the invention, comprises the following steps:
s401, image data of high-resolution yaks entering and exiting the colony house are obtained through the camera.
S402, performing mean filtering on the image, and adopting a pyramid construction structure.
And S403, graying the image by using the pyramid top image data as a data source, and performing histogram equalization operation.
S404, performing convolution filtering on the image by using a sobel gradient operator, and performing binarization processing on the image.
S405, performing morphological operation filtering on the image by adopting a 7 × 7 template, performing connected domain marking on the filtered image, and extracting a suspected target area.
S406, extracting the characteristics of the region and establishing a characteristic space; and meanwhile, by an off-line learning method, a Bayes classifier based on a minimum error rate criterion is applied to divide the yak sample into a positive sample and a negative sample for training.
S407, predicting the shape index, the standard deviation of the gray values of the region, the color mean value of the gray values of the region and a Bayes classifier based on the minimum classification error rate criterion on line, and judging whether the yak region is the yak region.
S408, if the yak area is the yak area, performing growth segmentation on the area based on the color characteristics, connecting the fractured yak areas, counting the target area, outputting the current number of the yaks, and returning to S401 again; if not, the process returns to S401 to restart.
And S409, compensating the identified later stage by using a region growing algorithm, so that the counting performance of the algorithm can be effectively improved.
The probability density function for simulating the characteristics of the yak and the non-yak by adopting the normal distribution probability density of the multidimensional random variable provided by the embodiment of the invention is as follows:
Figure BDA0002431728780000131
in the formula, ωiRepresenting yak characteristic class or non-yak characteristic class, i is 0 representing yak class, i is 1 representing non-yak class; p (X | ω)i) Representing conditional probabilities, i.e. at ωiProbability density of occurrence of the feature vector X under class conditions; x represents a feature vector in the feature space, SiRepresented is a covariance matrix of class i;
the logarithmic form of the discriminant function is defined as:
Figure RE-GDA0002542382900000132
the method for selecting the regioncut as the image segmentation algorithm provided by the embodiment of the invention has the advantages that the pixels are gathered into a larger area according to a predefined criterion; starting from a group of growing points, adjacent pixels with similar properties to the growing points are combined with the growing points to form new growing points, and the process is repeated until the growing points cannot grow.
In the process of down-sampling the image, the embodiment of the invention adopts an average weighted average filter:
Figure BDA0002431728780000133
wherein n represents the nth layer of the image pyramid; f. ofn(x, y) represents the pixel value at the nth level position x, y of the image pyramid.
The computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g., from one website site, computer, server, or data center to another website site, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DS L), or wireless (e.g., infrared, wireless, microwave, etc.) manner).
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed in the present invention should be covered within the scope of the present invention.

Claims (10)

1. A method for monitoring the growth environment of yak calves is characterized by comprising the following steps:
step one, monitoring the air quality of the growing environment of the yak calf through an air quality monitor:
(a) respectively acquiring indoor air quality parameters and outdoor air quality parameters of yak calf culture through an indoor air quality sensor and an outdoor air quality sensor;
(b) converting the indoor air quality parameter and the outdoor air quality parameter into digital signals through an analog-to-digital conversion module, and comparing the indoor air quality with the outdoor air quality by using an intelligent comparison program;
(c) controlling the opening and closing of the window through an intelligent window opener according to the comparison result, monitoring the indoor air quality in real time by using an intelligent adjusting program, and purifying the indoor air by opening an air purifier when the indoor air quality is lower than a preset threshold value;
step two, sending the collected data to a main control computer through communication equipment; the video enhancement algorithm is controlled by the main control computer to enhance the video data of the growth environment of the collected yak calf:
(I) decoding video coded data to be played received from a server end through an enhancement algorithm to obtain original playing data;
(II) carrying out video image enhancement and rendering processing on the original playing data to obtain terminal playing data; the video image enhancement and rendering processing process comprises the steps of carrying out image enhancement processing on original playing data according to an intensity parameter value Ecur;
(III) after the intensity parameter value Ecur is transmitted to an image enhancement algorithm program in the CPU, the CPU is used for realizing image enhancement processing, and data are played through a display;
calculating the number of the yak calves according to the collected video data through a calculation program:
(1) acquiring image data of high-resolution yaks when the yaks enter and exit the colony house through camera equipment;
(2) carrying out mean filtering on the image, and adopting a pyramid construction structure;
(3) utilizing pyramid top layer image data as a data source, graying an image, and performing histogram equalization operation;
(4) carrying out convolution filtering on the image by using a sobel gradient operator, and carrying out binarization processing on the image;
(5) performing morphological operation filtering on the image by adopting a 7 × 7 template, performing connected domain marking on the filtered image, and extracting a suspected target area;
(6) extracting the characteristics of the region and establishing a characteristic space; meanwhile, a Bayes classifier based on a minimum error rate criterion is applied by an off-line learning method to divide the yak sample into a positive sample and a negative sample for training;
(7) predicting a shape index, a standard deviation of a regional gray value, a color mean value of the regional gray and a Bayes classifier based on a minimum classification error rate criterion on line to judge whether the yak region is present;
(8) if the yak area is the yak area, performing growth segmentation on the area based on the color characteristics, connecting the fractured yak areas, counting the target area, outputting the current number of the yaks, and returning to the step (1); if not, returning to the step (1) and restarting;
(9) compensating the identified later stage by using a region growing algorithm;
step four, judging the sanitary growth environment of the yak calf through a judging program; and evaluating the growth health of the yak calf according to the environmental sanitation judgment result through an evaluation program, and generating a health evaluation report.
2. The method for monitoring the growth environment of yak calf according to claim 1, wherein the first step is preceded by the steps of: step I, acquiring growth environment video data of yak calves through a camera;
II, acquiring growth environment temperature data of the yak calf through a temperature sensor;
step III, acquiring growth environment humidity data of yak calves through a humidity sensor;
after the fourth step, the following steps are required:
step 1, storing the collected growing environment video, temperature, humidity and yak number of yak calves, health judgment results and health evaluation reports through a memory;
step 2, receiving the growth environment monitoring data of the yak calf through the mobile terminal, and remotely controlling the monitoring system;
and 3, displaying the acquired growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the real-time data of the health evaluation report through a display.
3. The method for monitoring the growth environment of yak calves as claimed in claim 1, wherein in step one, the intelligent comparison program is used for comparing the received indoor air quality parameter with the outdoor air quality parameter; if the indoor air quality is poor, outputting a windowing signal to the intelligent window opener; if the outdoor air quality is poor, outputting a window closing signal to the intelligent window opener;
the intelligent adjusting program is used for analyzing the received indoor air quality parameters, and when the indoor air quality parameters are lower than a preset threshold value, the intelligent adjusting program outputs signals to control the air purifier to work.
4. The method for monitoring the growth environment of yak calf as claimed in claim 1, wherein in step two, the intensity parameter value ecru of step (II) refers to a set of parameters comprising one or more of contrast intensity adjustment parameter, brightness adjustment parameter, saturation adjustment parameter, sharpening intensity parameter, detail enhancement intensity parameter;
between step (I) and step (II) further comprising:
a, setting a theoretical maximum value Emax of an intensity parameter value and a theoretical minimum value Emin of the intensity parameter value, setting a subjective effective maximum value Smax of the intensity parameter value and a subjective effective minimum value Smin of the intensity parameter value, wherein the Emin is less than or equal to the Smin and is more than or equal to the Smax and less than or equal to the Emax, and obtaining a screen brightness theoretical maximum value L max of a display and a screen brightness theoretical minimum value L min of the display;
step B, acquiring a current brightness value L cur of the display in real time;
step C, determining an intensity parameter value Ecur according to the current brightness value L cur of the display, and determining the intensity parameter value Ecur according to the following formula:
Figure FDA0002431728770000031
wherein b is an empirical coefficient;
step D, checking the validity of the intensity parameter value Ecur according to Smax and Smin and updating the intensity parameter value Ecur; wherein the content of the first and second substances,
Figure FDA0002431728770000041
5. the method for monitoring the growth environment of yak calf as claimed in claim 1, wherein in step three, the method of using the average weighted mean filter in the down-sampling of the image in step (2) is as follows:
Figure FDA0002431728770000042
wherein n represents the nth layer of the image pyramid; f. ofn(x, y) represents the pixel value at the nth level position x, y of the image pyramid.
6. The method for monitoring the growth environment of yak calf as claimed in claim 1, wherein in step three, the probability density function of simulating yak and non-yak features by using the normal distribution probability density of multidimensional random variables in the step (6) is as follows:
Figure RE-FDA0002542382890000043
in the formula, ωiRepresenting yak characteristic class or non-yak characteristic class, i is 0 representing yak class, i is 1 representing non-yak class; p (X | ω)i) Representing conditional probabilities, i.e. at ωiProbability density of occurrence of the feature vector X under class conditions; x represents a feature vector in the feature space, SiRepresented is a covariance matrix of class i;
the logarithmic form of the discriminant function is defined as:
Figure RE-FDA0002542382890000044
7. the method for monitoring the growth environment of yak calf as claimed in claim 1, wherein in step three, the process of selecting regioncut as the algorithm of image segmentation in the step (8) and aggregating pixels into a larger area according to a predefined criterion; starting from a group of growing points, combining the adjacent pixels with similar properties to the growing points with the growing points to form new growing points, and repeating the process until the growing points cannot grow.
8. A yak calf growth environment monitoring system applying the yak calf growth environment monitoring method according to any one of claims 1-7, wherein the yak calf growth environment monitoring system comprises:
the environment video acquisition module is connected with the data transmission module and used for acquiring the growth environment video data of the yak calf through the camera;
the environment temperature acquisition module is connected with the data transmission module and used for acquiring growth environment temperature data of the yak calves through the temperature sensor;
the environment humidity acquisition module is connected with the data transmission module and used for acquiring growth environment humidity data of the yak calves through the humidity sensor;
the air quality monitoring module is connected with the data transmission module and used for monitoring the air quality of the growing environment of the yak calf through the air quality monitor;
the data transmission module is connected with the environment video acquisition module, the environment temperature acquisition module, the environment humidity acquisition module, the air quality monitoring module and the main control module and is used for sending acquired data to the main control computer through communication equipment;
the main control module is connected with the data transmission module, the video enhancement module, the yak counting module, the environmental sanitation judgment module, the health evaluation module, the data storage module, the terminal module and the display module and is used for controlling the modules to normally work through the main control computer;
the video enhancement module is connected with the main control module and is used for enhancing the collected video data of the growth environment of the yak calf through a video enhancement algorithm;
the yak calf counting module is connected with the main control module and used for calculating the number of yak calves according to the collected video data through a calculation program;
the environmental sanitation judging module is connected with the main control module and used for judging the growth environmental sanitation of the yak calf through a judging program;
the health evaluation module is connected with the main control module and used for evaluating the growth health of the yak calf according to the environmental sanitation judgment result through an evaluation program and generating a health evaluation report;
the data storage module is connected with the main control module and used for storing the collected growing environment video, temperature, humidity and yak number of yak calves, health judgment results and health evaluation reports through the storage;
the terminal module is connected with the main control module and used for receiving the growth environment monitoring data of the yak calf through the mobile terminal and remotely controlling the monitoring system;
the display module is connected with the main control module and used for displaying the collected growth environment video, temperature, humidity and yak number of the yak calves, the health judgment result and the real-time data of the health evaluation report through the display.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the method for monitoring the growth environment of yak calves as claimed in any one of claims 1 to 7 when executed on an electronic device.
10. A computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to perform the method for monitoring the growth environment of yak calves as claimed in any one of claims 1 to 7.
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