Breeding duck breeding-oriented breeding environment intelligent monitoring method and system

Abstract

The invention relates to the field of breeding duck breeding monitoring, in particular to a breeding environment intelligent monitoring method and system for breeding duck breeding. According to the system, firstly, concentration data of different gases at different monitoring points of a breeding duck farm and temperature data, humidity data and noise intensity of the monitoring points are obtained in real time; according to the temperature data and the humidity data of the monitoring points at the current moment, the distribution of the noise intensity of each monitoring point at the current moment and the distribution of the noise intensity of the monitoring points in the reference time period, the duck group activity density of each monitoring point at the current moment is obtained, and the airflow intensity and the airflow direction of each monitoring point at the current moment are analyzed; and in combination with the concentration data of various gases at each monitoring point at the current moment, an environmental pollution accumulation coefficient at the current moment is obtained, and real-time early warning is carried out on the environment of the breeding duck farm. According to the invention, the local accumulation phenomenon of harmful gas in the breeding duck farm can be effectively monitored, and the accuracy of breeding duck breeding environment monitoring is improved.

Description

Technical Field

[0001] The present invention relates to the field of duck breeding monitoring, and specifically to an intelligent monitoring method and system for breeding environment for breeding ducks. Background Art

[0002] With the rapid development of modern livestock and poultry breeding industry, as an important variety in poultry breeding, the production performance and reproductive efficiency of breeding ducks are directly related to the benefit level of the downstream meat duck and egg duck industrial chains. Environmental factors (such as temperature, humidity, ammonia concentration, light intensity, carbon dioxide concentration, noise level, etc.) have significant effects on the growth and development, egg production rate, fertilization rate and survival rate of breeding ducks. With the rapid development of Internet of Things technology, it provides the possibility to realize intelligent, precise and automatic monitoring of breeding environment.

[0003] In winter or during the brooding period of ducklings, the breeding house needs to reduce ventilation to maintain temperature, but in this case, the discharge efficiency of harmful gases (such as ) will be reduced. Under the action of the internal air circulation system, the ventilation system may form internal eddies, resulting in uneven gas distribution. However, the current monitoring and alarm thresholds are mostly based on acute poisoning standards and the average concentration of harmful gases, and cannot effectively monitor the local accumulation phenomenon of harmful gases in duck breeding farms, thus reducing the accuracy of monitoring the breeding environment of breeding ducks. Summary of the Invention

[0004] In order to solve the technical problem that the current monitoring and alarm thresholds are mostly based on acute poisoning standards and the average concentration of harmful gases, and cannot effectively monitor the local accumulation phenomenon of harmful gases in duck breeding farms, thus reducing the accuracy of monitoring the breeding environment of breeding ducks, the purpose of the present invention is to provide an intelligent monitoring method and system for breeding environment for breeding ducks, and the specific technical solutions adopted are as follows: The present invention proposes an intelligent monitoring method for breeding environment for breeding ducks, and the method includes: Obtain in real time the concentration data of different gases at different monitoring points in a duck breeding farm at each moment within a preset time period, as well as the temperature data, humidity data and noise intensity data of the monitoring points at each moment; Divide a preset time period into multiple monitoring phases, take the monitoring phase where the current moment is located as the current monitoring phase, and take the time period before the current moment in the current monitoring phase as the reference period of the current moment. Obtain the phase progress coefficient of the current moment according to the length difference between the reference period and the current monitoring phase; take any monitoring point as the target monitoring point, and obtain the duck flock activity density of the target monitoring point at the current moment according to the differences in temperature data and humidity data between the target monitoring point at the current moment and the previous adjacent moment, the distribution of noise intensity data of all monitoring points at the current moment, and the distribution of the differences in noise intensity data of adjacent moments in the reference period of the target monitoring point. According to the position distribution of each monitoring point in the farm, the change differences in the concentration data of the same gas at each moment in the reference period between the target monitoring point and other monitoring points, and the phase progress coefficient and the duck flock activity density, obtain the air flow intensity and air flow direction of the target monitoring point at the current moment; according to the air flow intensity and air flow direction of each monitoring point at the current moment, and the concentration data of various gases of each monitoring point at the current moment, obtain the environmental pollution accumulation coefficient at the current moment. Based on the environmental pollution accumulation coefficient, conduct real-time early warning on the environment of the breeding duck farm.

[0005] Further, the obtaining of the phase progress coefficient of the current moment includes: Take the length of the reference period at the current time point as the numerator, take the length of the current monitoring phase as the denominator, and take the ratio as the phase progress coefficient of the current moment.

[0006] Further, the obtaining of the duck flock activity density of the target monitoring point at the current moment includes: According to the differences in temperature data and humidity data between the target monitoring point at the current moment and the previous adjacent moment, and the temperature data and humidity data of the target monitoring point at the current moment, obtain the first duck flock aggregation degree of the target monitoring point at the current moment; Fit the noise intensity data of all moments in the reference period of the target monitoring point to obtain the noise intensity fitting curve of the target monitoring point in the reference period. Analyze the discreteness of the absolute values of the slopes of all adjacent two moments on the noise intensity fitting curve to obtain the noise change chaos degree of the target monitoring point in the reference period. Take the product value of the noise change chaos degree of the target monitoring point in the reference period and the noise intensity data of the target monitoring point at the current moment as the second duck flock aggregation degree of the target monitoring point at the current moment; After analyzing the discreteness of the noise intensity data of all monitoring points at the current moment and performing normalization processing, obtain the noise distribution concentration degree at the current moment; Based on the calculation formula of the duck flock activity density, obtain the duck flock activity density at the current moment of the target monitoring point. The calculation formula of the duck flock activity density is as follows: where, represents the duck flock activity density at the current moment of the target monitoring point; represents the first duck flock aggregation degree at the current moment of the target monitoring point; represents the second duck flock aggregation degree at the current moment of the target monitoring point; represents the noise distribution concentration degree at the current moment.

[0007] Furthermore, the obtaining of the first duck flock aggregation degree at the current moment of the target monitoring point includes: Take the difference between the temperature data of the target monitoring point between the current moment and the adjacent previous moment as the temperature change amount of the target monitoring point at the current moment, and synthesize the temperature data of the target monitoring point at the current moment and the temperature change amount to obtain the temperature characteristic value of the target monitoring point at the current moment; Take the difference between the humidity data of the target monitoring point between the current moment and the adjacent previous moment as the humidity change amount of the target monitoring point at the current moment, and synthesize the humidity data of the target monitoring point at the current moment and the humidity change amount to obtain the humidity characteristic value of the target monitoring point at the current moment; Take the average value of the temperature characteristic value and the humidity characteristic value as the first duck flock aggregation degree at the current moment of the target monitoring point.

[0008] Furthermore, the obtaining of the air flow intensity and air flow direction at the current moment of the target monitoring point includes: Take the area of the breeding duck farm as the numerator, the number of monitoring points as the denominator, and the ratio as the unit coverage area value; with the target monitoring point as the center, take the circular area with an area of the unit coverage area value as the adjacent area of the target monitoring point; in the adjacent area, select the adjacent monitoring points of the target monitoring point from other monitoring points except the target monitoring point, where there is no monitoring point on the line connecting the adjacent monitoring point and the target monitoring point; Take any adjacent monitoring point of the target monitoring point as the target adjacent monitoring point, use the dynamic time warping algorithm to match the concentration data of the same gas at each moment in the reference period between the target monitoring point and the target adjacent monitoring point, and take the difference between each moment of each gas of the target monitoring point in the reference period and the moment of the same gas of the target adjacent monitoring point matched at this moment as the time difference of each gas of the target monitoring point in each moment of the reference period with respect to the target adjacent monitoring point; According to the time differences of each gas at the target monitoring point with respect to each adjacent monitoring point at each moment during the reference period, screen out the gas flow monitoring points of the target monitoring point at the current moment from all adjacent monitoring points, and take the direction from the target monitoring point to the gas flow monitoring point as the air flow direction of the target monitoring point at the current moment; According to the change in the concentration data of each gas at the target monitoring point at each moment during the reference period, the time differences of each gas at the target monitoring point with respect to the gas flow monitoring point at each moment during the reference period, the distance between the target monitoring point and the gas flow monitoring point, and the stage progress coefficient and the duck flock activity density of the target monitoring point at the current moment, obtain the air flow intensity of the target monitoring point at the current moment.

[0009] Further, the gas flow monitoring points of the target monitoring point at the current moment include: Take the average value of the time differences of each gas at the target monitoring point with respect to each adjacent monitoring point at all moments during the reference period as the overall time difference of each gas at the target monitoring point with respect to each adjacent monitoring point during the reference period; Screen out the candidate monitoring points of the target monitoring point from all adjacent monitoring points of the target monitoring point, where the overall time differences of various gases at the target monitoring point with respect to the candidate monitoring points during the reference period are all negative; Take the average value of the absolute values of the differences between the time differences of each gas at the target monitoring point between all adjacent two moments with respect to each candidate monitoring point during the reference period to obtain the initial screening value of each gas at the target monitoring point with respect to each candidate monitoring point during the reference period, and take the average value of the initial screening values of all gases at the target monitoring point with respect to each candidate monitoring point during the reference period as the final screening value of the target monitoring point with respect to each candidate monitoring point during the reference period; Take the candidate monitoring point corresponding to the minimum value of the final screening value as the gas flow monitoring point of the target monitoring point at the current moment.

[0010] Further, the obtaining of the air flow intensity of the target monitoring point at the current moment includes: Perform curve fitting on the concentration data of each gas at the target monitoring point at each moment during the reference period to obtain the concentration fitting curve of each gas at the target monitoring point; Take the average value of the absolute values of the slopes of the concentration fitting curves of all gases at the target monitoring point at the current moment as the overall gas concentration change degree of the target monitoring point at the current moment; Take the distance between the target monitoring point and the gas flow monitoring point as the numerator, and take the average value of the time differences of all gases at the target monitoring point with respect to the gas flow monitoring point at all moments during the reference period as the denominator, and take the ratio as the air flow speed parameter of the target monitoring point at the current moment. Integrate the overall gas concentration change degree and the air flow velocity parameter to obtain the air flow coefficient of the target monitoring point at the current moment; Based on the calculation formula of air flow intensity, obtain the air flow intensity of the target monitoring point at the current moment, and the calculation formula of the air flow intensity is: Wherein, represents the air flow intensity of the target monitoring point at the current moment; represents the stage progress coefficient of the target monitoring point at the current moment; represents the duck flock activity density of the target monitoring point at the current moment; represents the air flow coefficient of the target monitoring point at the current moment.

[0011] Furthermore, the obtaining of the environmental pollution accumulation coefficient at the current moment includes: Take the average value of the concentration data of all kinds of gases at the target monitoring point at the current moment as the overall gas concentration level of the target monitoring point at the current moment; Take the included angle between the air flow direction and the horizontal direction of the target monitoring point at the current moment as the air flow angle of the target monitoring point at the current moment, take the average value of the air flow angles of all monitoring points at the current moment as the overall air flow angle at the current moment, and take the absolute value of the difference between the air flow angle of the target monitoring point at the current moment and the overall air flow angle as the air flow direction deviation degree of the target monitoring point at the current moment; After integrating and performing negative correlation mapping on the air flow direction deviation degree and the air flow intensity of the target monitoring point at the current moment, obtain the air flow retention degree of the target monitoring point at the current moment; Integrate the overall gas concentration level and the air flow retention degree of the target monitoring point at the current moment to obtain the air flow aggregation degree of the target monitoring point at the current moment; Normalize the average value of the air flow aggregation degrees of all monitoring points at the current moment to obtain the environmental pollution accumulation coefficient at the current moment.

[0012] Furthermore, the real-time monitoring of the environment of the breeding duck farm includes: If the environmental pollution accumulation coefficient at the current moment is greater than the preset pollution threshold, then send out an environmental pollution alarm message.

[0013] The present invention also proposes an intelligent monitoring system for the breeding environment for breeding ducks, the system includes a memory, a processor, and a computer program stored in the memory and operable on the processor, and when the processor executes the computer program, it implements the steps of any one of the intelligent monitoring methods for the breeding environment for breeding ducks.

[0014] The present invention has the following beneficial effects: The present invention provides an intelligent monitoring method and system for the breeding environment of breeding ducks. By deploying a variety of high-precision sensors in the breeding environment of breeding ducks, continuously collecting data on the breeding environment of breeding ducks, segmenting a preset time period according to key breeding events to obtain several monitoring stages, and determining the stage progress index at the current moment. According to the change situation of the sensor data at each monitoring point, analyze the duck flock activity density at the position of each monitoring point at the current moment, and combine the data change characteristics of each monitoring point to evaluate the air flow characteristics of the breeding house at the position of each monitoring point, including the air flow direction and air flow intensity. Combine the air flow characteristics of each monitoring point to analyze the environmental pollution accumulation coefficient of the breeding farm, which is used to reflect the severity of the harmful gas accumulation phenomenon in the internal environment of the breeding duck farm. Furthermore, based on the environmental pollution accumulation index, the environment of the breeding duck farm is monitored in real time, so as to effectively monitor the local accumulation phenomenon of harmful gases in the breeding duck farm. This method analyzes the data change characteristics between monitoring points, improves the perception ability of the breeding environment monitoring system to the local accumulation situation of harmful gases in the breeding duck farm, and improves the accuracy of monitoring the breeding environment of breeding ducks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of an intelligent monitoring method for the breeding environment of breeding ducks provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the position distribution of each monitoring point in a breeding duck farm provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in combination with the accompanying drawings and preferred embodiments, elaborate in detail on a method and system for intelligent monitoring of the breeding environment of breeding ducks proposed according to the present invention, its specific implementation manner, structure, characteristics and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs.

[0019] The following specifically describes the specific solutions of a method and system for intelligent monitoring of the breeding environment for breeding ducks provided by the present invention in conjunction with the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of a method for intelligent monitoring of the breeding environment for breeding ducks provided by an embodiment of the present invention. The method includes: Step S1: Real-time obtain the concentration data of different gases at different monitoring points in the breeding duck farm at each moment within a preset time period, as well as the temperature data, humidity data, and noise intensity data at each monitoring point at each moment.

[0021] In order to achieve intelligent monitoring of the breeding environment for breeding ducks, it is necessary to collect various data of the breeding environment for breeding ducks. During the breeding process of breeding ducks, the breeding ducks are very sensitive to changes in the breeding environment. A suitable and stable environment is the key to ensuring the health of breeding ducks, improving reproductive performance (such as egg production rate, fertilization rate, hatching rate, etc.), and reducing the death and culling rate.

[0022] In intensive breeding, due to factors such as seasonal changes, ventilation systems, feeding densities, and manure treatment, the concentrations of pollutants such as , , and dust generated by the metabolism of the duck flock are prone to exceed the standard. Breeding ducks are relatively sensitive to environmental abnormalities (such as sudden drops in temperature and increases in ammonia concentration), which can easily lead to a decrease in egg production rate, a decrease in fertilization rate, an increase in the incidence of diseases, etc. Therefore, in the embodiments of the present invention, multiple monitoring points are first deployed in the breeding duck farm. Among them, it should be ensured that at least 2 groups of monitoring points are arranged within every 100 square meters to ensure no dead corners in environmental monitoring. More monitoring points are deployed at the air inlet, air outlet, manure area, intensive duck activity area, and central axis area. Please refer to Figure 2 , which shows a schematic diagram of the position distribution of each monitoring point in a breeding duck farm provided by an embodiment of the present invention.

[0023] Then, various sensors are installed at each monitoring point position to real-time collect the concentration data of different gases at each monitoring point at each moment within a preset time period, as well as the temperature data, humidity data, and noise intensity data at each monitoring point at each moment. Among them, the gases collected in the embodiments of the present invention are harmful gases in the breeding farm, such as carbon dioxide, ammonia, and hydrogen sulfide, etc. In an embodiment of the present invention, the preset time period is set to 1 day. The specific value of the preset time period can also be set by the implementer according to the specific implementation scenario and is not limited herein.

[0024] It should be noted that since the dimensions of each data are different, in order to facilitate the calculation and analysis of subsequent steps, it is necessary to standardize the various collected data to eliminate the influence of dimensions. Among them, data standardization is a technical means well-known to those skilled in the art and will not be elaborated here.

[0025] Step S2: Divide the preset time period into multiple monitoring phases, take the monitoring phase where the current moment is located as the current monitoring phase, and take the time period before the current moment in the current monitoring phase as the reference period for the current moment. Obtain the stage progress coefficient of the current moment according to the length difference between the reference period and the current monitoring phase; Take any monitoring point as the target monitoring point, and obtain the duck flock activity density of the target monitoring point at the current moment based on the differences in temperature data and humidity data between the target monitoring point at the current moment and the adjacent previous moment, the distribution of noise intensity data of all monitoring points at the current moment, and the distribution of the change differences in noise intensity data of the target monitoring point at adjacent moments in the reference period.

[0026] In the environment of a breeding duck house, when the ventilation system is operating, harmful gases are discharged outside the house with the air flow. When the air exchange between the inside and outside of the breeding house is reduced for the purpose of keeping warm or other reasons, the harmful gases form a circulating flow inside the house, resulting in continuous fluctuations in the harmful gas values detected by the monitoring equipment. However, due to the internal air circulation effect, the concentration never exceeds the set threshold. Although the alarm is not triggered, the continuous accumulation and dynamic fluctuations of harmful gases in this state still pose a potential threat to the safety of the breeding duck house environment and the health of breeding ducks. Therefore, it is necessary to analyze the local accumulation characteristics of current harmful gases in combination with the change characteristics of the sensor monitoring data of the current breeding duck house.

[0027] In the embodiments of the present invention, the preset time period is first segmented by the key breeding events in the current breeding house. The key events specifically refer to the events that may affect the activities of the duck flock and thus cause a decrease in air quality. Among them, the digestive system of breeding ducks operates relatively fast. The chyme starts to defecate about 2 hours after entering the intestine and is basically digested and emptied within 4 hours. Especially after concentrated feeding, it will enter the peak period of defecation. Therefore, the time point when each feeding starts can be used as the segmentation point of the preset time point. In addition, after the lights are turned off at night, the activities of the duck flock gradually decrease, enter the rest state, the water intake decreases, and the metabolic and digestion speeds decrease. Usually, relatively formed feces are discharged after waking up in the morning. Therefore, the time points when the lights are turned off and on in the breeding farm can be used as the segmentation points of the preset time point. In addition, in addition to the intensive defecation time of breeding ducks, cleaning the breeding house is also one of the important factors affecting the environment of the breeding house. The main factor affecting the air quality of the breeding house for breeding ducks is the feces of breeding ducks. Therefore, the time point of each cleaning of the breeding house should also be used as the segmentation point of the detected data. Therefore, the above selected segmentation points can be used to segment the preset time period. The time period between two adjacent segmentation points can be considered as a monitoring stage. By segmenting the preset time period, the accuracy and pertinence of environmental monitoring can be improved.

[0028] In the case where the air exchange inside and outside the breeding farm is relatively small, in order to accurately evaluate the current air pollution situation, one cannot rely solely on instantaneous readings. Since harmful gases tend to accumulate, the current situation is the result of the combined action of pollutant generation, accumulation, and limited removal over a past period of time. The change trend of the environmental parameters in the breeding house over a past period of time should be combined for comprehensive analysis. Therefore, the monitoring stage where the current moment is located can be used as the current monitoring stage, and the time period before the current moment in the current monitoring stage can be used as the reference period for the current moment. It should be noted that in order to ensure that there is enough data in the reference period for subsequent analysis, the current moment should not be too close to the starting moment of the current monitoring stage. For example, in an embodiment of the present invention, the analysis can start from the 10th moment of the current monitoring stage, which is not limited herein.

[0029] Since the change characteristics of various data collected by the sensor are different within the monitoring stages corresponding to different key breeding events. For example, in the monitoring stage corresponding to feeding, due to the accelerated breathing and excrement caused by eating, the carbon dioxide concentration first increases, and then the concentrations of ammonia and hydrogen sulfide gradually increase. Therefore, in the embodiments of the present invention, first, according to the length difference between the reference period and the current monitoring stage, the stage progress coefficient of the current moment is obtained, and the time progress of the current moment in the monitoring stage where it is located is evaluated through the stage progress coefficient. The larger the stage progress coefficient, the more complete the change characteristics of the monitoring stage data that the current moment can reflect.

[0030] Preferably, in an embodiment of the present invention, the method for obtaining the stage progress coefficient at the current moment specifically includes: Taking the length of the reference period at the current time point as the numerator and the length of the current monitoring stage as the denominator, and using the ratio as the stage progress coefficient at the current moment.

[0031] The harmful gases in the breeding duck farm are mainly affected by the activities of the duck flock. When analyzing the local accumulation characteristics of harmful gases, it is first necessary to analyze the activity density of the duck flock in the breeding duck farm over a past period of time. The activity density of the duck flock, that is, the degree of aggregation of the duck flock, has a close and mutually influential relationship with the monitoring data of the local environment. Specifically, it can be manifested as: in the densely populated areas of the duck flock, due to the release of body heat and the evaporation of excrement, the local temperature and humidity may also rise.

[0032] In addition, when evaluating the activity density of the duck flock at each time point of the monitoring node, it is also necessary to analyze in combination with the noise level: when the activity degree of the duck flock is relatively large, the data of the temperature and humidity sensors at a certain moment may not have had time to change yet. Therefore, it is also necessary to analyze through the data of the noise sensors. Usually, the noise level in the local area where the duck flock is located is relatively high. However, in some monitoring stages, such as when the cleaning equipment or feeding equipment is running, there are also situations where the noise level in the local area is relatively high. And when the activity degree of the duck flock is relatively large, the sounds made by the duck flock, such as crowing sounds and footsteps, usually have more complex fluctuation characteristics compared with the sounds of machine equipment. Then, the evaluation accuracy of the activity density of the duck flock can be further improved by monitoring the changes in the noise at the monitoring points. Therefore, first, any one monitoring point is used as the target monitoring point, and the distribution of the temperature data and humidity data of the target monitoring point at the current moment, the distribution of the noise intensity data of all monitoring points at the current moment, and the distribution of the differences in the noise intensity data of the target monitoring point at adjacent moments in the reference period are analyzed. The activity density of the duck flock obtained is used to reflect the degree of aggregation of the duck flock when it is active at the position of the target monitoring point at the current moment.

[0033] Preferably, in an embodiment of the present invention, the method for obtaining the activity density of the duck flock at the target monitoring point at the current moment specifically includes: First, according to the differences in temperature data and humidity data between the target monitoring point at the current moment and the adjacent previous moment, and the temperature data and humidity data of the target monitoring point at the current moment, the first duck flock aggregation degree of the target monitoring point at the current moment is obtained.

[0034] Preferably, in an embodiment of the present invention, the method for obtaining the first duck flock aggregation degree of the target monitoring point at the current moment specifically includes: The difference in temperature data of the target monitoring point between the current moment and the adjacent previous moment is used as the temperature change amount of the target monitoring point at the current moment. The temperature data and the temperature change amount of the target monitoring point at the current moment are combined to obtain the temperature characteristic value of the target monitoring point at the current moment. The larger the temperature characteristic value, the more it indicates that the temperature of the target monitoring point is rising and relatively high at the current moment, and further indicates that there is a greater possibility of duck flock aggregation at the target monitoring point at the current moment.

[0035] In an embodiment of the present invention, the sum value or product value of the temperature data and the temperature change amount of the target monitoring point at the current moment can be used as the temperature characteristic value of the target monitoring point at the current moment to achieve the combination of the two. There is no limitation here, and the subsequent steps of comprehensively processing two or more data can also be implemented using the same method, and no further elaboration will be made.

[0036] Similarly, the difference in humidity data of the target monitoring point between the current moment and the adjacent previous moment is used as the humidity change amount of the target monitoring point at the current moment. The humidity data and the humidity change amount of the target monitoring point at the current moment are combined to obtain the humidity characteristic value of the target monitoring point at the current moment.

[0037] The average value of the temperature characteristic value and the humidity characteristic value is used as the first duck flock aggregation degree of the target monitoring point at the current moment.

[0038] Then, the noise intensity data of all moments in the reference period of the target monitoring point are fitted to obtain the noise intensity fitting curve of the target monitoring point in the reference period. The dispersion degree of the absolute values of the slopes of all adjacent two moments on the noise intensity fitting curve is analyzed to obtain the noise change chaos degree of the target monitoring point in the reference period. The greater the noise change chaos degree, the stronger the fluctuation of the noise in the reference period, and further indicates that the noise characteristics in the reference period are more likely to be generated by duck flocks rather than by equipment. Therefore, the product value of the noise change chaos degree of the target monitoring point in the reference period and the noise intensity data of the target monitoring point at the current moment can be used as the second duck flock aggregation degree of the target monitoring point at the current moment.

[0039] In an embodiment of the present invention, the variance or standard deviation of the absolute values of the slopes of all adjacent two moments on the noise intensity fitting curve can be used as the noise change chaos degree of the target monitoring point in the reference period to achieve the analysis of the dispersion degree of the absolute values of the slopes of all adjacent two moments on the noise intensity fitting curve. And the subsequent steps of analyzing the dispersion degree of data can also be implemented using the same method, and no further elaboration will be made.

[0040] After analyzing the dispersion degree of the noise intensity data of all monitoring points at the current moment and performing normalization processing, the calculation result is limited to within a range to obtain the concentration of the noise distribution at the current moment.

[0041] In an embodiment of the present invention, an activation function and a hyperbolic tangent function can be used to implement the normalization process, and the same method can also be used in subsequent steps to implement the normalization process, without further elaboration.

[0042] Based on the calculation formula of the duck flock activity density, obtain the duck flock activity density at the current moment of the target monitoring point. The calculation formula of the duck flock activity density is: where represents the duck flock activity density at the current moment of the target monitoring point; represents the first duck flock aggregation degree at the current moment of the target monitoring point; represents the second duck flock aggregation degree at the current moment of the target monitoring point; represents the concentration of the noise distribution at the current moment.

[0043] where, the greater the concentration of the noise distribution at the current moment the more concentrated the activity of the duck flock is in a certain area at this time, and at this time the second duck flock aggregation degree can better reflect the duck flock activity density at the current moment of the target monitoring point. The smaller the concentration of the noise distribution at the current moment the more dispersed the activity of the duck flock is at this time, and at this time the first duck flock aggregation degree can better reflect the duck flock activity density at the current moment of the target monitoring point.

[0044] So far, the analysis of the aggregation degree of the duck flock activity at the position of the target monitoring point at the current moment is completed.

[0045] Step S3: According to the position distribution of each monitoring point in the farm, the change difference of the concentration data of the same gas at each moment in the reference period between the target monitoring point and other monitoring points, as well as the stage progress coefficient and the duck flock activity density, obtain the air flow intensity and air flow direction at the current moment of the target monitoring point; according to the air flow intensity and air flow direction at the current moment of each monitoring point, and the concentration data of various gases at each monitoring point at the current moment, obtain the environmental pollution accumulation coefficient at the current moment.

[0046] Since the harmful gases in the breeding duck farm are usually in a flowing state, it is also necessary to analyze the air flow direction and intensity at the monitoring point. Among them, the air flow direction and intensity can be comprehensively inferred through data characteristics such as the change trend of gas concentration captured by the monitoring point network. Its essence is to track the air flow path and diffusion direction. When synchronously collecting data at multiple monitoring points in the farm, the air flow direction and intensity can be analyzed through the time sequence and change rate of the monitoring data changes at different monitoring points. At the same time, when the stage progress coefficient at the current moment is smaller, it indicates that the environmental data at the current monitoring stage is still in a changing period, that is, the change of gas concentration data may be affected by the progress of the current monitoring stage. And the environmental data change reflected by the monitoring stage progress is mainly caused by the activities of the duck flock. Therefore, the higher the density of duck flock activities at the current node, the greater the degree to which the analysis of air flow intensity is affected by the progress of the current monitoring stage. Therefore, based on the position distribution of each monitoring point in the farm, the change difference of the concentration data of the same gas at each moment in the reference period between the target monitoring point and other monitoring points, and combined with the stage progress coefficient and the duck flock activity density, the air flow intensity and air flow direction of the target monitoring point at the current moment can be obtained.

[0047] Preferably, in an embodiment of the present invention, the method for obtaining the air flow intensity and air flow direction of the target monitoring point at the current moment specifically includes: When gas flows into or out of the target monitoring point, there will be a certain change delay feature in the concentration data of the same gas between the target monitoring point and other adjacent monitoring points in terms of spatial position. This feature can reflect the air flow direction of the target monitoring point.

[0048] Therefore, first, use the area of the breeding duck farm as the numerator and the number of monitoring points as the denominator, and take the ratio as the unit coverage area value; with the target monitoring point as the center, take a circular area with an area of the unit coverage area value as the adjacent area of the target monitoring point; in the adjacent area, select the adjacent monitoring points of the target monitoring point from other monitoring points except the target monitoring point. Among them, there is no monitoring point on the line connecting the adjacent monitoring point and the target monitoring point.

[0049] Take any adjacent monitoring point of the target monitoring point as the target adjacent monitoring point, use the dynamic time warping algorithm to match the concentration data of the same gas at each moment in the reference period between the target monitoring point and the target adjacent monitoring point, and take the difference between each moment of each gas at the target monitoring point in the reference period and the moment of the same gas at the target adjacent monitoring point matched at this moment as the time difference of each gas at the target monitoring point in each moment of the reference period with respect to the target adjacent monitoring point.

[0050] Generally, the above method can obtain the time difference of each gas at the target monitoring point with respect to each adjacent monitoring point at each moment during the reference period.

[0051] Then, based on the time difference of each gas at the target monitoring point with respect to each adjacent monitoring point at each moment during the reference period, the gas flow monitoring points of the target monitoring point at the current moment are screened out from all adjacent monitoring points. The gas flow monitoring point is the monitoring point towards which the air current of the target monitoring point flows at the current moment. Therefore, the direction from the target monitoring point to the gas flow monitoring point can be used as the air current direction of the target monitoring point at the current moment.

[0052] Preferably, in an embodiment of the present invention, the method for obtaining the gas flow monitoring point of the target monitoring point at the current moment specifically includes: Taking the average value of the time differences of each gas at the target monitoring point with respect to each adjacent monitoring point at all moments during the reference period as the overall time difference of each gas at the target monitoring point with respect to each adjacent monitoring point during the reference period, and screening out the candidate monitoring points of the target monitoring point from all adjacent monitoring points of the target monitoring point. Among them, if the overall time differences of various gases at the target monitoring point with respect to the candidate monitoring points during the reference period are all negative, it means that the concentration changes of various gases at the candidate monitoring points during the reference period occur after the target monitoring point.

[0053] Taking the average value of the absolute values of the differences between the time differences of each adjacent two moments of each gas at the target monitoring point with respect to each candidate monitoring point during the reference period to obtain the initial screening value of each gas at the target monitoring point with respect to each candidate monitoring point during the reference period. Taking the average value of the initial screening values of all gases at the target monitoring point with respect to each candidate monitoring point during the reference period as the final screening value of the target monitoring point with respect to each candidate monitoring point during the reference period. Furthermore, taking the candidate monitoring point corresponding to the minimum value of the final screening value as the gas flow monitoring point of the target monitoring point at the current moment.

[0054] The air current intensity can be analyzed through the distance between the gas flow monitoring point and the target monitoring node and the time delay of the gas monitoring data change between the two. At the same time, since the actual gas flow direction may not be exactly the same as the obtained air current direction, it is also necessary to analyze the air current intensity in combination with the change rate of the gas concentration data of the target monitoring point itself.

[0055] Therefore, based on the concentration data changes of each gas at the target monitoring point at each moment during the reference period, the time difference of each gas at the target monitoring point with respect to the gas flow monitoring point at each moment during the reference period, the distance between the target monitoring point and the gas flow monitoring point, and in combination with the stage progress coefficient and the duck flock activity density of the target monitoring point at the current moment, the air current intensity of the target monitoring point at the current moment can be obtained.

[0056] Preferably, in an embodiment of the present invention, the method for obtaining the air flow intensity at the target monitoring point at the current moment specifically includes: Perform curve fitting on the concentration data of each gas at each moment in the reference period at the target monitoring point to obtain the concentration fitting curve of each gas at the target monitoring point. Take the average value of the absolute values of the slopes of the concentration fitting curves of all gases at the target monitoring point at the current moment as the overall gas concentration change degree at the target monitoring point at the current moment. The greater the overall gas concentration change degree, the stronger the air flow at the target monitoring point at the current moment.

[0057] Use the distance between the target monitoring point and the gas flow monitoring point as the numerator, and use the average value of the time differences of all gases at the target monitoring point with respect to the gas flow monitoring point at all moments in the reference period as the denominator. Take the ratio as the air flow velocity parameter at the target monitoring point at the current moment. The greater the air flow velocity parameter, the stronger the air flow at the target monitoring point at the current moment.

[0058] Integrate the overall gas concentration change degree and the air flow velocity parameter to obtain the air flow coefficient at the target monitoring point at the current moment.

[0059] Based on the calculation formula of the air flow intensity, obtain the air flow intensity at the target monitoring point at the current moment. The calculation formula of the air flow intensity is: Wherein, represents the air flow intensity at the target monitoring point at the current moment; represents the stage progress coefficient at the target monitoring point at the current moment; represents the duck flock activity density at the target monitoring point at the current moment; represents the air flow coefficient at the target monitoring point at the current moment.

[0060] By using the above same method, the air flow intensity and air flow direction at each monitoring point at the current moment can be obtained. The greater the concentration data of various gases at each monitoring point at the current moment, the smaller the air flow intensity at each monitoring point at the current moment, and the more consistent the air flow direction at each monitoring point at the current moment with the overall direction of the air flow direction, the more likely there is a local accumulation phenomenon of harmful gases in the breeding duck farm at the current moment. Therefore, the air flow intensity and air flow direction at each monitoring point at the current moment, as well as the concentration data of various gases at each monitoring point at the current moment, can be analyzed, and the severity of the harmful gas accumulation phenomenon in the internal environment of the breeding duck farm can be reflected through the obtained environmental pollution accumulation coefficient.

[0061] Preferably, in an embodiment of the present invention, the method for obtaining the environmental pollution accumulation coefficient at the current moment specifically includes: The average value of the concentration data of all kinds of gases at the target monitoring point at the current moment is used as the overall gas concentration level of the target monitoring point at the current moment.

[0062] The included angle between the air flow direction and the horizontal direction at the target monitoring point at the current moment is used as the air flow angle of the target monitoring point at the current moment, where the value range of the air flow angle is , the average value of the air flow angles of all monitoring points at the current moment is used as the overall air flow angle at the current moment, and the absolute value of the difference between the air flow angle of the target monitoring point at the current moment and the overall air flow angle is used as the air flow direction deviation degree of the target monitoring point at the current moment.

[0063] After comprehensively considering the air flow direction deviation degree and air flow intensity of the target monitoring point at the current moment and performing a negative correlation mapping, the air flow retention degree of the target monitoring point at the current moment is obtained. The greater the air flow retention degree, the more likely it is that there are harmful gases at the position of the target monitoring point at the current moment.

[0064] By comprehensively considering the overall gas concentration level and air flow retention degree of the target monitoring point at the current moment, the air flow aggregation degree of the target monitoring point at the current moment is obtained. The greater the air flow aggregation degree, the more likely it is that there is a harmful gas accumulation phenomenon at the position of the target monitoring point at the current moment.

[0065] As an example, in an embodiment of the present invention, the expression of the air flow aggregation degree of the target monitoring point at the current moment can be specifically, for example: Wherein, represents the air flow aggregation degree of the target monitoring point at the current moment; represents the th kind of gas concentration data of the target monitoring point at the current moment; represents the number of gas types; represents the overall gas concentration level of the target monitoring point at the current moment; represents the air flow angle of the target monitoring point at the current moment; represents the overall air flow angle at the current moment; represents the air flow direction deviation degree of the target monitoring point at the current moment; represents the air flow intensity of the target monitoring point at the current moment; represents the air flow retention degree of the target monitoring point at the current moment; represents a preset adjustment parameter for preventing the denominator from being 0, The value range of , in an embodiment of the present invention, is set to 0.01, The specific value can also be set by the implementer according to the specific implementation scenario and is not limited here.

[0066] It should be noted that in other embodiments of the present invention, negative correlation mapping can also be achieved through other basic mathematical operations, which will not be elaborated here.

[0067] By the same method as above, the airflow aggregation degree of each monitoring point at the current moment can be obtained.

[0068] Furthermore, the average value of the airflow aggregation degrees of all monitoring points at the current moment can be normalized, and the calculation result is limited to within the range, so as to obtain the environmental pollution accumulation coefficient at the current moment.

[0069] As an example, in an embodiment of the present invention, the expression of the environmental pollution accumulation coefficient at the current moment can be specifically, for example: Among them, represents the environmental pollution accumulation coefficient at the current moment; represents the th airflow aggregation degree of the monitoring point at the current moment; represents the number of monitoring points; represents the hyperbolic tangent function, which is used for normalization processing.

[0070] So far, the analysis of the harmful gas accumulation phenomenon in the breeding duck farm has been completed.

[0071] Step S4: Based on the environmental pollution accumulation coefficient, perform real-time warning on the environment of the breeding duck farm.

[0072] The larger the environmental pollution accumulation coefficient at the current moment, the more likely there is a harmful gas accumulation phenomenon in the breeding duck farm and the more serious the accumulation phenomenon is. Therefore, based on the environmental pollution accumulation coefficient, the environment of the breeding duck farm can be monitored in real time, so as to effectively monitor the local accumulation phenomenon of harmful gases in the breeding duck farm and improve the accuracy of monitoring the breeding duck farm environment.

[0073] Preferably, in an embodiment of the present invention, the method for real-time monitoring of the environment of the breeding duck farm specifically includes: If the environmental pollution accumulation coefficient at the current moment is greater than the preset pollution threshold, an environmental pollution alarm message is sent. Among them, the value range of the preset pollution threshold is , in an embodiment of the present invention, the preset pollution threshold is set to 0.75, and the specific value of the preset pollution threshold can also be set by the implementer according to the specific implementation scenario and is not limited here.

[0074] An embodiment of the present invention provides an intelligent monitoring system for the breeding environment of breeding ducks, which includes a memory, a processor, and a computer program. The memory is used to store the corresponding computer program, the processor is used to run the corresponding computer program, and when the computer program runs in the processor, it can implement the methods described in steps S1 to S4.

[0075] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the advantages or disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0076] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. An intelligent monitoring method for the breeding environment of breeding ducks, characterized in that The method includes: Obtaining in real time the concentration data of different gases at different monitoring points in a duck breeding farm within a preset time period at each moment, as well as the temperature data, humidity data, and noise intensity data of the monitoring points at each moment; Dividing the preset time period into multiple monitoring stages, taking the monitoring stage where the current moment is located as the current monitoring stage, and taking the time period before the current moment in the current monitoring stage as the reference period of the current moment. Obtaining the stage progress coefficient of the current moment according to the length difference between the reference period and the current monitoring stage; taking any one of the monitoring points as the target monitoring point, and obtaining the duck flock activity density of the target monitoring point at the current moment according to the difference in temperature data and humidity data between the target monitoring point at the current moment and the adjacent previous moment, the distribution of the noise intensity data of all monitoring points at the current moment, and the distribution of the change difference in the noise intensity data of the adjacent moments in the reference period of the target monitoring point; Obtaining the air flow intensity and air flow direction of the target monitoring point at the current moment according to the position distribution of each monitoring point in the breeding farm, the change difference in the concentration data of the same gas at each moment in the reference period between the target monitoring point and other monitoring points, as well as the stage progress coefficient and the duck flock activity density; obtaining the environmental pollution accumulation coefficient at the current moment according to the air flow intensity and air flow direction of each monitoring point at the current moment, and the concentration data of various gases of each monitoring point at the current moment; Based on the environmental pollution accumulation coefficient, performing real-time early warning on the environment of the duck breeding farm.

2. The intelligent monitoring method for breeding environment for breeding ducks according to claim 1, wherein, The obtaining of the stage progress coefficient of the current moment includes: Taking the length of the reference period of the current time point as the numerator and the length of the current monitoring stage as the denominator, and taking the ratio as the stage progress coefficient of the current moment.

3. The intelligent monitoring method for breeding environment for breeding ducks according to claim 1, characterized in that The obtaining of the duck flock activity density of the target monitoring point at the current moment includes: Obtaining the first duck flock aggregation degree of the target monitoring point at the current moment according to the difference in temperature data and humidity data between the target monitoring point at the current moment and the adjacent previous moment, and the temperature data and humidity data of the target monitoring point at the current moment; Fitting the noise intensity data of all moments in the reference period of the target monitoring point to obtain the noise intensity fitting curve of the target monitoring point in the reference period, analyzing the dispersion degree of the absolute values of the slopes of all adjacent two moments on the noise intensity fitting curve, obtaining the noise change chaos degree of the target monitoring point in the reference period, and taking the product value of the noise change chaos degree of the target monitoring point in the reference period and the noise intensity data of the target monitoring point at the current moment as the second duck flock aggregation degree of the target monitoring point at the current moment; Analyzing the dispersion degree of the noise intensity data of all monitoring points at the current moment and performing normalization processing to obtain the noise distribution concentration degree at the current moment; Based on the calculation formula of the duck flock activity density, obtaining the duck flock activity density of the target monitoring point at the current moment, and the calculation formula of the duck flock activity density is: Among them, represents the duck flock activity density at the target monitoring point at the current moment; represents the first duck flock aggregation degree at the target monitoring point at the current moment; represents the second duck flock aggregation degree at the target monitoring point at the current moment; represents the noise distribution concentration degree at the current moment.

4. The intelligent monitoring method for breeding environment for breeding ducks according to claim 3, wherein The obtaining of the first duck flock aggregation degree of the target monitoring point at the current moment includes: Take the difference between the temperature data of the target monitoring point between the current moment and the adjacent previous moment as the temperature change amount of the target monitoring point at the current moment, and synthesize the temperature data of the target monitoring point at the current moment and the temperature change amount to obtain the temperature characteristic value of the target monitoring point at the current moment; Take the difference between the humidity data of the target monitoring point between the current moment and the adjacent previous moment as the humidity change amount of the target monitoring point at the current moment, and synthesize the humidity data of the target monitoring point at the current moment and the humidity change amount to obtain the humidity characteristic value of the target monitoring point at the current moment; Take the average value of the temperature characteristic value and the humidity characteristic value as the first duck flock aggregation degree of the target monitoring point at the current moment.

5. The intelligent monitoring method for breeding environment for breeding ducks according to claim 1, characterized in that The obtaining of the air flow intensity and air flow direction of the target monitoring point at the current moment includes: Take the area of the breeding duck farm as the numerator and the number of monitoring points as the denominator, and take the ratio as the unit coverage area value; with the target monitoring point as the center, take the circular area with an area of the unit coverage area value as the adjacent area of the target monitoring point; in the adjacent area, select the adjacent monitoring points of the target monitoring point from other monitoring points except the target monitoring point, where there is no monitoring point on the line connecting the adjacent monitoring point and the target monitoring point; Take any adjacent monitoring point of the target monitoring point as the target adjacent monitoring point, use the dynamic time warping algorithm to match the concentration data of the same gas at each moment in the reference period between the target monitoring point and the target adjacent monitoring point, and take the difference between each moment of each gas of the target monitoring point in the reference period and the moment of this gas of the target adjacent monitoring point matched at this moment as the time difference of each gas of the target monitoring point at each moment in the reference period with respect to the target adjacent monitoring point; According to the time difference of each gas of the target monitoring point at each moment in the reference period with respect to each adjacent monitoring point, screen out the gas flow monitoring point of the target monitoring point at the current moment from all adjacent monitoring points, and take the direction from the target monitoring point to the gas flow monitoring point as the air flow direction of the target monitoring point at the current moment; According to the change of the concentration data of each gas of the target monitoring point at each moment in the reference period, the time difference of each gas of the target monitoring point at each moment in the reference period with respect to the gas flow monitoring point, the distance between the target monitoring point and the gas flow monitoring point, and the stage progress coefficient and the duck flock activity density of the target monitoring point at the current moment, obtain the air flow intensity of the target monitoring point at the current moment.

6. The intelligent monitoring method for breeding environment for breeding ducks according to claim 5, characterized in that, The gas flow monitoring point of the target monitoring point at the current moment includes: Take the average value of the time differences of each gas of the target monitoring point at all moments in the reference period with respect to each adjacent monitoring point as the overall time difference of each gas of the target monitoring point in the reference period with respect to each adjacent monitoring point; Screen out the candidate monitoring points of the target monitoring point from all adjacent monitoring points of the target monitoring point, where the overall time differences of various gases of the target monitoring point in the reference period with respect to the candidate monitoring points are all negative; For each gas at the target monitoring point, calculate the average of the absolute values of the differences between the time differences of all adjacent two moments in the reference period with respect to each candidate monitoring point, to obtain the initial screening value of each gas at the target monitoring point in the reference period with respect to each candidate monitoring point. Take the average of the initial screening values of all gases at the target monitoring point in the reference period with respect to each candidate monitoring point as the final screening value of the target monitoring point in the reference period with respect to each candidate monitoring point; Take the candidate monitoring point corresponding to the minimum value of the final screening value as the gas flow monitoring point of the target monitoring point at the current moment.

7. The intelligent monitoring method for breeding environment for breeding ducks according to claim 5, characterized in that, The obtaining of the air flow intensity of the target monitoring point at the current moment includes: Perform curve fitting on the concentration data of each gas at the target monitoring point at each moment in the reference period to obtain the concentration fitting curve of each gas at the target monitoring point; Take the average of the absolute values of the slopes of the concentration fitting curves of all gases at the target monitoring point at the current moment as the overall gas concentration change degree of the target monitoring point at the current moment; Use the distance between the target monitoring point and the gas flow monitoring point as the numerator, and the average of the time differences of all gases at the target monitoring point at all moments in the reference period with respect to the gas flow monitoring point as the denominator, and take the ratio as the air flow velocity parameter of the target monitoring point at the current moment; Integrate the overall gas concentration change degree and the air flow velocity parameter to obtain the air flow coefficient of the target monitoring point at the current moment; Based on the calculation formula of the air flow intensity, obtain the air flow intensity of the target monitoring point at the current moment. The calculation formula of the air flow intensity is: Among them, represents the air flow intensity of the target monitoring point at the current moment; represents the stage progress coefficient of the target monitoring point at the current moment; represents the duck flock activity density of the target monitoring point at the current moment; represents the air flow coefficient of the target monitoring point at the current moment.

8. The intelligent monitoring method for breeding environment for breeding ducks according to claim 1, characterized in that, The obtaining of the environmental pollution accumulation coefficient at the current moment includes: Take the average of the concentration data of all gases at the target monitoring point at the current moment as the overall gas concentration level of the target monitoring point at the current moment; Take the angle between the air flow direction and the horizontal direction of the target monitoring point at the current moment as the air flow angle of the target monitoring point at the current moment. Take the average of the air flow angles of all monitoring points at the current moment as the overall air flow angle at the current moment. Take the absolute value of the difference between the air flow angle of the target monitoring point at the current moment and the overall air flow angle as the air flow direction deviation degree of the target monitoring point at the current moment; After integrating and performing negative correlation mapping on the air flow direction deviation degree and the air flow intensity of the target monitoring point at the current moment, obtain the air flow retention degree of the target monitoring point at the current moment; Integrate the overall gas concentration level and the air flow retention degree of the target monitoring point at the current moment to obtain the air flow aggregation degree of the target monitoring point at the current moment; Normalize the average of the air flow aggregation degrees of all monitoring points at the current moment to obtain the environmental pollution accumulation coefficient at the current moment.

9. The intelligent monitoring method for breeding environment for breeding ducks according to claim 1, characterized in that, The real-time monitoring of the environment of the breeding duck farm includes: If the environmental pollution accumulation coefficient at the current moment is greater than the preset pollution threshold, then send out an environmental pollution alarm message.

10. An intelligent monitoring system for the breeding environment of breeding ducks, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it realizes the steps of the method according to any one of claims 1 to 9.

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