A multi-channel walk-in flat poultry growth performance measurement system and method

Abstract

The present invention discloses a multi-channel walk-in flat poultry growth performance measurement system and method, belonging to the field of poultry farming. The method adopts a walk-in multi-channel structure of a growth performance measurement device based on behavioral characteristics to adapt to poultry farming groups of different scales, realizing flexible expansion and deployment. Through a signal calibration and matching strategy, the RFID signals of different channels are accurately matched with the data of strain sensors to ensure that the signals between different channels do not interfere with each other, achieving error-free individual information identification. Using RFID technology to record the activity frequency and residence time of poultry in different areas, analyzing their activity distribution rules, providing data support for further behavioral research and health status, providing a large amount of effective data support for the screening of excellent poultry, and realizing unmanned automatic monitoring of the farm, improving the production efficiency of the poultry farm, reducing the stress of the poultry group caused by manual operation, and ensuring the standardization and reliability of data collection.

Description

Technical Field

[0001] The present invention relates to the field of poultry farming, and particularly to a multi-channel walk-in flat poultry growth performance measurement system and method. Background Art

[0002] Currently, the poultry farming modes are mainly divided into two modes: cage farming and flat farming. Among them, compared with the cage farming mode, animals in the flat farming mode will not have excessive stress, and it is more in line with the standards of animal welfare. Among them, the individual growth performance of flat poultry is an important physiological parameter monitored during the breeding process. By real-time monitoring of the individual growth performance of a large group of flat poultry, the growth status and welfare of poultry can be reflected, and at the same time, poultry individuals with abnormal weights can be detected and removed in time.

[0003] Currently, the weighing method used by farms to measure the live weight of poultry is mainly the traditional manual static weighing. Although the accuracy of the live weight measured by the manual weighing method is relatively accurate, when weighing a large group of poultry, the operation is difficult, and it takes a lot of manpower and time to measure the weight of each poultry one by one; in addition, the time span measured by this method is relatively large, and it is difficult to achieve real-time monitoring of the poultry group; and during manual weighing, it is easy to cause stress to the poultry and reduce the production efficiency of the poultry.

[0004] To solve the above problems, currently, some researchers have used different technologies to obtain the live weight of animals without stressing them. The prior art uses 3D vision technology to estimate the weight of pigs. After using an RGBD camera to collect images of pigs and entering 3D point cloud modeling to obtain their three-dimensional models, the weight of pigs is obtained by combining a weight estimation model. Although this method saves time and effort and does not cause stress, it is difficult to perform three-dimensional modeling on small individual poultry, and due to the presence of feathers and other situations, it is difficult to achieve accurate weight estimation of poultry. The perch-type device invented by using the perching habit of poultry automatically measures the weight of poultry when they perch on the pole. However, for the poultry group that is willing to perch, it still belongs to some individuals, and it is difficult to measure other poultry in the large group. In addition, waterfowl such as geese do not have this habit, and it is also difficult to measure the live weight through this device. Summary of the Invention

[0005] In view of the above deficiencies in the prior art, the present invention provides a multi-channel walk-in flat poultry growth performance measurement method.

[0006] To achieve the above invention purpose, the technical solution adopted by the present invention is as follows:

[0007] A multi-channel walk-in flat poultry growth performance measurement system, including a control and processing module, a position information module, a behavior analysis module, a weight calculation module, and a result storage module, wherein:

[0008] The position information module transmits the poultry position information to the control processing module unidirectionally. After data processing, the control processing module obtains the poultry position information. Then, the control processing module sends an instruction to activate the weight calculation module, collects the dynamic weight of the poultry passing through the channel, calculates the true weight of the poultry, and returns it to the control processing module. The control processing module obtains the behavior type of the poultry through the behavior analysis module for the collected information, and finally analyzes the predicted weight of the poultry based on the obtained dynamic weight and the behavior characteristics of the poultry, and inputs the data into the result storage module to save the data.

[0009] A method for a multi-channel walk-through free-range poultry growth performance measurement system includes the following steps:

[0010] S1. Build a multi-channel walk-through free-range poultry growth performance measurement device, including a ramp, an RFID reader, a channel platform, a bottom resistive strain sensor, channel railings, an RFID reader, a system host, a multi-functional weighing and force measuring instrument, a system display screen, a console-type operation housing platform, and channel baffles;

[0011] S2. When the poultry steps onto the channel platform, activate the weight calculation module. At this time, the resistive strain sensor at the bottom of the channel platform starts to work, continuously reads the weight information of the poultry, and when the weight returns below the threshold, the weight reading work for this time is completed;

[0012] S3. Calculate the true weight of the poultry from the collected weight information;

[0013] S4. Calculate the distribution position of the poultry based on the read poultry identity information.

[0014] Further, the specific steps of S3 include the following:

[0015] S31. Calculate the expected value of the overall dynamic weight data based on the continuously read weight information of the poultry obtained in S2;

[0016] S32. Judge whether the dynamic weight is balanced according to the expected value calculated in S31. If it is not balanced, filter out the abnormally fluctuating weight values through the median filtering algorithm;

[0017] S33. Perform mean filtering on the weight values after median filtering to reduce the overall dynamic weight fluctuation;

[0018] S34. Based on the processing result of S33, input the processed data into the weight calculation module for weight calculation and output the weight calculation result;

[0019] S35. Divide the weight calculation result output in S34 into multiple groups of data slices, and calculate the slope, intercept, and root mean square error of each group;

[0020] S36. Repeat steps S31 - S35 until there is no next set of data, then complete the body weight calculation and output the optimal predicted body weight as the true body weight of the poultry.

[0021] Further, the calculation method of the expected value in S32 is as follows:

[0022]

[0023] Where: E represents the expected value of the dynamic body weight curve; n represents the number of body weights collected; w i represents the true body weight value.

[0024] Further, the specific method of median filtering in S32 is as follows:

[0025]

[0026] Where: i represents the time, represents the predicted body weight value, w i represents the true body weight value; m represents the window size of median filtering, and median() represents calculating the median of a set of data.

[0027] Further, the specific calculation formula of mean filtering in S33 is:

[0028]

[0029] Where: i represents the time, represents the predicted body weight value; k represents the position of the body weight data within the filtering window; w k represents the body weight value before mean filtering; m is the window size of mean filtering.

[0030] Further, the specific calculation formula of root mean square error in S35 is:

[0031]

[0032] Where, i represents the time, represents the predicted body weight value w i represents the true body weight value; M represents the number of samples for calculating the root mean square error.

[0033] Further, S4 specifically includes the following steps:

[0034] S41. After the poultry passes through the channel, transmit the information collected by the RFID reader - writer to the location information module; sort it according to the chronological order of collection;

[0035] S42. After preprocessing the data, compare the RFID antenna numbers of the signals read before and after the poultry passes through the channel to determine whether the poultry has passed through the channel;

[0036] S43. According to the RFID antenna numbers before and after reading the identity information, determine the entry and exit directions of the poultry. Based on the current position of the RFID antenna where the poultry is read and the entry and exit directions, determine the current position information of the poultry;

[0037] S44. By comparing the relevant data such as time, weight, and reading position collected in different time periods, obtain the distribution position law of the poultry.

[0038] The present invention has the following beneficial effects:

[0039] (1) Design a detachable modular walk-in multi-channel design, which can adapt to poultry groups of different scales and has good flexibility and scalability;

[0040] (2) Realize unmanned automated 24-hour real-time monitoring, reduce manual intervention, save a large amount of labor and time costs, and at the same time reduce the stress of poultry caused by manual operations;

[0041] (3) By combining low-cost chips with RFID antennas, while greatly saving costs, the identity and position information of poultry can be accurately read;

[0042] (4) Conduct big data statistics on individual poultry, and can automatically collect multi-dimensional data including individual growth performance, behavioral characteristics, position distribution, etc., realize comprehensive information collection, and provide accurate and reliable data support;

[0043] (5) The data system platform can analyze various data collected in real time and quickly feedback abnormal situations, which helps to make management decisions in a timely manner and improve the efficiency of breeding management. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a three-dimensional schematic diagram of the complete structure of the present invention.

[0045] Figure 2 is a three-dimensional schematic diagram of the complete channel of the present invention.

[0046] Figure 3 is a device control logic diagram of the present invention.

[0047] Figure 4 is a device implementation flowchart of the present invention.

[0048] Figure 5 is a weight calculation flowchart of the present invention.

[0049] Figure 6It is the flow chart for analyzing the position of poultry in the present invention. Detailed implementation manners

[0050] The following describes the detailed implementation manners of the present invention to facilitate those skilled in the art of this technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the detailed implementation manners. For those of ordinary skill in the art of this technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions made using the concept of the present invention are within the scope of protection.

[0051] As Figure 1 - Figure 2 shown, it is the schematic diagram of the specific structure of the device of the present invention. In the figure, the device consists of a ramp 1, an RFID reader 2, a channel platform 3, a bottom resistive strain sensor 4 (the installation position is shown in the figure, located on the back of the bottom of the channel platform), a channel railing 5, an RFID reader 6, a system host 7, a multi-functional weighing & force measuring instrument 8, a system display screen 9, a console operation housing platform 10, a channel baffle 11, etc.

[0052] As Figure 3 shown, it is the device control logic diagram of the present invention. The device can be divided into five modules, with the host control processing module as the center. The position information module unidirectionally transmits the poultry position information to the host control processing module. After the control processing module processes the data, it obtains the poultry position information; the control processing module then sends an instruction to activate the weight calculation module, collects the dynamic weight of the poultry passing through the channel, and calculates the real weight of the poultry and returns it to the host control processing module; the host control processing module obtains the behavior type of the poultry through the behavior analysis module based on the collected information, and finally analyzes the predicted weight of the poultry according to the obtained dynamic weight and the behavior characteristics of the poultry, and transmits the data to the result storage module to save the data.

[0053] As Figure 4 - Figure 6 shown, it is the specific implementation flow chart of the present invention.

[0054] As Figure 4 shown, it is all the state processes of the poultry passing through the platform. The specific steps are as follows:

[0055] S1 When the poultry steps onto the channel platform, the RFID antenna installed at the bottom of the ramp continuously reads the poultry identity information and transmits the information and time to the host control processing module.

[0056] S2 When the poultry steps onto the channel platform, the weight calculation module is activated. At this time, the resistive strain sensor at the bottom of the channel platform starts to work, continuously reads the weight information of the poultry, and when the weight returns below the threshold, the weight reading work for this time is completed.

[0057] S3. Calculate the true weight of the poultry from the collected weight information, as Figure 5 shown, the specific steps for calculating the true weight are as follows:

[0058] S31. Calculate the expected value of the overall dynamic weight data based on the continuously read weight information of the poultry obtained in S2;

[0059] S32: Calculate the expected value of the entire dynamic weight data through the expected value calculation formula, where the expected value calculation formula is as follows:

[0060]

[0061] where: E represents the expected value of the dynamic weight curve; n represents the number of weights collected; w i represents the true weight value.

[0062] S33. Perform mean filtering on the median-filtered weight values to reduce the overall dynamic weight fluctuation;

[0063] Judge whether the dynamic weight is stable through the calculated expected value, and perform a filtering operation on the dynamic weight. First, through the median filtering algorithm, screen the weight values with abnormal weight fluctuations to reduce the maximum and minimum value intervals of the curve. The median filtering calculation formula is as follows:

[0064]

[0065] where: E represents the expected value of the dynamic weight curve; n represents the number of weights collected; w i+1 and w i represent the true weight values at the i + 1 and i moments respectively.

[0066] After performing the median filtering algorithm, perform a mean filtering algorithm again to reduce the overall dynamic weight fluctuation and make the accuracy of the next weight calculation higher. The mean filtering calculation formula is as follows:

[0067]

[0068] where: i represents the position of the weight data to be processed currently; ŵ i represents the filtered weight value; k represents the position of the weight data within the filtering window; w k represents the weight value before filtering; m is the window size of the mean filtering.

[0069] S34: After preprocessing the data, input the processed data into the weight calculation algorithm for weight calculation.

[0070] S35. Slice the data into groups of five data each, and calculate the slope k, intercept b, and root mean square error (RMSE) of each group. The formula for calculating the RMSE is as follows:

[0071]

[0072] where i represents the time instant; represents the predicted weight value, w i represents the actual weight value, and M represents the number of samples for calculating the RMSE.

[0073] S36: Continuously loop through this step until there is no next group of data. Then the weight calculation is completed, and the optimal predicted weight is output as the actual weight of the poultry.

[0074] S4. Calculate the distribution location of the poultry based on the read poultry identity information

[0075] As Figure 6 shown, it is the judgment process of the poultry distribution location. The judgment process of the poultry distribution location:

[0076] S41: After the poultry passes through the passage, transmit the information collected by the RFID reader / writer to the location information module; sort it in the order of the collection time.

[0077] S42: After preprocessing the data, compare the RFID antenna numbers of the signals read before and after the poultry passes through the passage to determine whether the poultry has passed through the passage.

[0078] S43: Determine the entry and exit directions of the poultry according to the RFID antenna numbers before and after reading the identity information. Based on the current RFID antenna position of the read poultry and the entry and exit directions, determine the current location information of the poultry.

[0079] S44: By comparing the relevant data such as time, weight, and reading position collected in different time periods, obtain the distribution location rule of the poultry.

[0080] This method performs operations such as data re - cleaning, preprocessing, and analysis on the behavioral data collected in the above steps, which can reduce the influence of data interference items and greatly improve the accuracy of analyzing the growth performance of individual poultry; at the same time, through the collected information such as the location and weight of the poultry, big data analysis is carried out on the distribution rule and growth performance rule of the poultry. The following are the specific rule analysis steps.

[0081] To explore the individual growth pattern of poultry, we first obtain the daily live weight data of poultry collected in step S3. Taking weeks and months as time units, we calculate the most accurate daily live weight of each poultry according to its behavioral characteristics and location information in different positions. Then, we plot the change curve of the live weight data of each poultry, and organize the change of the average live weight of the group by week and month, and use line charts for visual display respectively. Through the line chart of the change of the average live weight of the group, we analyze the weight change trend of the whole group of poultry, and determine the growth period and slaughter period of the poultry group. In addition, by plotting the change curve of the live weight data of each poultry and comparing it with the change of the average weight of the poultry group, we screen out individuals with abnormal weight and eliminate them as early as possible. By controlling the feeding of poultry at different times and eliminating poultry with abnormal weight at the same time, we can save the feeding cost and improve the economic benefits of the farm.

[0082] To explore the distribution pattern of poultry, we organize the poultry location information collected in step S4 according to time. Subsequently, we use a stacked chart to show the duration of poultry staying in different areas, so as to understand the preferences and activity patterns of poultry in different areas.

[0083] Next, by plotting the time-area distribution map, we analyze the location distribution pattern of poultry at different times, and conduct in-depth analysis in combination with the weight change of poultry. By comparing the relationship between the activity frequency of poultry in different areas and their weight gain, we can predict the weight change trend of poultry under different environmental conditions and improve the accuracy of weight management. At the same time, the system will continuously monitor the location information of each poultry. Based on the location information of poultry, we use big data analysis methods to deeply mine its long-term activities, and further study the activity patterns and weight changes of poultry under different environmental factors, so as to provide data support for predicting the weight trend of poultry and optimizing scientific management.

[0084] To enable users to more intuitively see the individual growth performance of poultry, the system platform provides a data dashboard module, a growth performance module, a behavior analysis module, a data warning module, and an operation management module. The technology stack used is the Vue3 framework and Alibaba open source components to implement the front-end style, and the Java SpringBoot framework, middleware redis, and MyBatisPlus framework to implement the back-end structure;

[0085] The data dashboard module provides users with a page to view the data information of the poultry group, and respectively displays the on-site installation diagram of the equipment, the site camera video, the number of equipment, and the summary of the behavioral characteristics, growth performance data information, and equipment abnormal alarms of the poultry group.

[0086] The described growth performance module provides a page for users to view the growth performance of individual poultry, showing the current weight, yesterday's weight, last month's weight, and initial weight of the poultry respectively, presenting the growth of the poultry from different time spans, and providing a reference criterion for users to judge the future growth trend of the poultry.

[0087] The described behavior analysis module provides a page for users to view the behavior patterns of poultry at different time periods. This page shows the different behaviors carried out by the poultry in each time period, helping users accurately locate the distribution position of the poultry and the living habits of the poultry group. Relying on these data, a more scientific poultry management strategy can be realized.

[0088] The described alarm information module provides an alarm information page for users, prompting users about the current problems with equipment types, poultry, etc., enabling users to promptly discover problems with the equipment and poultry and conduct inspections and repairs.

[0089] The described operation management module provides a page for threshold management and equipment management for users. Users can adjust different parameter types in the threshold management to control parameters such as the normal weight range of poultry, and support users to adjust the behavior parameters of poultry according to the actual production scenario. The equipment management page shows all the equipment types deployed by the users of this farm, and clear viewing, management, and other operations can be performed on each equipment.

[0090] The management system and user interaction platform provided by this measurement device enable users to more clearly view parameters such as the growth performance and behavior characteristics of poultry in the farm, realize high-precision real-time monitoring of poultry, and have strong practical value.

[0091] This invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0092] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device realizes the functions in the processFigure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide for implementing in the process Figure 1 one process or multiple processes and / or blocks Figure 1 the steps of the functions specified in one block or multiple blocks.

[0094] In the present invention, specific embodiments are used to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

[0095] Those of ordinary skill in the art will realize that the embodiments described herein are for helping the reader understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. A method for measuring the growth performance of poultry in a multi-channel walk-in flat-raising manner, characterized in that: The steps include: S1. Construct a multi-channel walk-in flat-raising poultry growth performance measurement system, including a control processing module, a position information module, a behavior analysis module, a weight calculation module and a result storage module, wherein: The position information module transmits the poultry position information to the control processing module in one direction, and the control processing module obtains the poultry position information after data processing; the control processing module then sends instructions to activate the weight calculation module, collects the dynamic weight of the poultry passing through the channel, and calculates the real weight of the poultry and returns it to the control processing module; the control processing module obtains the behavior type of the poultry through the collected information through the behavior analysis module, and finally analyzes the predicted weight of the poultry based on the obtained dynamic weight and the behavior characteristics of the poultry, and transmits the data to the result storage module for storage; Build a multi-channel walk-in flat-raising poultry growth performance measurement device, including a ramp, an RFID reader / writer, a channel platform, a bottom resistive strain sensor, a channel railing, an RFID reader / writer, a system host, a multi-function weighing and force measuring instrument, a system display screen, a piano-style operating shell platform, and a channel baffle; S2. When the poultry steps onto the channel platform, the weight calculation module is activated. At this time, the resistive strain sensor at the bottom of the channel platform starts to work and continuously reads the weight information of the poultry. When the weight returns to below the threshold, the weight reading work is completed. S3, calculating the actual weight of the poultry from the collected weight information, specifically in the following manner: S31, calculating the expected value of the overall dynamic weight data according to the continuously read weight information of the poultry obtained in S2; S32, judging whether the dynamic body weight is balanced according to the expected value calculated in S31, and if it is unbalanced, filtering the abnormally fluctuating body weight value through a median filtering algorithm; S33, performing mean filtering on the weight value after median filtering to reduce overall dynamic weight fluctuation; S34, based on the processing result of S33, input the processed data into the weight calculation module for weight calculation, and output the weight calculation result; S35, dividing the weight calculation result outputted by S34 into multiple groups of data slices, and calculating the slope, intercept and root mean square error of each group of data; S36, repeating steps S31-S35 until there is no next set of data, completing the weight calculation, and outputting the optimal predicted weight as the actual weight of the poultry; S4. Calculate the distribution location of the poultry based on the read poultry identity information.

2. The method for measuring growth performance of poultry in a multi-channel walk-in flat-raising manner according to claim 1, characterized in that: The calculation method of the expected value in S32 is: Where: E represents the expected value of the dynamic weight curve; n represents the number of weights collected; w i+1 and w i Represent the actual weight values ​​at time i+1 and time i respectively.

3. The method for measuring growth performance of poultry in a multi-channel walk-in flat-raising manner according to claim 1, characterized in that: The specific method of median filtering in S32 is: Among them: i represents the time, Represents the predicted weight value, w i Represents the actual weight value; m represents the window size of the median filter, and median() means calculating the median of a set of data.

4. The method for measuring growth performance of poultry in a multi-channel walk-in flat-raising manner according to claim 1, characterized in that: The specific calculation formula of the mean filtering in S33 is: Among them: i represents the moment; represents the predicted weight value; k represents the position of the weight data in the filter window; w k Represents the weight value before mean filtering; m is the window size of mean filtering.

5. The method for measuring growth performance of poultry in a multi-channel walk-in flat-raising manner according to claim 1, characterized in that: The specific calculation formula of the root mean square error in S35 is: Among them, i represents the moment; Represents the predicted weight value, w i represents the true weight value, and M represents the number of samples for calculating the root mean square error.

6. The method for measuring growth performance of poultry in a multi-channel walk-in flat-raising manner according to claim 1, characterized in that: The S4 specifically includes the following steps: S41, after the poultry passes through the channel, the information collected by the RFID reader is transmitted to the location information module; and the information is sorted according to the time sequence of collection; S42, after pre-processing the data, comparing the RFID antenna numbers of the signals read before and after the poultry passes through the channel, to determine whether the poultry has passed through the channel; S43, judging the entry and exit direction of the poultry according to the front and rear RFID antenna numbers of the read identity information, and judging the current location information of the poultry according to the RFID antenna position and the entry and exit direction of the poultry currently read; S44. By comparing the relevant data of time, weight, and reading position collected in different time periods, the distribution pattern of the poultry is obtained.

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