Live pig slaughtering data tracing system based on Internet of Things

Abstract

The invention relates to the field of Internet of Things data tracing, in particular to a live pig slaughtering data tracing system based on Internet of Things, which comprises a plurality of reading modules used for reading information of electronic ear tags worn by live pigs, a storage module used for storing the information of the electronic ear tags, preprocessing the information of the electronic ear tags and generating corresponding preprocessing data, and a learning module used for learning the electronic ear tags worn by the live pigs. The learning module is used for selecting a plurality of index characteristics of the preprocessed data for learning and generating a corresponding slaughter traceability graph according to the index characteristics, and the adjusting module is used for adjusting the learning module according to the slaughter traceability graph of the learning module, and the slaughter traceability model is used for visualizing the pig slaughter data, so that the difficulty of the traceability process is reduced, and the efficiency is improved. The accuracy of live pig slaughtering data tracing is effectively improved, the problem that tracing cannot be continued due to human reasons after live pig slaughtering is effectively solved, and a foundation is laid for whole-process safe tracing of pork production.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things data tracing, and in particular to a pig slaughtering data tracing system based on the Internet of Things. Background Art

[0002] my country is the world's largest pork producer, with pork accounting for 65% of my country's meat production. However, the quality and safety of pork in my country is poor, and meat food safety incidents occur from time to time. In 2005, the Ministry of Agriculture and Rural Affairs began to pilot the construction of animal identification and disease traceability systems in accordance with relevant laws and regulations, and attempted to build an information-based livestock industry. However, in recent years, meat food safety accidents still occur from time to time. There are many reasons for this. First, the industrial chain is relatively long. Pork production involves breeding, slaughtering, processing and other links. Without efficient regulatory means and methods, it is difficult to achieve full traceability. Secondly, under my country's current conditions, there will be a large number of small-scale meat breeding and production companies for a long time. The existing food traceability is usually batch operation, and there are regulatory loopholes for the products of small-scale companies.

[0003] China Patent Authorization Announcement No.: CN114897539B discloses a livestock product traceability system based on big data, including a livestock data acquisition module for acquiring livestock product breeding environment data, generating monitoring data after associating the breeding environment data with the electronic ID card of the livestock product, a slaughter information acquisition module for acquiring slaughter information, a transportation information acquisition module for acquiring transportation information, a store sales information acquisition module for acquiring store sales information, a cloud computing storage module for storing data acquired by the above modules, and a query module for querying livestock product breeding environment data and other data. The invention acquires the breeding environment data of livestock products, and then associates it with the electronic ID card of the livestock products and transmits it to the cloud computing storage module for storage. This setting method is conducive to providing corresponding environmental data when tracing the source of livestock products, so as to provide reference information on the breeding environment when analyzing livestock product quality issues.

[0004] China Patent Application Publication No.: CN114897539A discloses a livestock product traceability system based on big data, including a livestock data acquisition module for acquiring livestock product breeding environment data, generating monitoring data after associating the breeding environment data with the electronic ID card of the livestock product, a slaughter information acquisition module for acquiring slaughter information, a transportation information acquisition module for acquiring transportation information, a store sales information acquisition module for acquiring store sales information, a cloud computing storage module for storing data acquired by the above modules, and a query module for querying livestock product breeding environment data and other data. The invention acquires the breeding environment data of livestock products, and then associates it with the electronic ID card of the livestock products and transmits it to the cloud computing storage module for storage. This setting method is conducive to providing corresponding environmental data when tracing the source of livestock products, so as to provide reference information on the breeding environment when analyzing livestock product quality issues.

[0005] However, the above method has the following problems: it is impossible to intelligently trace pig slaughter data in real time and the traceability accuracy is low. Summary of the invention

[0006] To this end, the present invention provides a pig slaughtering data tracing system based on the Internet of Things, which is used to overcome the problems in the prior art that the pig slaughtering data cannot be intelligently traced in real time and the tracing accuracy is low.

[0007] To achieve the above object, the present invention provides a pig slaughter data tracing system based on the Internet of Things, comprising:

[0008] Several reading modules, which are used to read the electronic ear tag information worn by each pig;

[0009] A storage module connected to the reading module, used to store the electronic ear tag information, and pre-process the electronic ear tag information to generate corresponding pre-processed data;

[0010] A learning module, which is connected to the storage module and is used to select several indicator features of the preprocessed data for learning, and generate a corresponding slaughter traceability map according to the indicator features;

[0011] an adjustment module connected to the learning module, for adjusting the learning module according to the slaughter traceability diagram of the learning module;

[0012] Wherein, the electronic ear tag is installed on the head of each pig;

[0013] Half of the electronic ear tag information is stored in the electronic ear tag, and the other half is stored in the reading module;

[0014] The preprocessed data is fitted according to the electronic ear tag information, and a number of data with a sampling rate of a standard sampling rate is generated, and corresponding indicator features are generated;

[0015] The indicator characteristics include the weight, slaughter time and / or reading time of each pig.

[0016] Furthermore, the reading module includes:

[0017] A reader, which is used to store the electronic ear tag information and read the electronic ear tag information worn by each pig;

[0018] A timer connected to the reader for sending a reading instruction in real time at fixed intervals;

[0019] A transmitter connected to the reader for receiving and transmitting the electronic ear tag information;

[0020] The reading instruction is to control the reader to read the electronic ear tag information.

[0021] Furthermore, the storage module includes:

[0022] A receiver connected to the transmitter for receiving the electronic ear tag information;

[0023] A memory, connected to the receiver, for extracting and storing the electronic ear tag information;

[0024] A preprocessor is connected to the memory and is used to preprocess the electronic ear tag information and generate corresponding preprocessing data.

[0025] Furthermore, the learning module includes:

[0026] A processor, configured to receive the preprocessed data and select a plurality of the indicator features of the preprocessed data;

[0027] A learner connected to the processor for learning the preprocessed data to obtain a corresponding slaughter traceability diagram;

[0028] Wherein, a slaughter traceability model is provided in the learner, and the slaughter traceability model is generated by training the preprocessed data.

[0029] Furthermore, the adjustment module includes:

[0030] A monitor, which is used to analyze the slaughter traceability diagram and obtain corresponding analysis results;

[0031] A regulator, connected to the monitor, for making an adjustment judgment on the learner according to the analysis result and sending an adjustment instruction;

[0032] A transmitter, connected to the regulator and the learner, for sending the regulation instruction;

[0033] Wherein, a traceability accuracy threshold is provided in the monitor;

[0034] The traceability accuracy threshold is the minimum standard of the traceability accuracy of the slaughter traceability model for each pig slaughter data.

[0035] Furthermore, the reader is placed above the head removal station, and the timer sends the reading instruction to the reader at fixed intervals. When the pig's head passes by, the reader receives the reading instruction and reads the electronic ear tag information installed on the pig's head. When the electronic ear tag information on the pig's head is consistent with the electronic ear tag information in the reader, the reader collects the electronic ear tag information and transmits it to the receiver through the transmitter.

[0036] Furthermore, the receiver receives the electronic ear tag information, the memory extracts and stores the electronic ear tag information, and transmits the electronic ear tag information to the preprocessor to preprocess the electronic ear tag information.

[0037] The preprocessing is to standardize the electronic ear tag information.

[0038] The standardization process is to segment the electronic ear tag information according to a standard sampling rate;

[0039] The standard sampling rate is a sampling rate that can be recognized by the slaughter traceability model, and is related to the minimum recognition capability of the slaughter traceability model.

[0040] Furthermore, the processor in the learning module receives the preprocessing information, generates corresponding indicator features according to the preprocessing information, and transmits the features to the learner, and the slaughter traceability model obtains the slaughter traceability diagram.

[0041] Among them, the slaughter traceability map is a traceability map of the slaughter destination of the live pigs.

[0042] Furthermore, the monitor analyzes the slaughter traceability map to obtain the traceability accuracy of the slaughter destination map, and compares the traceability accuracy with the traceability accuracy threshold. When the traceability accuracy is greater than the traceability accuracy threshold, the regulator does not adjust the learner.

[0043] Furthermore, when the regulator determines that the traceability accuracy is less than the traceability accuracy threshold, the transmitter sends an adjustment instruction to the learner, and the learner adjusts the learning rate of the slaughter traceability model when receiving the adjustment instruction.

[0044] Compared with the prior art, the present invention utilizes several reading modules to read the electronic ear tag information worn by each pig, a storage module to store the electronic ear tag information, and pre-process the electronic ear tag information to generate corresponding pre-processed data, a learning module to select several indicator features of the pre-processed data for learning, and generate a corresponding slaughter traceability map according to the indicator features, and an adjustment module to adjust the learning module according to the slaughter traceability map of the learning module. The slaughter data of pigs is visualized using a slaughter traceability model, which reduces the difficulty of the traceability process, effectively improves the accuracy of the traceability of pig slaughter data, and effectively solves the problem of being unable to continue tracing due to human reasons after the pigs are slaughtered, laying a foundation for the full-process safe traceability of pork production.

[0045] Furthermore, by setting a timer in the reading module, the electronic ear tag information can be read in real time, thereby improving the operating efficiency of the pig slaughter data traceability system and reducing the complexity of pig slaughter data traceability.

[0046] Furthermore, by setting a preprocessor in the storage module to preprocess the electronic ear tag information, errors caused by mistakes in collecting pig slaughter data are avoided, thereby improving the accuracy of the model learning results.

[0047] Furthermore, by setting up a slaughter traceability model and learning the preprocessed data, the accuracy of pig slaughter data was improved, effectively solving the problem of being unable to continue tracing due to human factors after pig slaughter.

[0048] Furthermore, by setting a traceability accuracy threshold in the monitor, it is possible to quickly determine whether the learner needs to be adjusted, thereby further reducing the difficulty of tracing pig slaughter data.

[0049] Furthermore, by utilizing the processor to generate indicator features for preprocessed information, the efficiency of pig slaughter data traceability is improved, so that effective features of pig slaughter data can be quickly selected, thereby further improving the accuracy of model learning results.

[0050] Furthermore, by sending adjustment instructions to the learner through the transmitter, the learning rate of the slaughter traceability model is adjusted, thereby realizing the intelligent and real-time regulation of live pig slaughter data, laying the foundation for the full safety traceability of pork production. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1This is a schematic diagram of the structure of the pig slaughter data tracing system based on the Internet of Things of the present invention;

[0052] Figure 2 This is a schematic diagram of the structure of the reading module of the present invention;

[0053] Figure 3 This is a schematic diagram of the storage module structure of the present invention;

[0054] Figure 4 This is a schematic diagram of the structure of the learning module of the present invention;

[0055] Figure 5 This is a schematic diagram of the structure of the adjustment module of the present invention;

[0056] Figure 6 Schematic diagram of the process of reading electronic ear tags in the present invention;

[0057] Among them: 1. Electronic ear tag; 2. Electronic ear tag information in the reader; 3. Live pig ear. DETAILED DESCRIPTION

[0058] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0059] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0060] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0061] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0062] See also Figure 1 As shown, it is a schematic diagram of the structure of the pig slaughter data tracing system based on the Internet of Things of the present invention, including:

[0063] Several reading modules, which are used to read the electronic ear tag information worn by each pig;

[0064] A storage module, which is connected to the reading module and is used to store the electronic ear tag information and pre-process the electronic ear tag information to generate corresponding pre-processed data;

[0065] A learning module, which is connected to the storage module, is used to select several indicator features of the preprocessed data for learning, and generate a corresponding slaughter traceability map according to the indicator features;

[0066] An adjustment module, which is connected to the learning module and is used to adjust the learning module according to the slaughter traceability diagram of the learning module;

[0067] Among them, electronic ear tags are installed on the heads of each pig;

[0068] The electronic ear tag information is divided into two parts, one of which is stored in the storage module and the other is stored in the reading module;

[0069] The preprocessed data is fitted according to the electronic ear tag information, and a number of data with a standard sampling rate are generated, and corresponding indicator features are generated;

[0070] For the obtained pig slaughtering data, the corresponding indicator characteristics are the weight, slaughtering time and / or reading time of each pig.

[0071] Preferably, setting the sampling rate to 100 / second has a better traceability effect on pig slaughter data, and for the system described in this application, the corresponding analysis and traceability effect is optimal.

[0072] Embodiment 1:

[0073] The following is the data of pig slaughter:

[0074] "Pig A weighs 125kg, and was slaughtered at 22:13 on September 2, 2024. The read time is 22:20 on September 2, 2024."

[0075] If the sampling rate is 80, the extracted indicator features are "125, 22:13, 22:20".

[0076] If the sampling rate is 100, the extracted indicator features are "125kg, September 2, 2024 22:13, September 2, 2024 22:20".

[0077] The system is provided with a plurality of reading modules for reading the electronic ear tag information worn by each pig, a storage module for storing the electronic ear tag information, and preprocessing the electronic ear tag information to generate corresponding preprocessed data, a learning module for selecting a plurality of indicator features of the preprocessed data for learning, and generating a corresponding slaughter traceability diagram according to the indicator features, and an adjustment module for adjusting the learning module according to the slaughter traceability diagram of the learning module. The slaughter data of the pigs is visualized by using the slaughter traceability model, which reduces the difficulty of the traceability process, effectively improves the accuracy of the traceability of the pig slaughter data, and effectively solves the problem of being unable to continue the traceability due to human factors after the pigs are slaughtered, thus laying a foundation for the safe traceability of the whole process of pork production.

[0078] See also Figure 2 As shown, it is a schematic diagram of the structure of the reading module of the present invention, including:

[0079] A reader, which is used to read and collect the electronic ear tag information worn by each pig;

[0080] A timer connected to the reader for sending a read instruction in real time at fixed intervals;

[0081] A transmitter connected to the reader for receiving and transmitting electronic ear tag information;

[0082] The reading instruction is to control the reader to read the electronic ear tag information.

[0083] Embodiment 2:

[0084] Assuming the fixed duration is 0.5s, the timer sends a read instruction to the reader at 0.5s, and the reader performs the first read; sends a read instruction to the reader at 1.0s, and the reader performs the second read; sends a read instruction to the reader at 1.5s, and the reader performs the third read; sends a read instruction to the reader at 2.0s, and the reader performs the fourth read.

[0085] Embodiment 3:

[0086] Assuming the fixed duration is 0.2s, the timer sends a read instruction to the reader at 0.2s, and the reader performs the first reading; sends a read instruction to the reader at 0.4s, and the reader performs the second reading; sends a read instruction to the reader at 0.6s, and the reader performs the third reading; sends a read instruction to the reader at 0.8s, and the reader performs the fourth reading.

[0087] By setting a timer in the reading module, the electronic ear tag information can be read in real time, which improves the operating efficiency of the pig slaughter data traceability system and reduces the complexity of pig slaughter data traceability.

[0088] See also Figure 3 As shown, it is a schematic diagram of the storage module structure of the present invention, including:

[0089] A receiver connected to the transmitter for receiving electronic ear tag information;

[0090] A memory, connected to the receiver, for extracting and storing electronic ear tag information;

[0091] The preprocessor is connected to the memory and is used to preprocess the electronic ear tag information and generate corresponding preprocessed data.

[0092] By setting a preprocessor in the storage module to preprocess the electronic ear tag information, errors caused by mistakes in collecting pig slaughter data can be avoided, thereby improving the accuracy of the model learning results.

[0093] See also Figure 4 As shown, it is a schematic diagram of the structure of the learning module of the present invention, including:

[0094] A processor, which is used to receive pre-processed data and select several indicator features of the pre-processed data;

[0095] A learner, which is connected to the processor and is used to learn the pre-processed data to obtain a corresponding slaughter traceability diagram;

[0096] Among them, a slaughter traceability model is provided in the learner, and the slaughter traceability model is generated by preprocessing data training.

[0097] By setting up a slaughter traceability model and learning the preprocessed data, the accuracy of pig slaughter data is improved, and the problem of being unable to continue tracing due to human factors after pig slaughter is effectively solved.

[0098] See also Figure 5 As shown, it is a schematic diagram of the structure of the adjustment module of the present invention, including:

[0099] A monitor, which is used to analyze the slaughter traceability map and obtain corresponding analysis results;

[0100] A regulator, which is connected to the monitor and is used to make adjustment judgments on the learner according to the analysis results and send adjustment instructions;

[0101] A transmitter, connected to the regulator and the learner, for sending a regulation instruction;

[0102] Among them, a traceability accuracy threshold is set in the monitor;

[0103] The traceability accuracy threshold is the minimum standard for the traceability accuracy of each pig slaughter data by the slaughter traceability model.

[0104] By setting the traceability accuracy threshold in the monitor, it is possible to quickly determine whether the learner needs to be adjusted, thereby further reducing the difficulty of tracing pig slaughter data.

[0105] See also Figure 6 As shown, it is a schematic diagram of the process of reading the electronic ear tag of the present invention. The electronic ear tag information is divided into two parts, wherein one part is stored in the storage module, and the other part of the electronic ear tag information 2 in the reader is stored in the reading module. The reader is placed above the head removal station, and the timer sends a read instruction to the reader at a fixed interval. When the pig ear 3 passes by, the reader receives the read instruction and reads the electronic ear tag 1 installed on the pig's head. When the electronic ear tag information of the pig ear 3 is consistent with the electronic ear tag information 2 in the reader, the reader collects the electronic ear tag information in the electronic ear tag 1 and transmits it to the receiver through the transmitter.

[0106] Specifically, the receiver receives the electronic ear tag information, the memory extracts and stores the electronic ear tag information, and transmits the electronic ear tag information to the preprocessor to preprocess the electronic ear tag information.

[0107] Among them, preprocessing is to standardize the electronic ear tag information.

[0108] The standardization process is to segment the electronic ear tag information according to the standard sampling rate;

[0109] The standard sampling rate is the sampling rate that the slaughter traceability model can identify, which is related to the minimum recognition capability of the slaughter traceability model.

[0110] Specifically, the processor in the learning module receives the preprocessing information, generates corresponding indicator features based on the preprocessing information, and transmits them to the learner. The slaughter traceability model obtains the slaughter traceability map.

[0111] Among them, the slaughter traceability map is a traceability map of the slaughter destination of live pigs.

[0112] By using the processor to generate indicator features from preprocessed information, the efficiency of pig slaughter data traceability is improved, so that effective features of pig slaughter data can be quickly selected, thereby further improving the accuracy of model learning results.

[0113] Specifically, the monitor analyzes the slaughter traceability map, obtains the traceability accuracy of the slaughter destination map, and compares the traceability accuracy with the traceability accuracy threshold. When the traceability accuracy is greater than the traceability accuracy threshold, the regulator does not adjust the learner.

[0114] Embodiment 4:

[0115] If the traceability accuracy threshold is 80%, the learning rate of the slaughter traceability model is 0.1, and the traceability accuracy is monitored to be 85%, the regulator does not adjust the learner.

[0116] Specifically, when the regulator determines that the traceability accuracy is less than the traceability accuracy threshold, the transmitter sends an adjustment instruction to the learner, and when the learner receives the adjustment instruction, it adjusts the learning rate of the slaughter traceability model.

[0117] Embodiment 5:

[0118] If the traceability accuracy threshold is 80%, the learning rate of the slaughter traceability model is 0.1, and the traceability accuracy is monitored to be 75%, the transmitter sends an adjustment instruction to the learner. When the learner receives the adjustment instruction, it adjusts the learning rate of the slaughter traceability model to 0.001.

[0119] By sending adjustment instructions to the learner through the transmitter, the learning rate of the slaughter traceability model is adjusted, which realizes the intelligent and real-time regulation of live pig slaughter data and lays the foundation for the full safety traceability of pork production.

[0120] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0121] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A pig slaughter data traceability system based on the Internet of Things, characterized in that: include: Several reading modules, which are used to read the electronic ear tag information worn by each pig; A storage module connected to the reading module, used to store the electronic ear tag information, and pre-process the electronic ear tag information to generate corresponding pre-processed data; A learning module, which is connected to the storage module and is used to select several indicator features of the preprocessed data for learning, and generate a corresponding slaughter traceability map according to the indicator features; an adjustment module connected to the learning module, for adjusting the learning module according to the slaughter traceability diagram of the learning module; Wherein, the electronic ear tag is installed on the head of each pig; The electronic ear tag information is divided into two parts, one part is stored in the storage module, and the other part is stored in the reading module; The preprocessed data is fitted according to the electronic ear tag information, and a number of data with a sampling rate of a standard sampling rate is generated, and corresponding indicator features are generated; The indicator characteristics include the weight, slaughter time and / or reading time of each pig.

2. The pig slaughter data tracing system based on the Internet of Things according to claim 1 is characterized in that: The reading module comprises: A reader, which is used to store the electronic ear tag information and read the electronic ear tag information worn by each pig; A timer connected to the reader for sending a reading instruction in real time at fixed intervals; A transmitter connected to the reader for receiving and transmitting the electronic ear tag information; The reading instruction is to control the reader to read the electronic ear tag information.

3. The pig slaughter data tracing system based on the Internet of Things according to claim 2 is characterized in that: The storage module comprises: A receiver connected to the transmitter for receiving the electronic ear tag information; A memory, connected to the receiver, for extracting and storing the electronic ear tag information; A preprocessor is connected to the memory and is used to preprocess the electronic ear tag information and generate corresponding preprocessing data.

4. The pig slaughter data tracing system based on the Internet of Things according to claim 3 is characterized in that: The learning module includes: A processor, configured to receive the preprocessed data and select a plurality of the indicator features of the preprocessed data; A learner connected to the processor for learning the preprocessed data to obtain a corresponding slaughter traceability diagram; Wherein, a slaughter traceability model is provided in the learner, and the slaughter traceability model is generated by training the preprocessed data.

5. The pig slaughter data tracing system based on the Internet of Things according to claim 4 is characterized in that: The adjustment module comprises: A monitor, which is used to analyze the slaughter traceability diagram and obtain corresponding analysis results; A regulator connected to the monitor, configured to make an adjustment judgment on the learner according to the analysis result and send an adjustment instruction; A transmitter, connected to the regulator and the learner, for sending the regulation instruction; Wherein, a traceability accuracy threshold is provided in the monitor; The traceability accuracy threshold is the minimum standard of the traceability accuracy of the slaughter traceability model for each pig slaughter data.

6. The pig slaughter data tracing system based on the Internet of Things according to claim 5 is characterized in that: The reader is placed above the head removal station, and the timer sends the reading instruction to the reader at fixed intervals. When the pig's head passes by, the reader receives the reading instruction and reads the electronic ear tag information installed on the pig's head. When the electronic ear tag information on the pig's head is consistent with the electronic ear tag information in the reader, the reader collects the electronic ear tag information and transmits it to the receiver through the transmitter.

7. The pig slaughter data tracing system based on the Internet of Things according to claim 6 is characterized in that: The receiver receives the electronic ear tag information, the memory extracts and stores the electronic ear tag information, and transmits the electronic ear tag information to the preprocessor to preprocess the electronic ear tag information. The preprocessing is to standardize the electronic ear tag information. The standardization process is to segment the electronic ear tag information according to a standard sampling rate; The standard sampling rate is a sampling rate that can be recognized by the slaughter traceability model, and is related to the minimum recognition capability of the slaughter traceability model.

8. The pig slaughter data tracing system based on the Internet of Things according to claim 7 is characterized in that: The processor in the learning module receives the preprocessing information, generates corresponding indicator features according to the preprocessing information, and transmits the features to the learner. The slaughter traceability model obtains the slaughter traceability diagram. Among them, the slaughter traceability map is a traceability map of the slaughter destination of the live pigs.

9. The pig slaughter data tracing system based on the Internet of Things according to claim 8 is characterized in that: The monitor analyzes the slaughter traceability map, obtains the traceability accuracy of the slaughter destination map, and compares the traceability accuracy with the traceability accuracy threshold. When the traceability accuracy is greater than the traceability accuracy threshold, the regulator does not adjust the learner.

10. The pig slaughter data tracing system based on the Internet of Things according to claim 9 is characterized in that: When the regulator determines that the traceability accuracy is less than the traceability accuracy threshold, the transmitter sends an adjustment instruction to the learner, and the learner adjusts the learning rate of the slaughter traceability model when receiving the adjustment instruction.

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