Digital intelligent yak breeding system and method based on artificial intelligence

Abstract

The invention provides a yak digital intelligent breeding system and method based on artificial intelligence. The system comprises a terminal equipment communication module, a digital identity identification module, an automatic weighing and grouping module, a pasture environment monitoring module, a breeding management module, an epidemic prevention and health care module, a breeding stock management module, a breeding large model module, an industrial chain tracing module, a quality tracing and monitoring module and an asset credible supervision and financial service module. And a biological asset service ecological module. According to the application, technologies of Internet of Things, artificial intelligence, block chains, digital native, big data and the like are integrated, the characteristics of the yak industry are combined, upstream and downstream ecological cooperative partners of the industry are opened, a yak digital solution is created, and digital asset security sharing of the whole industry is opened, so that the problems of yak positioning, scientific management and economic appreciation are solved.

Description

Technical Field

[0001] This application relates to the field of smart farming technology, and in particular to a digital smart farming system and method for yaks based on artificial intelligence. Background Technology

[0002] Yaks are among the world's most geographically limited free-range animals, mainly distributed in the plateau region centered on the Qinghai-Tibet Plateau in China, inhabiting high-altitude areas of 2,000 to 6,000 meters above sea level.

[0003] The free-range yak farming in the Qinghai-Tibet Plateau region has certain unique characteristics: the breeding areas are vast and sparsely populated with complex terrain, resulting in large-scale blind spots in public networks; yaks have a large range of activities and are highly dynamic, rendering traditional fixed-enclosure management techniques completely ineffective; the industrial chain is long and involves many participants, leading to serious data silos, which prevents the value of high-quality yak products from being transmitted through reliable channels and hinders the effective intervention of financial and insurance services.

[0004] Therefore, how to manage yak production more scientifically, enhance the supply capacity of yak meat, and comprehensively promote rural revitalization and stable economic and social development has become a problem that needs to be solved. Summary of the Invention

[0005] The technical problem to be solved by this application is to provide a digital intelligent yak breeding system and method based on artificial intelligence, which addresses the above-mentioned shortcomings of the existing technology and solves the problems existing in the existing technology.

[0006] In a first aspect, this application provides a digital intelligent yak farming system based on artificial intelligence, the system comprising:

[0007] The terminal device communication module includes an adaptive handover mechanism unit for data communication via satellite network or cellular network;

[0008] The digital identity module includes an tamper-proof yak collar with a blockchain security chip, a real-time positioning unit, an electronic fence unit, a trajectory playback unit, and a ranch management unit;

[0009] The automatic weighing and grouping module includes a grouping rule engine unit that dynamically generates grouping instructions based on individual yak weight information and a preset multi-objective optimization model;

[0010] The pasture environment monitoring module is used to monitor meteorological parameters of the grassland environment in real time.

[0011] The breeding management module is used for data-driven monitoring and event early warning of yak growth, reproduction, health, and feeding processes;

[0012] The disease prevention and health care module is used to analyze information on yaks' diseases, immunization, quarantine, and health care.

[0013] The breeding stock management module is used for digital monitoring, production performance testing, and breeding pedigree management of breeding bulls and cows;

[0014] The large-scale aquaculture model module is used to generate production early warnings and guidance suggestions;

[0015] The supply chain traceability module is used to provide digital service support for the yak breeding supply chain process through blockchain and encryption algorithms;

[0016] The quality traceability and monitoring module is used to supervise standardized breeding processes and trace the yak information chain through blockchain.

[0017] The asset trust supervision and financial services module is used to provide secure and trustworthy livestock ledger services for financial financing and insurance businesses. It uses yak life cycle data as a basis for credit, conducts value assessment and risk pricing of yaks, and outputs trustworthy asset valuation reports.

[0018] The biological asset service ecosystem module is used to establish traceability information for the yak industry among breeders, governments, financial institutions, traders, consumers, and regulators, and to build a regulatory service ecosystem.

[0019] In some embodiments, the adaptive switching mechanism unit is used to continuously monitor the Received Signal Strength Indicator (RSSI) of the cellular network. When the RSSI of the cellular network is lower than a preset threshold and the duration reaches a preset duration, it switches to LoRaWAN mode to upload communication data to the gateway so that the gateway can transmit communication data back via satellite. When the RSSI of the cellular network is higher than or equal to the preset threshold, it switches to the cellular network for data communication.

[0020] In some embodiments, the tamper-proof yak collar generates an asymmetric encryption key pair at the time of manufacture, wherein the private key is permanently stored in the blockchain security chip and cannot be exported, and the public key and a unique digital identity identifier are anchored and registered on the blockchain.

[0021] The tamper-proof yak collar is equipped with sensors that collect the yak's status in real time. The sensor data emitted from the tamper-proof yak collar is signed with the private key and verified with the public key.

[0022] In some embodiments, the real-time positioning unit is used to report the location of the yak in real time;

[0023] The electronic fence unit is used to provide early warnings for yaks exceeding the fence, early warnings for yaks entering the fence, and automatic inventory checks within the fence in key areas.

[0024] The trajectory review unit is used to draw the historical movement trajectory of the yak based on historical location information;

[0025] The ranch management unit is used to realize cattle distribution, cattle inventory, dynamic files, cattle herd structure, cattle herd analysis, and production reports.

[0026] In some embodiments, the grouping rule engine unit is used to obtain the individual weight information of yaks obtained through the automatic weighing system, dynamically generate grouping instructions based on a preset multi-objective optimization model, and transmit the grouping instructions to the intelligent grouping gate to group the yaks.

[0027] The objective function used in the multi-objective optimization model is:

[0028] Max slaughter efficiency = α·weight achievement rate + β·health index - γ·group cost;

[0029] Where α is the weight of the weight achievement rate, β is the weight of the health index, and γ is the weight of the group cost.

[0030] In some embodiments, the pasture environment monitoring module is used to monitor the temperature and humidity, wind speed, wind direction, rainfall, air pressure, photosynthetic radiation, evaporation, and soil temperature and humidity of the pasture environment in real time.

[0031] In some embodiments, the large-scale breeding model module is used to predict the estrus cycle, disease warning, and optimal slaughter period of yaks through a pre-trained network model, and generate production warnings and guidance suggestions based on the prediction results.

[0032] In some embodiments, the supply chain traceability module is used to provide digital service support for the breeding stock, feed, disease prevention and control, fattening, slaughtering and transaction management processes of yak farming through blockchain and encryption algorithms;

[0033] Among them, when in the "seed" stage of the industrial chain: integrating breeding data, estrus monitoring, and mating and breeding;

[0034] When the industry chain is in the "development" stage: integrate feeding data, measurement data, and evaluation data;

[0035] When the industry chain is in the "nurturing" stage: integrate filing information, status monitoring, quarantine information, weighing information, slaughtering information, and early warning;

[0036] When in the "addition" stage of the industrial chain: integrate information on market entry, origin, slaughtering, processing, and packaging;

[0037] When in the "operation" stage of the industrial chain: integrate order information, batch information, logistics information, and QR code traceability.

[0038] In some embodiments, the asset trust supervision and financial services module achieves blockchain gateway on-chain through tamper-proof yak collars to establish global blockchain management from the data source to the cloud server. Key on-chain nodes include breeding, feeding, weighing, quarantine, slaughtering, quality inspection, and orders.

[0039] Secondly, this application provides a digital intelligent yak farming method based on artificial intelligence, the method comprising:

[0040] Based on an adaptive handover mechanism, data communication is conducted via satellite network or cellular network;

[0041] The yak breeding and management system employs tamper-proof yak collars with blockchain security chips, real-time positioning units, electronic fence units, trajectory playback units, and pasture management units.

[0042] Based on the individual weight information of yaks and a preset multi-objective optimization model, a grouping instruction is dynamically generated and issued to group the yaks.

[0043] Real-time monitoring of meteorological parameters of the grassland environment;

[0044] Data-driven monitoring and event early warning of yak growth, reproduction, health, and feeding processes;

[0045] Analyze information on yak diseases, immunization, quarantine, and health care;

[0046] Digital monitoring, production performance testing, and breeding pedigree management of breeding bulls and cows;

[0047] Generate production early warnings and guidance suggestions;

[0048] Providing digital service support for the yak farming industry chain through blockchain and encryption algorithms;

[0049] Standardized breeding processes are monitored and yak information is traced through blockchain technology.

[0050] Provide secure and reliable livestock ledger services for financial financing and insurance businesses, use yak life cycle data as a basis for credit, conduct yak value assessment and risk pricing, and output reliable asset valuation reports;

[0051] Establish a traceability system for the yak industry, involving breeders, government, financial institutions, traders, consumers, and regulators, and create a regulatory service ecosystem.

[0052] This application provides an AI-based digital intelligent yak farming system and method. The system includes: a terminal device communication module, comprising an adaptive switching mechanism unit for data communication via satellite or cellular networks; a digital identity module, comprising an tamper-proof yak collar with a blockchain security chip, a real-time positioning unit, an electronic fence unit, a trajectory playback unit, and a pasture management unit; an automatic weighing and grouping module, comprising a grouping rule engine unit that dynamically generates grouping instructions based on individual yak weight information and a preset multi-objective optimization model; a pasture environment monitoring module for real-time monitoring of meteorological parameters of the grassland environment; a farming management module for data-driven monitoring and event warning of yak growth, reproduction, health, and feeding processes; a disease prevention and health care module for analyzing yak disease, immunization, quarantine, and health care information; and a breeding stock management module. The project comprises five modules: a management module for digital monitoring, performance measurement, and breeding pedigree management of breeding bulls and cows; a large-scale breeding model module for generating production early warnings and guidance; a supply chain traceability module for providing digital service support for the yak breeding supply chain through blockchain and encryption algorithms; a quality traceability and monitoring module for regulating standardized breeding processes and tracing yak information chains through blockchain; an asset trust supervision and financial service module for providing secure and reliable livestock ledger services for financial financing and insurance businesses, using yak life-cycle data as a basis for credit, conducting yak value assessment and risk pricing, and outputting reliable asset valuation reports; and a biological asset service ecosystem module for establishing yak industry traceability information among breeders, governments, financial institutions, traders, consumers, and regulators, and establishing a regulatory service ecosystem. This application integrates technologies such as the Internet of Things, artificial intelligence, blockchain, digital native technologies, and big data, combined with the characteristics of the yak industry, to connect upstream and downstream ecosystem partners, create a yak digital solution, and enable secure sharing of digital assets across the entire industry to solve the problems of yak positioning, scientific management, and economic value enhancement. For the vast grassland ranches of our clients, we have built a "full-coverage" LoRaWAN + satellite / cellular IoT connectivity service, bridging the last ten kilometers of satellite IoT and solving the problem of inaccessible terrestrial cellular networks in remote and geographically complex grassland ranches. We have customized LoRaWAN collars for yaks, integrating digital identity identification, location tracking, activity monitoring, and body temperature measurement, forming the foundation for "digitalized yaks." We have established a fully reliable traceability system for all stages of breeding, raising, raising, slaughtering, processing, and nutrition, highlighting the unique value of grassland yaks: breed, breeding methods, grassland environment and forage quality, growth records, meat quality testing, etc., to support brand building. We have established a reliable biological asset supervision and financial service system, providing secure and reliable livestock ledger services for core aspects of financial financing and insurance businesses. We have integrated with the new marketing system, providing reliable traceability data for various marketing methods such as online and offline sales, live streaming, and pre-sales for tourism, realizing added value for yak products and demonstrating systematic and comprehensive advantages. Attached Figure Description

[0053] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0054] Figure 1 A schematic diagram of an AI-based digital intelligent yak farming system provided in an embodiment of this application;

[0055] Figure 2 A digital schematic diagram of a yak provided in an embodiment of this application;

[0056] Figure 3 This is a schematic diagram of the communication architecture of the terminal device according to an embodiment of this application;

[0057] Figure 4 This is a schematic diagram of the digital transformation of the yak industry chain according to an embodiment of this application;

[0058] Figure 5 This is a schematic diagram illustrating the trusted asset supervision and financial services provided in an embodiment of this application.

[0059] Figure 6 A schematic diagram illustrating the yak biological asset service ecosystem as described in this application embodiment;

[0060] Figure 7 This is a schematic diagram of an artificial intelligence-based digital intelligent yak farming method provided in an embodiment of this application.

[0061] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0062] To enable those skilled in the art to better understand the technical solution of this application, the embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0063] It is understood that the specific embodiments and accompanying drawings described herein are merely for explaining this application and are not intended to limit this application.

[0064] It is understood that, without conflict, the various embodiments and features in the embodiments of this application can be combined with each other.

[0065] It is understood that, for ease of description, only the parts relevant to this application are shown in the accompanying drawings, while parts unrelated to this application are not shown in the drawings.

[0066] It is understood that each unit or module involved in the embodiments of this application may correspond to only one entity structure, or may be composed of multiple entity structures, or multiple units or modules may be integrated into one entity structure.

[0067] It is understood that the terms "first," "second," etc., used in the embodiments of this application are used to distinguish different objects or to distinguish different treatments of the same object, rather than to describe a specific order of objects.

[0068] It is understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of this application may occur in a different order than those marked in the accompanying drawings.

[0069] It is understood that the flowcharts and block diagrams of this application illustrate the possible architecture, functions, and operations of systems, apparatuses, devices, and methods according to various embodiments of this application. Each block in a flowchart or block diagram may represent a unit, module, program segment, or code, containing executable instructions for implementing the specified function. Furthermore, each block or combination of blocks in the block diagrams and flowcharts may be implemented using a hardware-based system to implement the specified function, or using a combination of hardware and computer instructions.

[0070] It is understood that the units and modules involved in the embodiments of this application can be implemented by software or by hardware. For example, the units and modules can be located in the processor.

[0071] It is understood that the specific values ​​of each parameter in this application are merely illustrative examples, and in practical applications, the parameters can be optimized and adjusted based on specific requirements.

[0072] Currently, the main challenges in yak farming are as follows:

[0073] I. Lack of scientific management: Inbreeding leads to population degradation; yak breeding has a long cycle and low productivity; it is difficult to carry out precise disease prevention and regional management; unsupervised grazing leads to grassland degradation.

[0074] II. Lost Yaks: How to accurately locate and quickly recover free-range yaks that have been stolen or lost? In areas with no network coverage in grasslands, how can the locator report its location in a timely manner? How can we effectively prevent yaks from wandering off and causing traffic disruptions or damage to municipal infrastructure? Free-range yaks are prone to loss, and network blind spots can lead to location tracking failures.

[0075] Third, the average mortality rate of livestock caused by various disasters in the Tibetan plateau region is 2.5 times that of agricultural areas, and the mortality rate in disaster years is as high as 24%. Yak insurance has become the most important barrier against these risks. Existing yak insurance cannot monitor various data of yaks in real time during their growth process, so as to achieve the effect of prevention and control.

[0076] IV. Economic Value-Added Needs: Digital traceability, brand building, and financial and insurance support are required.

[0077] V. Insufficient communication coverage: The plateau pastoral areas are vast and sparsely populated, with poor cellular network coverage, resulting in frequent communication interruptions for traditional IoT devices;

[0078] VI. Severe data silos: Data from breeding, disease prevention, trading, and finance are not integrated, and there is a lack of a unified and reliable data platform;

[0079] VII. Difficulty in Valuing Live Assets: As biological assets, yaks lack dynamic and objective valuation models, leading to difficulties in financing and insurance.

[0080] 8. Management relies on experience: estrus period judgment, disease warning, and slaughter decision-making rely heavily on human experience and lack AI-driven accurate predictive capabilities;

[0081] 9. Low credibility of traceability: Existing traceability systems are easily tampered with and centralized, making it difficult to support brand premium and financial risk control.

[0082] In response to the above issues, the main needs of yak farming are: to establish a complete digital traceability system to ensure quality; to create a high-end brand so that good cattle can fetch good prices; and to introduce financial insurance to protect returns and reduce risks.

[0083] Based on this, the main technical concept of this application includes: uniting upstream and downstream ecosystem partners in the industry to create a yak digital solution, integrating technologies such as the Internet of Things, artificial intelligence, blockchain, digital native, and big data, and combining them with the characteristics of the yak industry to enable secure sharing of digital assets across the entire industry, in order to solve the problems of yak positioning, scientific management, and economic value-added.

[0084] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0085] Figure 1 This is a schematic diagram of an artificial intelligence-based digital intelligent yak farming system provided in an embodiment of this application. Figure 2 A digital schematic diagram of a yak provided in the embodiments of this application, such as Figure 1 as well as Figure 2 As shown, this application provides a digital intelligent yak farming system based on artificial intelligence, the system comprising:

[0086] The terminal device communication module includes an adaptive handover mechanism unit for data communication via satellite network or cellular network;

[0087] The digital identity module includes an tamper-proof yak collar with a blockchain security chip, a real-time positioning unit, an electronic fence unit, a trajectory playback unit, and a ranch management unit;

[0088] The automatic weighing and grouping module includes a grouping rule engine unit that dynamically generates grouping instructions based on individual yak weight information and a preset multi-objective optimization model;

[0089] The pasture environment monitoring module is used to monitor meteorological parameters of the grassland environment in real time.

[0090] The breeding management module is used for data-driven monitoring and event early warning of yak growth, reproduction, health, and feeding processes;

[0091] The disease prevention and health care module is used to analyze information on yaks' diseases, immunization, quarantine, and health care.

[0092] The breeding stock management module is used for digital monitoring, production performance testing, and breeding pedigree management of breeding bulls and cows;

[0093] The large-scale aquaculture model module is used to generate production early warnings and guidance suggestions;

[0094] The supply chain traceability module is used to provide digital service support for the yak breeding supply chain process through blockchain and encryption algorithms;

[0095] The quality traceability and monitoring module is used to supervise standardized breeding processes and trace the yak information chain through blockchain.

[0096] The asset trust supervision and financial services module is used to provide secure and trustworthy livestock ledger services for financial financing and insurance businesses. It uses yak life cycle data as a basis for credit, conducts value assessment and risk pricing of yaks, and outputs trustworthy asset valuation reports.

[0097] The biological asset service ecosystem module is used to establish traceability information for the yak industry among breeders, governments, financial institutions, traders, consumers, and regulators, and to build a regulatory service ecosystem.

[0098] In some embodiments, the adaptive switching mechanism unit is used to continuously monitor the Received Signal Strength Indicator (RSSI) of the cellular network. When the RSSI of the cellular network is lower than a preset threshold and the duration reaches a preset duration, it switches to LoRaWAN mode to upload communication data to the gateway so that the gateway can transmit communication data back via satellite. When the RSSI of the cellular network is higher than or equal to the preset threshold, it switches to the cellular network for data communication.

[0099] In this application, the terminal device's communication module, leveraging the wide coverage of satellites to supplement cellular communication, addresses the issue of inaccessible terrestrial cellular networks in remote and geographically complex grassland and pasture areas. This module features an adaptive switching mechanism unit for "LoRaWAN + Satellite / Cellular," embedding a signal strength detection algorithm and communication protocol stack. When the cellular network signal strength falls below a preset threshold, the module automatically switches to LoRaWAN mode to upload data to the gateway, which then transmits it back via satellite. When entering cellular network coverage, it automatically switches back to cellular network to reduce power consumption and communication costs. This solution overcomes the limitations of a single communication method, achieving a balance between high coverage, low power consumption, and cost-effectiveness.

[0100] Specifically, Figure 3 This is a schematic diagram of the communication architecture of the terminal device according to an embodiment of this application, such as... Figure 3 As shown, the terminal device's communication module, leveraging the wide coverage of satellites to supplement cellular communication, employs LoRaWAN + satellite / cellular to achieve ubiquitous signal coverage, extending from fenced areas to vast natural pastures. The satellite terminal connects to a LoRaWAN gateway, bridging the last ten kilometers of the satellite Internet of Things and building ubiquitous LoRaWAN + cellular / satellite network coverage.

[0101] The adaptive switching mechanism unit operates as follows: it continuously monitors the Received Signal Strength Indication (RSSI) of the cellular network; when the RSSI remains below a set threshold (e.g., -110dBm) for more than time T (e.g., 5 minutes), it controls the communication module to switch to LoRaWAN mode and sends data to the LoRaWAN gateway. Specifically, if RSSI < -110dBm for 5 minutes, it switches to LoRaWAN; the gateway transmits the aggregated data back to the cloud platform via its built-in satellite communication module or when it moves to a cellular network coverage area; when the module detects that the cellular network RSSI is higher than the recovery threshold (e.g., -95dBm), it automatically switches back to the cellular network to reduce overall power consumption.

[0102] In some embodiments, the tamper-proof yak collar generates an asymmetric encryption key pair at the time of manufacture, wherein the private key is permanently stored in the blockchain security chip and cannot be exported, and the public key and a unique digital identity identifier are anchored and registered on the blockchain.

[0103] The tamper-proof yak collar is equipped with sensors that collect the yak's status in real time. The sensor data emitted from the tamper-proof yak collar is signed with the private key and verified with the public key.

[0104] In this application, the tamper-proof yak collar is a smart collar with a blockchain security chip, which ensures data trustworthiness from the hardware level, is used to uniquely identify the source of the data, establishes a system for verifying the identity and continuously recording the target throughout its entire life cycle, and realizes the uniqueness and traceability management of the target.

[0105] Specifically, the digital identity module assigns a unique digital identity to each yak and uses electronic ear tags / collars to uniquely identify the data source, establishing a system for verifying the identity and continuously recording the entire lifecycle of the yak, thus achieving uniqueness and traceability management. The tamper-proof yak collar integrates a Beidou / GPS dual-mode positioning chip, a body temperature sensor, a three-axis accelerometer (for activity monitoring), and a built-in blockchain hardware security module (HSM) for generating and storing unique digital identity keys.

[0106] The tamper-proof yak collar incorporates a blockchain hardware security module (HSM). Upon manufacturing, it generates an asymmetric encryption key pair. The private key is permanently stored within the HSM and cannot be exported. The public key, along with its generated unique digital identity identifier (such as a DID), is registered and anchored on the blockchain. All sensor data emitted from the collar is signed using this private key. When the sensor data is transmitted to the data platform, the platform verifies the signature using the public key. If the verification passes, the data is written to the blockchain for later retrieval. If the verification fails, the data is lost, thus ensuring the authenticity and non-repudiation of the data source. Examples include sensor accuracy (body temperature ±0.1℃, positioning error <5m) and the HSM encryption algorithm (ECC256).

[0107] The tamper-proof yak collar can collect data such as body temperature and activity level. For cow herds, it can also collect data on rumination and estrus, enabling yak status monitoring and health status early warning and management through data analysis. The aforementioned digital identification can be customized with monitoring items for different groups and purposes.

[0108] For example, the following is a detailed description of the tamper-proof yak collar:

[0109] .

[0110] In some embodiments, the real-time positioning unit is used to report the location of the yak in real time;

[0111] Specifically, the real-time positioning unit updates the location in real time based on the location reported by the locator (electronic ear tag / collar) to realize a yak distribution view: for herders or owners to monitor the overall distribution of cattle in real time, and to monitor cattle approaching or exceeding the permitted area; to realize cattle location tracking: to track the location of lost cattle in a timely manner for lost cattle retrieval; and to view the pastures where specific cattle are grazed for tracing their origin.

[0112] In some embodiments, the electronic fence unit is used to provide early warnings for yaks exceeding the fence, early warnings for yaks entering the fence, and automatic inventory checks within the fence for key areas;

[0113] Specifically, the electronic fence unit is set up for key areas, such as pens and pastures, to provide early warnings and inventory checks. It enables warnings for yaks exceeding the fence: such as warnings for grazing beyond permitted pastures, to prevent yaks from wandering off or entering roads or municipal areas; warnings for yaks entering the fence: such as warnings for entering prohibited pastures, to ensure proper grazing and prevent damage to the pasture ecosystem; and automatic inventory checks within the pen: such as inventory checks upon entry into the pen and warnings for cattle not yet in the pen.

[0114] In some embodiments, the trajectory review unit is used to draw the historical movement trajectory of the yak based on historical location information;

[0115] Specifically, the trajectory review unit can draw historical movement trajectories based on historical location information to achieve cattle location tracking: based on the historical trajectory, the breeding site of the cattle's growth process can be viewed and its breeding method can be determined (which can be combined with activity level) for tracing the source; it can also predict the direction of the cattle's movement and current location based on the historical trajectory.

[0116] In some embodiments, the ranch management unit is used to realize cattle distribution, cattle inventory, dynamic files, cattle herd structure, cattle herd analysis, and production reports.

[0117] Specifically, the ranch management unit enables cattle distribution, cattle inventory, dynamic records, herd structure, herd analysis, and production reports, providing farmers / ranch owners with operational visualization and decision-making support.

[0118] In this application, the digital identity module includes a real-time positioning unit that updates the location instantly based on the location reported by the locator. The digital identity module also includes an electronic fence unit, set up for key areas such as pens and pastures, to prevent yaks from getting lost or wandering onto roads or into municipal areas, addressing issues such as reasonable grazing and preventing grassland ecological damage. Furthermore, the digital identity module includes a trajectory review unit, which draws historical movement trajectories based on historical location information for traceability and cattle tracking. Finally, the digital identity module includes a pasture management unit, enabling cattle distribution, inventory, dynamic records, herd structure, herd analysis, and production reports, providing farmers / ranchers with operational visualization and decision-making support.

[0119] In this application, an automatic weighing and grouping module is used to acquire individual weight information and upload it to the yak digital system. Based on weight changes, feeding efficiency can be accurately evaluated, and the optimal economic slaughter rate for each individual can be dynamically determined. This module is equipped with a grouping rule engine unit, which receives weight data from the automatic weighing module and age and health status data (such as abnormal body temperature markers) from the digital identity module. Based on a preset multi-objective optimization model (such as optimizing slaughter efficiency and group health), it dynamically generates grouping instructions and controls the intelligent grouping gate actuator. This application realizes multi-data source-driven, dynamic, and intelligent grouping management.

[0120] In some embodiments, the grouping rule engine unit is used to obtain the individual weight information of yaks obtained through the automatic weighing system, dynamically generate grouping instructions based on a preset multi-objective optimization model, and transmit the grouping instructions to the intelligent grouping gate to group the yaks.

[0121] The objective function used in the multi-objective optimization model is:

[0122] Max slaughter efficiency = α·weight achievement rate + β·health index - γ·group cost;

[0123] Where α is the weight of the weight achievement rate, β is the weight of the health index, and γ is the weight of the group cost.

[0124] Specifically, the automatic weighing and grouping module installs an automatic weighing system on the individual cattle's passageway. It identifies the animal's electronic tag, obtains individual weight information, and uploads it to the yak digital breeding system via the terminal device's communication module. Based on weight changes, it can accurately evaluate feeding efficiency and dynamically determine the optimal economic slaughter time for each animal. Based on comprehensive data analysis, grouping rules are formulated with reference to factors such as weight class, age at birth, sick animals, slaughter time, culling, and waiting for mating. Instructions are transmitted to the intelligent grouping gate, automatically grouping animals into groups with similar conditions, thus improving breeding efficiency.

[0125] In some embodiments, the pasture environment monitoring module is used to monitor the temperature and humidity, wind speed, wind direction, rainfall, air pressure, photosynthetic radiation, evaporation, and soil temperature and humidity of the pasture environment in real time.

[0126] In this application, the pasture environment monitoring module is used to monitor various meteorological parameters in real time, such as grassland temperature and humidity, wind speed, wind direction, rainfall, air pressure, photosynthetic radiation, evaporation, and soil temperature and humidity; it integrates multiple meteorological parameter sensors and combines them with soil moisture data so that the risk of grassland degradation can be predicted through AI models; all kinds of monitoring equipment adopt solar energy + low power consumption design to adapt to the extreme environment of the plateau.

[0127] Specifically, the pasture environment monitoring module operates stably in various harsh outdoor environments, featuring low power consumption, high stability, high precision, and unattended operation. It can monitor various meteorological parameters in real time, including pasture temperature and humidity, wind speed, wind direction, rainfall, air pressure, photosynthetic radiation, evaporation, and soil temperature and humidity. Data communication utilizes a satellite / cellular communication module based on terminal devices, primarily composed of meteorological sensors, a power system, a field protection box, a stainless steel support frame, and solar power panels. Combined with location information and electronic fence data, it monitors the yak's living environment, supplemented by pasture variety and forage quality testing reports for traceability; and it also assists in pasture ecological management.

[0128] In this application, the breeding management module is used to monitor and warn of events related to growth, reproduction, health, and feeding processes through digitalization, thereby facilitating refined breeding. For example, a blockchain smart contract example is that when the body temperature is >40℃ and the activity level decreases by 50%, an early warning is automatically triggered and recorded on the blockchain.

[0129] In this application, the disease prevention and health care module is used to analyze disease, immunization, quarantine, and health care information and reports, and to efficiently protect the health of cattle by connecting with the government's disease prevention system and combining health early warning.

[0130] In this application, the livestock management module is used to increase digital monitoring of breeding bulls and cows, production performance testing, breeding pedigree management, etc., to improve the quality of the herd and prevent degradation.

[0131] Specifically, the breeding stock management module improves herd quality and prevents degradation by establishing yak pedigrees, increasing digital monitoring of breeding bulls and cows, measuring production performance, and managing reproductive pedigrees. It also monitors rumination and estrus data (for cows) and uses AI to analyze the reproductive cycle.

[0132] In some embodiments, the large-scale breeding model module is used to predict the estrus cycle, disease warning, and optimal slaughter period of yaks through a pre-trained network model, and generate production warnings and guidance suggestions based on the prediction results.

[0133] Specifically, the large-scale breeding model module collects data in real time based on the terminal device communication module. It utilizes machine learning to train, fine-tune, and iterate the data generated by the various modules, performing in-depth mining and analysis of yak data to generate production early warnings and guidance suggestions. Specifically, based on the Transformer architecture, it is pre-trained on massive amounts of yak behavior and physiological data, and fine-tuned for local pastures; it achieves estrus prediction (monitoring estrus behavior through AI cameras during the mating stage, with an accuracy rate ≥90%), early disease warning (identifying abnormal behavior 3-5 days in advance), and optimal slaughter period recommendation (considering weight gain, feed conversion rate, and market price trends), pushing actionable suggestions to farmers via APP / SMS. It introduces a machine learning-driven dynamic value assessment and risk pricing model, incorporating growth curves, health status, and market conditions into credit criteria.

[0134] In this application, the supply chain traceability module is used to integrate industry ecosystem partner resources, provide comprehensive digital service support for the core business processes of animal husbandry, and provide guarantees for the standardization, digitalization and intelligentization of the industry. It integrates comprehensive data and industry knowledge around breeding livestock, feed, disease prevention and control, fattening, slaughtering and transaction management.

[0135] In some embodiments, the supply chain traceability module is used to provide digital service support for the breeding stock, feed, disease prevention and control, fattening, slaughtering and transaction management processes of yak farming through blockchain and encryption algorithms;

[0136] Specifically, Figure 4 This is a schematic diagram of the digital transformation of the yak industry chain according to an embodiment of this application, such as... Figure 4 As shown, the aforementioned supply chain traceability utilizes sensor collection (hardware system) and IoT transmission and processing (cloud service) to extend upstream and collect data from the entire supply chain, including planting, breeding, raising, processing, and operation. Among these:

[0137] When in the "seed" stage of the industrial chain: integrate breeding data, monitor estrus, and breed.

[0138] When the industry chain is in the "development" stage: integrate feeding data, measurement data, and evaluation data;

[0139] When the industry chain is in the "nurturing" stage: integrate filing information, status monitoring, quarantine information, weighing information, slaughtering information, and early warning;

[0140] When in the "addition" stage of the industrial chain: integrate information on market entry, origin, slaughtering, processing, and packaging;

[0141] When in the "operation" stage of the industrial chain: integrate order information, batch information, logistics information, and QR code traceability.

[0142] In this application, the supply chain traceability module captures data from the entire livestock supply chain, employs encryption algorithms, and implements information security classifications to ensure data immutability. By establishing a traceability system, information is searchable, the source is traceable, and production and consumption are mutually trusted and recognized, ensuring product quality and safety. Furthermore, by establishing a promotional system, the application cultivates and strengthens leading brands, emphasizing the development of standardized organic production bases and green organic products, highlighting the unique value of regional yak breeds, breeding methods, and natural pastures, thereby enhancing the influence of local brands.

[0143] The specific nodes and processes for data on-chain: From birth, immunization, feeding, exercise to slaughter / trading, key event data is uploaded to the blockchain in real time, using a consortium blockchain (such as Hyperledger Fabric). Nodes include ranches, veterinary stations, financial institutions, and regulators, providing credible evidence for insurance claims, movable property mortgages, and carbon footprint certification. For example: "At each key node in the industry chain, electronic ear tags are scanned using handheld terminals to identify the digital identity, and the structured data of that node (such as: slaughtering - time, location, weight, quarantine officer ID; slaughtering - slaughterhouse ID, aging time; quality inspection - quality inspection report hash value) is bound to that digital identity. Transaction hashes are generated through a blockchain gateway and written to the blockchain. When consumers scan the product's QR code, they can access this immutable, end-to-end record." Compared to existing traceability systems, this application uses blockchain technology to ensure the immutability and credibility of data from source to end, providing a technological foundation for brand value enhancement and financial empowerment.

[0144] In this application, the quality traceability and monitoring module, by supervising standardized breeding processes, tracing the yak information chain, and analyzing big data on yaks across the entire region, connects all participants in the yak breeding industry, promotes deep integration among all parties in the industry, and optimizes the industry structure.

[0145] Specifically, the quality traceability and monitoring module establishes standardized breeding processes and achieves digital management of yak immunization and quarantine across the county through ear tags, thereby realizing breeding supervision. Yaks automatically upload traceability information to the blockchain, building a trusted foundation for regional high-end yak product brands and ensuring reliable data traceability. Big data enables intelligent analysis of yak inventory, sales, breeding profits, quality and safety across the entire region, assisting the government in making precise decisions. It connects all participants in the yak breeding industry, promoting deep integration among all parties and optimizing the industrial structure to improve efficiency.

[0146] In this application, the asset trust supervision and financial services module, through livestock terminals, links data from the data source to the blockchain, capturing data from the entire livestock industry chain, using encryption algorithms and information security classifications to ensure data security and prevent tampering. This creates a trustworthy digital yak system, enabling the management, traceability, and sharing of yak lifecycle data, providing secure and reliable livestock ledger services for core aspects of financial financing and insurance. This is a significant measure to empower traditional industries with cutting-edge technology, solve the challenges of live animal asset collateral, actively explore rural digital inclusive finance, and promote rural revitalization. The module includes a biological asset collateral model unit, using yak lifecycle data as the basis for lending. For example, "This model uses yak lifecycle data (breed, weight gain curve, health history, pedigree) as input features, and uses machine learning algorithms (such as random forests or gradient boosting trees) to assess the value and risk of yaks, outputting a trustworthy asset valuation report as the core basis for financial institutions to lend; combining IoT data, AI models, and blockchain trustworthy data creatively solves the core pain points of 'difficult valuation and risk control' in live animal asset collateral."

[0147] In some embodiments, the asset trust supervision and financial services module achieves blockchain gateway on-chain through tamper-proof yak collars to establish global blockchain management from the data source to the cloud server. Key on-chain nodes include breeding, feeding, weighing, quarantine, slaughtering, quality inspection, and orders.

[0148] Specifically, Figure 5 This is a schematic diagram illustrating the trusted asset supervision and financial services of an embodiment of this application, as shown below. Figure 5 As shown, the asset trust supervision and financial service module utilizes tamper-proof collars / ear tags to upload data to the blockchain via a fully connected communication network and a blockchain gateway. It identifies key on-chain nodes (breeding → weighing → quarantine → slaughter → quality inspection), establishing a global blockchain management system from the data source to the cloud server, achieving data security and immutability. With the tamper-proof collars / ear tags as the core, it uniquely identifies the data source, establishing a system for verifying the identity and continuously recording the entire lifecycle of the asset, achieving uniqueness and traceability management.

[0149] Input variables include daily weight gain, activity level, body temperature fluctuations, vaccination records, and historical transaction prices. Algorithms used include integrating XGBoost / LSTM for time-series value prediction and combining Monte Carlo simulation for risk pricing, enabling bank credit line calculation, dynamic adjustment of insurance premiums, and valuation of living collateral.

[0150] In this application, the specific logic for triggering claims using a blockchain smart contract is as follows: when the health data of a yak is abnormal, the insurance verification process is automatically initiated.

[0151] Through the aforementioned technological means, financial institutions, insurance companies, guarantee institutions, and slaughtering enterprises can leverage cutting-edge technologies to empower the yak breeding industry, solve the problem of mortgaging live yak assets, and establish a credible supervision and financial service platform for livestock farmers' biological assets.

[0152] This application uses livestock terminals to connect data sources to the blockchain, ensuring data security and immutability, creating a trustworthy digital yak system, and enabling the management, traceability, and sharing of yak lifecycle data. This provides secure and reliable livestock ledger services for core business processes such as financial financing and insurance.

[0153] In this application, the biological asset service ecosystem module is used to connect yak industry traceability information among breeders, governments, financial institutions, traders, consumers, and regulators, and to establish a regulatory service ecosystem.

[0154] Specifically, Figure 6 This is a schematic diagram of the yak biological asset service ecosystem according to an embodiment of this application, such as... Figure 6 As shown, the biological asset service ecosystem module utilizes the aforementioned technical means to construct a yak biological asset service ecosystem, thereby connecting yak farmers, governments, financial institutions, traders, consumers, and regulators to trace yak industry information and establish a regulatory service ecosystem.

[0155] Based on the above-mentioned digital and intelligent yak farming, this application provides a digital and intelligent yak farming method based on artificial intelligence. Figure 7 A schematic diagram of an artificial intelligence-based digital intelligent yak farming method provided in this application embodiment, as shown below. Figure 7 As shown, the method includes:

[0156] S1. Based on an adaptive handover mechanism, data communication is conducted via satellite network or cellular network;

[0157] Specifically, terminal device communication, with the help of the wide coverage of satellites, supplements cellular communication and solves the problem of the inaccessibility of ground cellular networks in grasslands and pastures in remote and complex terrain areas.

[0158] S2. The yak breeding and management system uses a tamper-proof yak collar with a blockchain security chip, a real-time positioning unit, an electronic fence unit, a trajectory playback unit, and a pasture management unit.

[0159] Specifically, digital identity identification uniquely identifies the source of data, establishing a system for verifying the identity and continuously recording the entire lifecycle of the asset, achieving uniqueness and traceability management. It enables real-time positioning, trajectory review, and pasture management functions. This is used to prevent yaks from getting lost or wandering onto roads or into municipal areas, addressing issues such as reasonable grazing and preventing grassland ecological damage; for traceability and cattle tracking; and to provide operational visualization and decision-making support for farmers / ranchers, including cattle distribution, inventory, dynamic records, herd structure, herd analysis, and production reports.

[0160] S3. Based on the individual weight information of yaks and a preset multi-objective optimization model, dynamically generate a grouping instruction and issue the grouping instruction to group the yaks.

[0161] Specifically, automatic weighing and grouping can obtain individual weight information. Based on weight changes, feeding efficiency can be accurately evaluated, and the optimal economic slaughter rate for each individual can be dynamically determined.

[0162] S4. Real-time monitoring of meteorological parameters of the grassland environment;

[0163] Specifically, pasture environmental monitoring involves real-time monitoring of various meteorological parameters such as pasture temperature and humidity, wind speed, wind direction, rainfall, air pressure, photosynthetic radiation, evaporation, and soil temperature and humidity.

[0164] S5. Conduct data-driven monitoring and event early warning of the growth, breeding, health, and feeding process of yaks;

[0165] Specifically, in aquaculture management, digital monitoring and early warning of growth, reproduction, health, and feeding processes are used to support refined aquaculture.

[0166] S6. Analyze information on yak diseases, immunization, quarantine, and health care;

[0167] Specifically, in terms of disease prevention and health care, we analyze information and reports on diseases, immunization, quarantine, and health care, and efficiently safeguard the health of cattle by connecting with the government's disease prevention system and combining it with health early warning systems.

[0168] S7. Digital monitoring, production performance testing, and breeding pedigree management of breeding bulls and cows;

[0169] Specifically, in livestock management, digital monitoring of breeding bulls and cows will be increased, along with production performance testing and breeding pedigree management, to improve the quality of the herd and prevent degradation.

[0170] S8. Generate production early warnings and guidance suggestions;

[0171] Specifically, the large-scale aquaculture model generates production early warnings and guidance suggestions.

[0172] S9. Provide digital service support for the yak breeding industry chain through blockchain and encryption algorithms;

[0173] Specifically, it involves supply chain traceability, integrating industry ecosystem partner resources, providing comprehensive digital service support for the core business processes of animal husbandry, and ensuring the standardization, digitalization, and intelligentization of the industry. It also involves comprehensive data and industry knowledge integration around breeding stock, feed, disease prevention and control, fattening, slaughtering, and transaction management.

[0174] S10. Use blockchain to monitor standardized breeding processes and trace yak information chains;

[0175] Specifically, quality traceability and monitoring involve regulating standardized breeding processes, tracing the yak information chain, and analyzing big data on yaks across the entire region to connect all participants in the yak breeding industry, promote deep integration among all parties in the industry, and optimize the industrial structure.

[0176] S11. Provide secure and reliable livestock ledger services for financial financing and insurance businesses, use yak life cycle data as a basis for credit, conduct value assessment and risk pricing of yaks, and output reliable asset valuation reports.

[0177] Specifically, the project aims to provide trusted asset supervision and financial services by connecting livestock data to the blockchain via livestock terminals. This ensures data security and immutability, creating a trusted digital system for yaks. It enables the management, traceability, and sharing of yak lifecycle data, providing secure and reliable livestock ledger services for core aspects of financial financing and insurance. This is a crucial measure to leverage cutting-edge technology to empower traditional industries, solve the challenges of using live animal assets as collateral, actively explore inclusive digital finance in rural areas, and promote rural revitalization.

[0178] S12. Establish a traceability information system for the yak industry, involving breeders, government, financial institutions, traders, consumers, and regulators, and build a regulatory service ecosystem.

[0179] Specifically, we will establish a biological asset service ecosystem, connect yak farmers, governments, financial institutions, traders, consumers, and regulators to trace yak industry information, and build a regulatory service ecosystem.

[0180] This application integrates technologies such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, digital native technologies, and big data, combined with the characteristics of the yak industry, to connect upstream and downstream ecosystem partners and create a digital solution for yaks. It aims to achieve secure sharing of digital assets across the entire industry, addressing issues related to yak location, scientific management, and economic value enhancement. For the vast grassland pastures where clients are located, a "full-coverage" LoRaWAN + satellite / cellular IoT connectivity service has been built, bridging the last ten kilometers of satellite IoT and solving the problem of inaccessible terrestrial cellular networks in remote and geographically complex grassland pastures. A customized LoRaWAN collar for yaks has been developed, integrating digital identity identification, location tracking, activity level monitoring, and body temperature measurement, forming the foundation for "digital yaks." A fully reliable traceability system has been established for all stages of breeding, raising, raising, slaughtering, processing, and nutrition, highlighting the unique value of grassland yaks: breed, breeding methods, grassland environment and forage quality, growth records, meat quality testing, etc., supporting brand building. A reliable biological asset supervision and financial service system has been established to provide secure and reliable livestock ledger services for core aspects of financial financing and insurance businesses. By connecting to the new marketing system, it provides reliable traceability data for various marketing methods such as online and offline sales, live streaming, and pre-sales of tourism, thereby realizing the added value of yak products and has systematic and comprehensive advantages.

[0181] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0182] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of this application, and this application is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this application, and these modifications and improvements are also considered to be within the scope of protection of this application.

Claims

1. A digital intelligent yak farming system based on artificial intelligence, characterized in that, The system includes: The terminal device communication module includes an adaptive handover mechanism unit for data communication via satellite network or cellular network; The digital identity module includes an tamper-proof yak collar with a blockchain security chip, a real-time positioning unit, an electronic fence unit, a trajectory playback unit, and a ranch management unit; The automatic weighing and grouping module includes a grouping rule engine unit that dynamically generates grouping instructions based on individual yak weight information and a preset multi-objective optimization model; The pasture environment monitoring module is used to monitor meteorological parameters of the grassland environment in real time. The breeding management module is used for data-driven monitoring and event early warning of yak growth, reproduction, health, and feeding processes; The disease prevention and health care module is used to analyze information on yaks' diseases, immunization, quarantine, and health care. The breeding stock management module is used for digital monitoring, production performance testing, and breeding pedigree management of breeding bulls and cows; The large-scale aquaculture model module is used to generate production early warnings and guidance suggestions; The supply chain traceability module is used to provide digital service support for the yak breeding supply chain process through blockchain and encryption algorithms; The quality traceability and monitoring module is used to supervise standardized breeding processes and trace the yak information chain through blockchain. The asset trust supervision and financial services module is used to provide secure and trustworthy livestock ledger services for financial financing and insurance businesses. It uses yak life cycle data as a basis for credit, conducts value assessment and risk pricing of yaks, and outputs trustworthy asset valuation reports. The biological asset service ecosystem module is used to establish traceability information for the yak industry among breeders, governments, financial institutions, traders, consumers, and regulators, and to build a regulatory service ecosystem.

2. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The adaptive switching mechanism unit is used to continuously monitor the Received Signal Strength Indicator (RSSI) of the cellular network. When the RSSI of the cellular network is lower than a preset threshold and the duration reaches a preset duration, it switches to LoRaWAN mode to upload communication data to the gateway so that the gateway can transmit communication data back via satellite. When the RSSI of the cellular network is higher than or equal to the preset threshold, it switches to the cellular network for data communication.

3. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The tamper-proof yak collar generates an asymmetric encryption key pair at the time of manufacture. The private key is permanently stored in the blockchain security chip and cannot be exported, while the public key and the unique digital identity identifier are anchored and registered on the blockchain. The tamper-proof yak collar is equipped with sensors that collect the yak's status in real time. The sensor data emitted from the tamper-proof yak collar is signed with the private key and verified with the public key.

4. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The real-time positioning unit is used to report the yak's location in real time; The electronic fence unit is used to provide early warnings for yaks exceeding the fence, early warnings for yaks entering the fence, and automatic inventory checks within the fence in key areas. The trajectory review unit is used to draw the historical movement trajectory of the yak based on historical location information; The ranch management unit is used to realize cattle distribution, cattle inventory, dynamic files, cattle herd structure, cattle herd analysis, and production reports.

5. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The grouping rule engine unit is used to obtain the individual weight information of yaks obtained through the automatic weighing system, dynamically generate grouping instructions based on a preset multi-objective optimization model, and transmit the grouping instructions to the intelligent grouping gate to group the yaks. The objective function used in the multi-objective optimization model is: Max slaughter efficiency = α·weight achievement rate + β·health index - γ·group cost; Where α is the weight of the weight achievement rate, β is the weight of the health index, and γ is the weight of the group cost.

6. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The pasture environment monitoring module is used to monitor the temperature, humidity, wind speed, wind direction, rainfall, air pressure, photosynthetic radiation, evaporation, and soil temperature and humidity of the pasture environment in real time.

7. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The large-scale breeding model module is used to predict the estrus cycle, disease warning, and optimal slaughter time of yaks through a pre-trained network model, and to generate production warnings and guidance suggestions based on the prediction results.

8. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The supply chain traceability module is used to provide digital service support for the breeding, feed, disease prevention and control, fattening, slaughtering and transaction management processes of yak farming through blockchain and encryption algorithms; Among them, when in the "seed" stage of the industrial chain: integrating breeding data, estrus monitoring, and mating and breeding; When the industry chain is in the "incubation" stage: integrate feeding data, measurement data, and evaluation data; When in the "nurturing" stage of the industrial chain: integrate filing information, status monitoring, quarantine information, weighing information, slaughtering information, and early warning; When in the "addition" stage of the industrial chain: integrate information on market entry, origin, slaughtering, processing, and packaging; When in the "operation" stage of the industrial chain: integrate order information, batch information, logistics information, and QR code traceability.

9. The yak digital intelligent breeding system based on artificial intelligence according to claim 1, characterized in that, The asset trust supervision and financial services module uses the tamper-proof yak collar to achieve blockchain gateway on-chain, so as to establish a global blockchain management from the data source to the cloud server. The key on-chain nodes include breeding, feeding, weighing, quarantine, slaughtering, quality inspection, and orders.

10. A digital intelligent yak farming method based on artificial intelligence, characterized in that, The method includes: Based on an adaptive handover mechanism, data communication is conducted via satellite network or cellular network; The yak breeding and management system employs tamper-proof yak collars with blockchain security chips, real-time positioning units, electronic fence units, trajectory playback units, and pasture management units. Based on the individual weight information of yaks and a preset multi-objective optimization model, a grouping instruction is dynamically generated and issued to group the yaks. Real-time monitoring of meteorological parameters of the grassland environment; Data-driven monitoring and event early warning of yak growth, reproduction, health, and feeding processes; Analyze information on yak diseases, immunization, quarantine, and health care; Digital monitoring, production performance testing, and breeding pedigree management of breeding bulls and cows; Generate production early warnings and guidance suggestions; Providing digital service support for the yak farming industry chain through blockchain and encryption algorithms; Standardized breeding processes are monitored and yak information is traced through blockchain technology. Provide secure and reliable livestock ledger services for financial financing and insurance businesses, use yak life cycle data as a basis for credit, conduct yak value assessment and risk pricing, and output reliable asset valuation reports; Establish a traceability system for the yak industry, involving breeders, government, financial institutions, traders, consumers, and regulators, and create a regulatory service ecosystem.

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