Traceable management system and method based on aquaculture industry service platform

Abstract

The invention relates to the technical field of data management systems and methods of classification numbers G06Q, and provides a traceable management system and method based on an aquaculture industry service platform. Comprising a server, a mobile data anchoring device, a detachable traceability label module, a life cycle state management module, an event hash and anchor verification module and a block chain intelligent verification module. The detachable traceability label module is used for identifying the identity and life cycle state of a breeding individual and triggering a state change event in a disassembly behavior; the mobile data anchoring device collects data of the key node and forms an anchor point record; the life cycle state management module maintains a life cycle logic state diagram of each individual and verifies whether uploading of all events is compliant or not; the event hash and anchor verification module encapsulates all behavior nodes into a structured hash event, and compares and verifies the structured hash event with a current state diagram to form a credible anchor; and the block chain intelligent verification module performs contract-level verification on the event hash and the state path.

Description

Technical Field

[0001] The present invention relates to the technical field of data management systems and methods for G06Q classification numbers, and in particular to a traceable management system and method based on a breeding industry service platform. Background Art

[0002] The existing livestock farming industry faces challenges in data fragmentation, unverifiable information, and difficult accountability processes throughout the entire animal husbandry process, from breeding and pen transfer to transportation and slaughter. This is particularly true for food safety and traceability, as traditional systems rely on static tags and isolated records, lacking a unified, trusted platform. This makes it difficult for consumers to obtain complete and authentic information about the supply chain.

[0003] For example, the mobile terminal-based aquaculture traceability system disclosed in Chinese patent CN107222535A can trace the aquaculture process through mobile terminals, but it cannot achieve full tracking of the entire industry, resulting in a lack of persuasiveness in the security and reliability of the data.

[0004] In addition, the prior art also has the following defects: 1. The tag structure is simple and the life cycle cannot be distinguished. The same tag is used throughout the entire life cycle. The system cannot identify the individual status changes from "breeding" to "transporting" to "selling". If the tag is illegally replaced or removed prematurely, the system cannot identify or prevent it. 2. The data collection process is broken, and the point of responsibility is unclear. Once a problem occurs, it is difficult to pinpoint the specific link and individual responsible, making it impossible to establish a true chain of evidence for accountability. 3. Consumers have no way of verifying whether their data has been tampered with, and the platform lacks "non-repudiation"; 4. Tagging behavior is disconnected from system status; 5. Process information is not uploaded to the chain, and data trust is low. Most platform data links only form a traceability QR code in the product packaging link. The front-end data is manually imported and lacks process verifiability and non-tamperability.

[0005] The present invention is made to solve the common problems in this field, such as poor full name supervision capability, inability to ensure security, inability to ensure non-tampering, disconnection between labels and system status, and single label structure. Summary of the Invention

[0006] The purpose of the present invention is to address the current deficiencies and propose a traceability management system and method based on a breeding industry service platform.

[0007] In order to overcome the deficiencies of the prior art, the present invention adopts the following technical solutions: A traceability management system based on an aquaculture industry service platform, comprising a server and a mobile data anchoring device. The traceability management system also includes a detachable traceability tag module, a lifecycle state management module, an event hash and anchor point verification module, and a blockchain intelligent verification module. The detachable traceability tag module is used to identify the identity and life cycle status of the breeding individual and trigger a state change event during the disassembly behavior; The mobile data anchoring device collects data of key nodes and forms anchor point records; The lifecycle state management module maintains the lifecycle logical state diagram of each individual and verifies whether all event uploads are compliant; The event hash and anchor point verification module encapsulates all behavior nodes into structured hash events, compares and verifies them with the current state graph, and forms a trusted anchor point; The blockchain intelligent verification module performs contract-level verification on the event hash and state path, and only after passing the verification can it be stored on the blockchain to form a traceability chain. Optionally, the detachable traceability tag module includes a tag structure unit, a state chip, a unique ID encoder, and an anti-disassembly detection unit. The tag structure unit constructs a detachable but stably connected physical tag structure, so that the tag is firmly bound to the individual during the breeding stage, and can be disassembled and retain some information for product stage display and traceability after being marketed; the state chip records the current life cycle state of the tag and automatically switches the state bit when the physical behavior changes; the unique ID encoder assigns a unique identity number to each tag to ensure that it is bound to the individual animal files that exist and are bred in the database; the anti-disassembly detection unit is used to identify whether the tag has been illegally disassembled or destructively removed. If illegal disassembly or destructive removal occurs, the system should be able to identify and mark it as a risk event; The label structure unit includes a first label segment and a second label segment. The first label segment is bound to the animal during the breeding period and has an internal integrated status chip and a unique ID encoder. The second label segment can be disassembled from the first label segment and retains traceability information.

[0008] Optionally, the life cycle state management module includes a state path diagram modeling unit, a state flow control unit, an illegal state identifier, and a risk recorder. The state path diagram modeling unit is used to preset and maintain the life cycle logical state map of the farmed animal individual, including the state nodes of each stage and their legal flow paths; the state flow control unit records the current life cycle state of the tag based on the event data uploaded by the current tag, and calls the state path diagram each time an event is uploaded to perform a legality comparison on the path relationship between the current event target state and its historical predecessor state; If the comparison result is an illegal state jump, state rollback, or path break, the illegal state identifier will mark the event as an illegal state change behavior; the risk recorder receives the illegal mark, generates an abnormal event risk report, and submits its structure summary to the blockchain to form a risk mark node for subsequent regulatory evidence collection and consumer visual traceability display; If the comparison result is a legal state flow, the state flow control unit will synchronously update the life cycle status of the current tag and transfer the compliance event to the subsequent verification process to achieve dynamic state maintenance and continuous data compliance.

[0009] Optionally, the mobile data anchoring device includes a tag identification unit, a locator, a collection unit, a data storage device and a communication unit; the tag identification unit is used to read the current tag ID and the status data of the tag at key life cycle nodes, the locator is used to record the geographic location coordinates and timestamp when the event occurs, and the collection unit is used to collect breeding indicators of the environment, animal signs, and breeding process in the breeding area; the data storage device is used to store the tag ID, status data and breeding indicators obtained by identification and collection; the communication unit uploads the data stored in the data storage device to the event hash and anchor point verification module, the life cycle status management module and the blockchain intelligent verification module for subsequent event legitimacy judgment and chain processing.

[0010] Optionally, the event hash and anchor point verification module includes an event structure construction unit, a hash generation unit, a dual-point anchor comparison unit, and an abnormal jump detection unit. The event structure construction unit generates an original event structure based on a specific format (tag ID, event type, operation time, location coordinates, device number); the hash generation unit encrypts the generated original event structure using a hash algorithm to form an event hash; the dual-point anchor comparison unit implements a dual physical verification mechanism for the event source by performing consistency verification on the device ID, event type, time and location fields of data uploaded by different devices for the same tag event; the abnormal jump detection unit determines whether there is an illegal state switch or reverse behavior by reading the tag state diagram path and the previous event time. If it is abnormal, the data will be refused to be uploaded to the chain.

[0011] Optionally, the blockchain intelligent verification module includes a contract scheduling unit, a lifecycle rule engine, a logic judgment unit and a result feedback unit. The contract scheduling unit calls the corresponding pre-deployed smart contract according to the event type and its hash value as the entry point of the verification process; the lifecycle rule engine is used to maintain the life cycle status diagram of the animal or product within the contract, and judge whether the current event is a legal successor event of the current state; the logic judgment unit performs a comprehensive judgment on event double-point anchor matching, status compliance, disassembly legality and time sequence; the result feedback unit performs corresponding operations based on the judgment result: if the verification passes, the event data is written to the blockchain and the lifecycle status is updated; if it fails, an alarm is triggered and the event is recorded in the abnormal chain segment pool for subsequent review and accountability.

[0012] Optionally, the logic judgment unit includes a path disturbance detection subunit, which executes an ordered event mapping conflict disturbance index D based on the historical event mapping trajectory and the current event mapping position, and judges whether the current event causes a conflict disturbance in the life cycle path according to the conflict index. If the conflict disturbance index D exceeds the monitoring evaluation threshold Monitor set by the system, it is marked as an abnormal event and is rejected from being uploaded to the chain.

[0013] The present invention also provides a traceability management method based on the aquaculture industry service platform, which includes the following steps: S1. At the initial stage of animal breeding, the operator uses a mobile data anchoring device to read the unique ID of the detachable traceability tag. The system then binds the ID to the individual's profile in the database and sets the tag's initial lifecycle state to "breeding"; S2. At key stages in the individual life cycle, the mobile data anchoring device collects data for each operation event. The collected data includes tag ID, event type, collection time, geographic location, current status value, and breeding environment indicators. At the same time, the mobile data anchoring device uploads the collected data to the event hash and anchor point verification module, the life cycle state management module, and the blockchain intelligent verification module via the communication unit; S3. The event hash and anchor point verification module constructs the collected data into an original event structure according to a preset format, performs a hash algorithm on the original event structure, and forms an event hash value. At the same time, the event hash and anchor point verification module transmits the hash value to the contract scheduling unit in the blockchain intelligent verification module for subsequent lifecycle compliance judgment and event legitimacy verification processes; S4. The event hash and anchor verification module performs consistency check on the event fields uploaded by the two independent MDA devices, and determines whether the current event has abnormal evolution in time or path structure in combination with the life cycle state diagram. If an abnormality is found, the event is marked as illegal; S5. The blockchain intelligent verification module extracts the mapping coordinate sequence from the historical events that have been uploaded to the chain, and calculates the disturbance index based on the current event mapping value. If the SECI value is less than the system's preset monitoring threshold Monitor, the current event path evolution is deemed legal. Otherwise, it is considered a path conflict event, and the system refuses to enter the chain process, triggering an alarm and risk recording. S6. The blockchain intelligent verification module calls the contract to verify whether the event conforms to the legal subsequent path of the current state; S7. The blockchain intelligent verification module performs event writing and status update operations based on the aforementioned contract verification results. When an event passes the lifecycle compliance judgment, two-point anchoring verification, disassembly legality verification, and conflict disturbance index D judgment, the system writes the structured data of the event together with the hash value as a new block to the blockchain, and simultaneously updates the lifecycle status of the individual to the new status corresponding to the current event; If the event does not pass any of the above judgments, the event will be marked as an abnormal event, the abnormal type and triggering cause will be recorded, and the abnormal status will be synchronized to the supervision end.

[0014] Optionally, the traceability management method further includes: Consumers can view the complete breeding information and risk warning records of the breeding individuals by scanning the second label section of the code.

[0015] Optionally, traceability management methods also include: In step S3, the preset format includes: tag ID, event type, operation time, geographic location, and device number.

[0016] The beneficial effects achieved by the present invention are: 1. Through the interaction between the event hash and anchor verification module and the blockchain intelligent verification module, the event structure can be encrypted and hashed and compared with the dual-device anchor before the data is written to the chain. The generated trusted event hash and state transition information are then submitted to the pre-deployed smart contract for rule-level legitimacy judgment. This ensures that all data written to the blockchain undergoes triple verification of structure verification, physical anchoring, and lifecycle path verification, achieving a trusted chain-up mechanism with unforgeable data structure, irreversible state jumps, and irreversible sequence. This significantly improves the security strength of the traceability system in terms of data integrity, process compliance, and anti-tampering capabilities. 2. Through the collaboration between the mobile data anchoring device and the blockchain intelligent verification module, the collected geographic coordinates, status data, and device information can be packaged to generate structured events and hashed. After the legitimacy of the event is determined by the smart contract, it is written to the blockchain. This ensures that all anchoring behaviors have the compliance advantages of being traceable on the chain, identifiable by the device, and verifiable in the process, avoiding falsification, supplementary recording, or evasion of responsibility in the middle link. 3. Through the collaboration between the lifecycle state management module and the event hash and anchor point verification module, the collected event data can be structured and encapsulated into hash events. Path legitimacy comparison and time sequence verification are performed based on the preset lifecycle state map. At the same time, multi-device cross-verification is achieved through the dual-point anchoring mechanism, ensuring that all reported events have chain integrity in structure and conform to lifecycle compliance logic in status. This improves the credibility of event identification and the intelligence level of path verification, preventing abnormal events from bypassing the chain and entering the database. 4. Through the collaboration between the lifecycle state management module and the event hash and anchor verification module, the collected event data can be structured and encapsulated into hash events. Path legitimacy comparison and chronological verification are performed based on the preset lifecycle state map. A dual-point anchoring mechanism is also used to achieve multi-device cross-verification, ensuring that all reported events have chain integrity in structure and conform to lifecycle compliance logic in status. This improves the credibility of event identification and the intelligence level of path verification, preventing abnormal events from bypassing the chain and entering the database. 5. Through the interaction between the detachable traceability tag module and the mobile data anchoring device, tag identity recognition, key node status reading and real-time geographic location collection can be completed at the actual operation site of the farmed animals. This ensures that each piece of behavioral data is derived from the real physical event of the tagged individual. At the same time, combined with the anti-dismantling detection mechanism, it ensures that illegal prying or misuse can be immediately identified and reported, thereby ensuring the physical authenticity, temporal and spatial accuracy and tamper-resistance of the event data, and providing a trusted anchor point for subsequent verification. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but rather the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate the same parts.

[0018] Figure 1 It is an overall block diagram of the present invention.

[0019] Figure 2 It is a block diagram of the life cycle state management module of the present invention.

[0020] Figure 3 Schematic diagram of the workflow of the mobile data anchoring device of the present invention.

[0021] Figure 4 It is a structural diagram of the detachable traceability label module of the present invention. DETAILED DESCRIPTION

[0022] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted in actual size. It is stated in advance. The following embodiments will further explain the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0023] Example 1: According to Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 As shown, this embodiment provides a traceability management system based on a breeding industry service platform, the traceability management system based on the breeding industry service platform includes a server, and a mobile data anchoring device, the traceability management system based on the breeding industry service platform also includes a detachable traceability label module, a life cycle state management module, an event hash and anchor point verification module, and a blockchain intelligent verification module; the server is respectively connected to the mobile data anchoring device, the life cycle state management module, the event hash and anchor point verification module, and the blockchain intelligent verification module, and stores the intermediate data and process data of the mobile data anchoring device, the life cycle state management module, the event hash and anchor point verification module, and the blockchain intelligent verification module in the database of the server.

[0024] The detachable traceability tag module is used to identify the identity and life cycle status of the breeding individual, and trigger a state change event during the disassembly behavior, which is used for binding the data traceability starting point; The mobile data anchoring device collects data of key nodes and forms anchor point records; in this embodiment, the key nodes include breeding behavior, transfer, transportation, and market release.

[0025] The lifecycle state management module maintains the lifecycle logical state diagram of each individual and verifies whether all event uploads are compliant; The event hash and anchor point verification module encapsulates all behavior nodes into structured hash events, compares and verifies them with the current state graph, and forms a trusted anchor point; The blockchain intelligent verification module performs contract-level verification on the event hash and state path, and only after passing the verification can it be stored on the blockchain to form a traceability chain.

[0026] The traceability management system based on the breeding industry service platform also includes a central processor, which is respectively controlled and connected to the server, mobile data anchoring device, life cycle status management module, event hash and anchor point verification module, and blockchain intelligent verification module. Based on the central processor, the mobile data anchoring device, life cycle status management module, event hash and anchor point verification module, and blockchain intelligent verification module are centrally controlled to enhance the entire system's supervision of the entire process of the breeding industry.

[0027] In this embodiment, the mobile data anchoring device is a portable smart terminal device with identity recognition, environmental perception, and positioning upload capabilities. It is used by breeding managers, transporters, quarantine officers, etc. throughout the entire breeding process to perform "physical confirmation + data collection + location recording" of events at key nodes, and upload event information to the platform through the network to form an "anchor point".

[0028] Optionally, the mobile data anchoring device includes a tag identification unit, a locator, a collection unit, a data storage device and a communication unit; the tag identification unit is used to read the current tag ID and the status data of the tag at key life cycle nodes, the locator is used to record the geographic location coordinates and timestamp when the event occurs, and the collection unit is used to collect breeding indicators of the environment, animal signs, and breeding process in the breeding area; the data storage device is used to store the tag ID, status data and breeding indicators obtained by identification and collection; the communication unit uploads the data stored in the data storage device to the event hash and anchor point verification module, the life cycle status management module and the blockchain intelligent verification module for subsequent event legitimacy judgment and chain processing.

[0029] The tag identification unit includes a radio frequency identification reader, a status decoder, and a data interface buffer; The radio frequency identification reader is used to read the unique coding information and the current life cycle status value from the traceability tag. The status decoder is used to parse the status bit information stored in the tag chip into structured data. The data interface buffer is used to temporarily store the parsed tag ID and status value for recording in the data storage device or uploading to the event verification module by the communication unit for subsequent processing.

[0030] Wherein, the tag identification unit enables the tag to not only obtain the ID but also analyze the status; The acquisition unit includes a temperature sensor, a humidity sensor, an ammonia concentration sensor, a noise sensor, and a data processor. The temperature sensor collects temperature data of the breeding area in real time, the humidity sensor collects humidity data of the breeding area in real time, the ammonia sensor collects ammonia content in the air to reflect the breeding hygiene level. Excessive ammonia is a signal of animal stress or accumulation of feces. The noise sensor collects noise data and provides emergency feedback, attacks or external interference to the farmed animals; the data processor processes the data collected by the temperature sensor, humidity sensor, ammonia concentration sensor, and noise sensor. The processing includes but is not limited to the following operations: analog-to-digital conversion, filtering, standardization processing, and output of structured breeding indicator data.

[0031] In this embodiment, the farming indicators include but are not limited to the following: ambient temperature, ambient humidity, ammonia concentration and ambient noise.

[0032] The communication unit includes a communicator, a multi-module address encoder, a data compression and encoder, a network status detector, and an upload control logic. The communicator establishes a communication connection between the server and the number of households identified and collected by the collection unit and the tag identification unit, and transmits data; the multi-module address encoder packages and marks the data to be uploaded according to the target module (such as event hash module, life cycle module, etc.) to achieve distributed upload; the data compression and encoder compresses the collected data (such as JSON structure) and encodes it (such as Base64) to reduce communication overhead; the network status detector detects the current network connection status and selects an adapted network (such as 4G priority, NB-IoT low-power backup); the upload control logic is used to manage the upload timing, failure retry mechanism, and breakpoint resume strategy for adaptive adjustment.

[0033] If necessary, the communication unit also includes a security encryption subunit, which is used to encrypt key data fields during transmission to prevent tampering or interception by intermediate nodes.

[0034] Optionally, the detachable traceability tag module includes a tag structure unit, a status chip, a unique ID encoder, and an anti-disassembly detection unit. The tag structure unit constructs a detachable but stably connected physical tag structure, so that the tag is firmly bound to the individual during the breeding stage, and can be disassembled after the animal is released and retains some information for product stage display and traceability; the status chip unit records the current life cycle state of the tag and automatically switches the status bit when the physical behavior changes; the unique ID encoder assigns a unique identity number to each tag to ensure that it is bound to the individual animal file existing and bred in the database; the anti-disassembly detection unit is used to identify whether the tag has been illegally disassembled or destructively removed. If illegal disassembly or destructive removal occurs, the system should be able to identify and mark it as a risk event; The label structure unit includes a first label segment (segment A) and a second label segment (segment B). The first label segment is bound to the individual animal during the breeding period and has an internal integrated status chip and a unique encoder. The second label segment can be disassembled from the first label segment and retains traceability information for consumer scanning and visual traceability display during the product stage.

[0035] The anti-tamper detection unit includes a circuit break identification circuit, a contact point detection chip, a structural shrapnel fracture trigger, and an illegal state writing control unit; The disconnection identification circuit is provided in the connection area between the first label segment and the second label segment, and is used to detect whether there is disconnection behavior; The contact point detection chip is used to sense whether the physical contacts of the tag are in complete contact; If the shrapnel breaks or the connecting conductor is disconnected during the disassembly process, the illegal status write control unit automatically updates the status chip to an illegal status value (such as 0xFF) and uploads the abnormal status to the supervision platform system through the mobile data anchoring device, thereby realizing effective identification and risk marking of illegal disassembly or destructive removal.

[0036] In this embodiment, the platform system specifically refers to the animal husbandry supervision platform, which is a technical means well known to technicians in this field, and therefore will not be described in detail in this embodiment.

[0037] The circuit break identification circuit includes a conductive bridge structure disposed between the first label segment and the second label segment, a status chip detection pin, a loop closure terminal, and an alarm trigger logic unit; the conductive bridge structure is formed of a low-resistance metal wire or copper foil spring, one end of which is connected to the status chip detection pin and the other end is connected to a reference voltage or ground terminal, forming a closed detection loop; When the tag's physical structure is in a normal connection state, the detection pin level is at a stable reference value; If the tag is disassembled and the conductive bridge breaks, causing the circuit to be disconnected, the state chip detection pin will detect the level change, triggering the internal state update logic, and automatically writing the tag life cycle state into the illegal identification value; Among them, the first tag segment includes a plastic shell, an embedded chip and a fixing buckle; the plastic shell is the external protection structure of the tag, and a chip embedding groove or packaging cavity is provided inside to accommodate and fix the status chip and the unique coding module; the chip is embedded in the shell by card slot matching or sealing, and is connected to the conductive spring located inside the shell through its pins; the fixing buckle structure forms a plug-in or integrated connection with the shell, which is used to install the tag on the ear of an individual animal or a designated area. The plug-in structure of the fixing buckle is linked with the conductive spring, which triggers the spring to break when illegal disassembly occurs, thereby causing the status chip to detect the circuit break and automatically update the tag life cycle status.

[0038] In addition, the fixing buckle is generally a barbed ear tag pin or a rotating locking buckle, which cannot be reversed after being inserted into the animal's ear; the fixing buckle structure and the shell are: an integral injection molding structure (direct molding) or a plug-in combination (such as inserting into a lock slot and locking); The second label segment includes a QR code and a display area, and the second label segment includes a QR code identification layer and an information display area, wherein the QR code identification layer is used to display the QR code information corresponding to the unique encoder, so that consumers can scan the code to obtain platform traceability information; the information display area is located below or around the QR code identification layer, and is used to display additional visual information such as product batch, origin, and production time; the QR code identification layer is fixed to the supporting shell surface of the second label segment by printing, laser engraving or patching, and the information display area and the QR code identification layer are integrally arranged in the display surface. The second label segment forms a detachable whole with the first label segment through a structural connection position. The connection position adopts an easily breakable bridging structure or a snap-on structure, which can be removed and retained at the consumer end. After disassembly, the QR code and display information are still retained, ensuring that the label has independent traceability capabilities in the product circulation link.

[0039] The alarm trigger logic unit includes a level mutation detector, a status update trigger, an alarm flag register and an upload trigger initiator; when the status chip detection pin detects that the level suddenly changes from a normal state to a disconnected state, the level mutation detector generates an interrupt signal; the status update trigger responds to the interrupt signal and writes the illegal status value (such as 0xFF) into the status chip storage area; the alarm flag register is set to "1" to indicate that the current tag is in an illegal disassembly state; the upload trigger initiator generates an upload preparation flag, and the next time the mobile data anchor device reads the tag, the risk status is automatically uploaded to the platform for abnormal recording and regulatory warning.

[0040] like Figure 4As shown, in the initial state, the circuit is turned on (closed), and the status chip GPIO detects "low level" or "stable voltage"; if the user pries open segment B (the second tag segment), the bridge wire breaks, causing the circuit to be disconnected; the status chip IO pin detects a level change (such as from low level to floating or high resistance); the status chip performs an interrupt or polling judgment to confirm illegal disassembly behavior; the status chip immediately writes an "illegal status code (such as 0xFF)" for subsequent reading by the mobile data anchor device; once the mobile data anchor device reads the tag again, it can be identified as "illegally removed state" and uploaded to form a risk event.

[0041] Among them, Figure 4 The data display area is used by consumers to scan and obtain traceability information, which is then bound to a unique code to display the traceability URL or status.

[0042] Through the cooperation between the detachable traceability tag module and the mobile data anchoring device, tag identity recognition, key node status reading and real-time geographic location collection can be completed at the actual operation site of the farmed animals, so that each behavioral data is derived from the real physical event of the tagged individual. At the same time, in conjunction with the anti-dismantling detection mechanism, it ensures that illegal prying or misuse can be immediately identified and reported, thereby ensuring the physical authenticity, temporal and spatial accuracy and anti-tampering ability of the event data, and providing a trusted anchor point for subsequent verification.

[0043] Optionally, the life cycle state management module includes a state path diagram modeling unit, a state flow control unit, an illegal state identifier, and a risk recorder. The state path diagram modeling unit is used to preset and maintain the life cycle logical state map of the farmed animal individual, including the state nodes of each stage and their legal flow paths; the state flow control unit records the current life cycle state of the tag based on the event data uploaded by the current tag, and calls the state path diagram each time an event is uploaded to perform a legality comparison on the path relationship between the current event target state and its historical predecessor state; If the comparison result is an illegal state jump, state rollback, or path break, the illegal state identifier will mark the event as an illegal state change behavior; the risk recorder receives the illegal mark, generates an abnormal event risk report, and submits its structure summary to the blockchain to form a risk mark node for subsequent regulatory evidence collection and consumer visual traceability display; If the comparison result is a legal state flow, the state flow control unit will synchronously update the life cycle status of the current tag and transfer the compliance event to the subsequent verification process to achieve dynamic state maintenance and continuous data compliance.

[0044] The state path diagram modeling unit constructs a complete state path diagram through each state node of the animal life cycle, records each life cycle state (and sets legal flow conditions for each state.

[0045] Among them, the various status nodes include: breeding, marketed, slaughtered, etc.

[0046] Through the preset life cycle model, a status flow diagram of animals from birth to slaughter is created.

[0047] For example: breeding → transfer → market release → slaughter → sale, the legal connections of each state are set by rules to ensure that the state changes comply with business logic.

[0048] The state flow control unit is used to record the life cycle state of the current tag, and compare the path with the previous state based on the current state and upload time to confirm whether the flow is legal.

[0049] Specifically, the state transition control unit obtains the current tag's state information (for example, from a state chip or database). Based on the uploaded event timestamp, it determines whether the current state matches the historical state. It compares the current state with the historical state to see if they conform to the state transition path diagram and verifies the time sequence and state legitimacy. Any non-compliant transitions or unusual time sequences are flagged as illegal events.

[0050] The illegal state detector obtains the currently uploaded state information and compares it with the state path map. It compares the current state with the previous legal state to determine whether there are any illegal jumps (for example, jumping directly from slaughter to sales). It also checks whether the timestamps of the uploaded events match the state sequence to prevent time reversals (for example, slaughter events are performed after market release). If an illegal state is detected, it is flagged and an alarm is triggered.

[0051] The risk recorder records and marks abnormal events. When illegal conditions or illegal transactions are detected, a risk event record is generated and reported to the blockchain, generating an immutable risk tag. The specific working process is as follows: when an illegal condition or abnormal event is detected, the event is marked as a risk event and information such as the risk type, event details, and operator is recorded. This information is uploaded to the blockchain intelligent verification module via the communication unit, generating a risk tag on the blockchain.

[0052] Among them, risk events will affect the traceability path of the farmed animals, and their historical problems can be clearly viewed during subsequent review and tracing.

[0053] Optionally, the event hash and anchor point verification module includes an event structure construction unit, a hash generation unit, a two-point anchor comparison unit, and an abnormal jump detection unit. The event structure construction unit generates an original event structure based on a specific format; the hash generation unit encrypts the generated original event structure using a hash algorithm to form an event hash; the two-point anchor comparison unit implements a dual physical verification mechanism for the source of the event by performing consistency verification on the device ID, event type, time and location fields of data uploaded by different devices for the same tag event; the abnormal jump detection unit determines whether there is an illegal state switch or reverse behavior by reading the tag state diagram path and the previous event time. If it is abnormal, the data is refused to be uploaded to the chain to ensure the dual legitimacy of the time sequence and logical sequence of the data flow.

[0054] In this embodiment, the specific format includes: tag ID, event type, operation time, location coordinates, and device number; The event structure construction unit formats the event according to the structure template corresponding to the specific format, outputs the event as a standard time structure string, and hands it over to the hash generation unit. The hash generation unit performs hash function processing (such as SHA-256) on the standardized event structure to generate a unique and irreversible event hash value; the hash value is calculated from a structured string formed by splicing fields such as tag ID, event type, event time, device number and geographic coordinates, ensuring that the event has uniqueness, tamper-resistance and privacy protection capabilities at the data layer; any slight change in any field will result in a completely different hash result, ensuring the credibility of event information in the platform's internal verification and blockchain writing links.

[0055] For example, for farming, at a certain moment, the following data is anchored: Tag ID: TAG-8721-A; Event type: transfer (transfer column); Operation time: 2025-04-13T10:45:00; Location coordinates: N34.2274, E118.3382; Device number: MDA_0043; Concatenate the above five fields in a fixed order and format to form a structure string (usually in the form of key-value pair + connector): TAG-8721-A|transfer|2025-04-13T10:45:00|34.2274,118.3382|MDA_0043; The concatenated string is sent to the hash algorithm for processing. Taking SHA-256 as an example, the final output result is: e3d0ab97b1345fc3c0d204aa07d24f5ea57f09e1607fd73b40b2d5f5bc58cd2e; The dual-point anchor comparison unit determines whether two different devices have uploaded the same event and performs field consistency comparison. Specifically, the comparison process includes: Check the platform database to see if another device has uploaded the same event type at the same time, location, and tag ID. If a second upload record is found, extract the fields and compare them. The comparison parameters include: whether the timestamp is within the allowable error range (such as ±2 minutes), whether the coordinate distance is within the geographical error tolerance (such as ≤100m), and whether the event type, device ID, and tag ID are completely consistent. If the comparison passes, it is marked as a double-point confirmation event. If no double-point record is found or the fields are inconsistent, it will be marked as a single-point event for subsequent determination of whether to downgrade or reject it.

[0056] The abnormal jump detection unit path comparison subunit and the time sequence judgment subunit; the path comparison subunit is used to judge whether the current event state is a legal successor state of the previous state according to the current event state and the tag historical state information, and compare it with the preset life cycle state diagram; if a state jump or illegal conversion behavior is found, the event is marked as an illegal state change; the time sequence judgment subunit reads the current event timestamp and compares it with the previous legal event timestamp. If it is found that the current time is earlier than the previous event time, or the deviation exceeds the system tolerance threshold, it is regarded as a time reversal behavior; after determining the abnormality, the unit submits the event to the blockchain intelligent verification module to send a signal to reject the chain, to ensure the consistency and legitimacy of the event data in the time dimension and state logic.

[0057] Optionally, the blockchain intelligent verification module includes a contract scheduling unit, a lifecycle rule engine, a logic judgment unit and a result feedback unit. The contract scheduling unit calls the corresponding pre-deployed smart contract according to the event type and its hash value as the entry point of the verification process; the lifecycle rule engine is used to maintain the life cycle status diagram of the animal or product within the contract, and judge whether the current event is a legal successor event of the current state; the logic judgment unit performs a comprehensive judgment on event double-point anchor matching, status compliance, disassembly legality and time sequence; the result feedback unit performs corresponding operations based on the judgment result: if the verification passes, the event data is written to the blockchain and the lifecycle status is updated; if it fails, an alarm is triggered and the event is recorded in the abnormal chain segment pool for subsequent review and accountability.

[0058] The contract scheduling unit is used to find the corresponding smart contract address in the preset contract mapping table based on the structure fields of the currently uploaded event (including event type and tag ID); it then calls the target contract (pre-set) and passes the event hash value and structure fields as verification parameters; the lifecycle rule engine within the contract determines whether the current event is a legal successor state in the tag state diagram, and the logic judgment unit completes multi-dimensional verification; after the contract execution is completed, the verification result, exception type, etc. are fed back to the result feedback unit, which decides whether to write to the chain or generate an exception mark.

[0059] The target contract is a smart contract pre-deployed by the platform on the blockchain network. Each event type corresponds to a unique contract address, which is mapped to the event type field through the contract registry. The contract address can be stored in the on-chain index area or in the contract scheduling configuration managed by the platform server. The contract scheduling unit automatically retrieves the contract address and initiates a call based on the event type field in the event structure to ensure the consistency of the event verification process and the security of the contract call.

[0060] The lifecycle rule engine includes a lifecycle state graph database, a tag history state extractor, a state jump comparison unit, a path graph tracker and an exception code generator; the tag history state extractor extracts the state and time information of the last on-chain event of the current tag from the platform or blockchain; the state jump comparison unit determines whether the current event state is the direct successor state of the previous state; the state graph tracker performs state path tracking when there is a state branch path or nested structure to confirm the legitimacy of the path; the exception code generator outputs a state legitimacy mark based on the comparison result. If it is illegal, it generates an exception state code and corresponding description, and passes it to the logic judgment unit for the final on-chain decision.

[0061] Specifically: Tag history status extraction pulls the most recent legal event status and its timestamp from the blockchain or database based on the current tag ID; for example, the current tag is pig A1, and the last status was slaughtered; Next, fields are extracted from the current event structure and mapped to lifecycle state nodes. For example, if the event type is slaughter, the lifecycle state diagram database is called to query the lifecycle diagram of the category to which the current farmed animal belongs, such as: breeding → transfer → market release → slaughter → sale. The state jump comparison unit checks whether the current state is a direct successor of the most recent legal event state; if so, it is compliant; if not, it is determined to be a state jump anomaly; If complex state branches are involved (such as multiple categories and withdrawal links), execute the path graph traversal: trigger from the most recent legal event state, and see if there is a path: most recent legal event state →... → current state. If there is but it is not a direct successor, mark it as: indirect jump; if the path does not exist, mark it as: illegal transfer.

[0062] The logic judgment unit includes an anchor matching judge, a state legitimacy receiver, a disassembly state judge, a time sequence comparator, a result aggregator and an abnormality identification encoder; The state legitimacy receiver receives the event path compliance judgment result output by the lifecycle rule engine. If it is an illegal state jump or reversal, it is directly marked as an illegal event and the subsequent judgment process is terminated. If the state is compliant, the judgment process continues with the disassembly state judge reading the status code of the current tag to confirm whether the tag has been illegally disassembled. If the status is an illegal code, the event is determined to be illegal, and the exception identification encoder is triggered to mark it as a disassembly exception; If the disassembly is legal, the process continues to the time order comparator, which compares the current event timestamp with the previous legal event time. If the time sequence is reversed, a time anomaly is returned; If the time is legal, it enters the anchor matching judge to confirm the consistency of the device multi-point upload, and the anchor matching status is passed to the result aggregator as a credibility level identifier; finally, the result aggregator comprehensively determines whether the event is legal based on the three strong constraint results. If all are legal, the write chain is allowed. If any one fails, the exception identification encoder generates a corresponding error code and submits it to the result feedback unit for processing.

[0063] The result feedback unit includes a write chain controller, a life cycle state updater, an exception record manager, an alarm trigger, and a response returner. When the logic judgment unit returns a verification pass signal, the write chain controller writes the event structure and hash value into the blockchain network, and the life cycle state updater updates the life cycle state of the tag to the new state in the event. When the judgment result is failure, the exception record manager packages the event and the failure reason code into an exception record and writes it into the exception segment pool. The alarm trigger triggers a system-level warning to notify the supervisor or platform administrator; After the event processing is completed, the response returner will return the processing status to the upper layer of the system, completing the event processing closed loop.

[0064] Through the mutual cooperation of the event hash and anchor verification module and the blockchain intelligent verification module, the event structure can be encrypted hashed and compared with the dual-device anchor before the data is written to the chain, and the generated trusted event hash and state transfer information are submitted to the pre-deployed smart contract to execute the rule-level legality judgment, thereby ensuring that all data written to the blockchain are triple-verified by structural verification, physical anchoring and lifecycle path verification, realizing a trusted chain mechanism in which the data structure cannot be forged, the state cannot be jumped, and the sequence cannot be reversed, significantly improving the security strength of the traceability system in terms of data integrity, process compliance and anti-tampering capabilities.

[0065] Optionally, the logic judgment unit includes a path disturbance detection subunit, which performs ordered event mapping conflict disturbance index D based on the historical event mapping trajectory and the current event mapping position, and judges whether the current event causes conflict disturbance of the life cycle path according to the conflict index. If the conflict disturbance index D exceeds the monitoring evaluation threshold Monitor set by the system, it is marked as an abnormal event and rejected from being uploaded to the chain (that is, the event data is written into the blockchain ledger).

[0066] The path disturbance detection subunit extracts key fields such as event type, device number, and event timestamp from each successfully uploaded historical event. The event timestamp uses the Unix standard representation (in seconds or milliseconds). For example, the event 2025-03-01 15:32:10 is converted into the integer time value 1740816730. The above fields are then concatenated into a structured string, such as: "SALE"+"MDA03"+"1740816730"→ALEMDA031740816730; Perform a hash compression (such as SHA-256) operation on the structure string, and extract different paragraphs from the hash result to generate two-dimensional coordinate points: Take the first 8 hexadecimal digits as the x component; Take the last 8 hexadecimal digits as the y component; The coordinate point is recorded as the event map value P i =(x i ,y i ), used to construct historical path trajectories.

[0067] At the same time, the path disturbance detection subunit also performs the same structure splicing and hash compression on the current upload event to obtain the current mapping coordinate C=(x c ,y c ), and insert C into the historical path sequence {P1,P2,...,P i−1}; The path disturbance detection subunit calculates the conflict disturbance index D according to the following formula: ; Where, Δ dir is the time direction variation coefficient (reverse sequence is 1, positive sequence is 0), Δ dist is the mapping distance between the current point and the previous point, σ is the historical average disturbance scale in the path, and α and β are the disturbance weight factors set by the system.

[0068] Among them, the time direction transformation coefficient Δ dir Calculated according to the following formula: ; Where, T now is the current event timestamp, T prew The timestamp of the most recent legal event on the chain; The mapping distance Δ between the current point and the previous point dist Calculated according to the following formula: ; Where (x1, y1) is the hash map coordinate of the previous event, and (x2, y2) is the hash map coordinate of the current event.

[0069] The historical average disturbance scale σ in the path is calculated according to the following formula: ; Where n is the number of event points in the historical event sequence that has been verified by the system and uploaded to the chain and bound to the current tag ID, (x i ,y i ) is the hash map coordinate of the i-th event, (x i+1 ,y i+1 ) is the hash map coordinate of the i+1th event.

[0070] The above formula forms the disturbance tolerance standard by statistically analyzing the jump amplitude of the historical path.

[0071] In addition, in this embodiment, examples of values ​​of the system-set disturbance weight factors α and β are also provided: 1) In the case of farmed animals with frequent transfers, possible overlapping reports, and easily reversed time sequence, requiring strict verification: α=0.7; β = 0.3; 2) In the transportation scenario (where the geographical span is large and distance deviation is prone to errors, but the time is relatively fixed), then: α=0.3; β = 0.7; 3) In the case of batch injection / marking operations (operations occur simultaneously and in parallel, without excessive order constraints), then: α=0.4; β = 0.6; 4) In scenarios reported during daily inspections (non-critical behaviors with a high tolerance for sequence and position), then: α=0.5; β = 0.5; 5) In the accountability review scenario (tracing back the accident) (time logic is particularly critical and the order must be strictly controlled), then: α=0.8; β = 0.2; In summary, in this embodiment, it is necessary to select appropriate disturbance weight factors α and β based on the specific scenario and input them from the human-computer interaction interface. This is a technical means well known to technicians in this field, so it will not be described in detail in this embodiment.

[0072] In this embodiment, the monitoring threshold Monitor is determined by the system according to actual conditions. In addition, in this embodiment, a specific value example is provided, specifically: 1) In the daily feeding scenario in the breeding area (animals in the same batch have concentrated behavior locations, stable event time, and low tolerance for path disturbances), the monitoring threshold Monitor = 0.5; 2) In the scenario of pen transfer (transfer between pens) (where there is a small range of path disturbance, partial displacement must be allowed but the process must still be carried out in sequence), the monitoring threshold Monitor = 0.9; 3) In the scenario of slaughterhouse transportation (across a long geographical area, where the path is naturally subject to position disturbances), the monitoring threshold Monitor = 1.5; In this embodiment, the specific value of the monitoring threshold Monitor needs to be determined in combination with the specific usage scenario and input from the human-computer interaction interface. This is a technical means well known to those skilled in the art, and therefore will not be described in detail in this embodiment.

[0073] Through the collaboration of mobile data anchoring devices and blockchain intelligent verification modules, the collected geographic coordinates, status data and device information can be packaged to generate structured events and hashed. After the legality of the event is judged by the smart contract, it is written into the blockchain, thereby ensuring that all anchoring behaviors have the compliance advantages of leaving traces on the chain, being identifiable by the device, and having a verifiable process, avoiding falsification, re-recording or responsibility evasion in the middle links.

[0074] The present invention also provides a traceability management method based on the aquaculture industry service platform, which includes the following steps: S1. At the initial stage of animal breeding, the operator uses a mobile data anchoring device to read the unique ID of the detachable traceability tag. The system then binds the ID to the individual's profile in the platform database and sets the tag's initial lifecycle state to "breeding"; S2. At key stages in the individual life cycle, the mobile data anchoring device collects data for each operation event. The collected data includes tag ID, event type, collection time, geographic location, current status value, and breeding environment indicators. At the same time, the mobile data anchoring device uploads the collected data to the event hash and anchor point verification module, the life cycle state management module, and the blockchain intelligent verification module via the communication unit; S3. The event hash and anchor point verification module constructs the collected data into an original event structure according to a preset format, performs a hash algorithm on the original event structure, and forms an event hash value. At the same time, the event hash and anchor point verification module transmits the hash value to the contract scheduling unit in the blockchain intelligent verification module for subsequent lifecycle compliance judgment and event legitimacy verification processes; S4. The event hash and anchor verification module performs consistency check on the event fields uploaded by the two independent MDA devices, and determines whether the current event has abnormal evolution in time or path structure in combination with the life cycle state diagram. If an abnormality is found, the event is marked as illegal; S5. The blockchain intelligent verification module extracts the mapping coordinate sequence from the historical events that have been uploaded to the chain, and calculates the disturbance index based on the current event mapping value. If the SECI value is less than the system's preset monitoring threshold Monitor, the current event path evolution is deemed legal. Otherwise, it is considered a path conflict event, and the system refuses to enter the chain process, triggering an alarm and risk recording. S6. The blockchain intelligent verification module calls the contract to verify whether the event conforms to the legal subsequent path of the current state; S7. The blockchain intelligent verification module performs event writing and status update operations based on the aforementioned contract verification results. When an event passes the lifecycle compliance judgment, two-point anchoring verification, disassembly legality verification, and conflict disturbance index judgment, the system writes the structured data of the event together with the hash value as a new block to the blockchain, and simultaneously updates the individual's lifecycle status to the new status corresponding to the current event; If the event does not pass any of the above judgments, the event will be marked as an abnormal event, the abnormal type and triggering cause will be recorded, and the abnormal status will be synchronized to the regulatory end to trigger the platform-side early warning mechanism for review, disposal and accountability by the regulator.

[0075] Optionally, the traceability management method further includes: Consumers can view the complete breeding information and risk warning records of the breeding individuals by scanning the second label section of the code.

[0076] Optionally, traceability management methods also include: In step S3, the preset format includes: tag ID, event type, operation time, geographic location, and device number.

[0077] The blockchain referred to in this application refers to a data ledger system built on a distributed consensus mechanism, which records multiple behavioral event data in sequence through a block structure to form an unalterable, traceable, and verifiable data chain, and ensures the consistency and anti-counterfeiting ability of events between network nodes through chain encryption and consensus mechanism.

[0078] In this application, the blockchain is used to record key event information at each node in the life cycle of farmed individuals, including but not limited to: tag status changes, anchor data, life cycle flow events, abnormal behavior markers, etc., by submitting the hash summary of the event structure and its status path to the pre-deployed smart contract for legitimacy verification. Only after the verification is passed can it be written into the blockchain main ledger, forming a traceability data chain that can be jointly verified by consumers, regulators, and production companies.

[0079] The blockchain system can adopt consortium chain, permission chain, or combine edge nodes to build a lightweight side chain architecture to support event interaction and status synchronization between on-chain data and off-chain intelligent platforms.

[0080] The on-chain operation refers to submitting the verified event data structure to the blockchain ledger and recording it as a chain node; the segment pool refers to the event segments that are marked as abnormal but retained, which are used for regulatory review and are not visible to consumers; smart contracts assume the functional role of event verification and legality judgment in this architecture; blockchain ensures that data has the advantages of being tamper-proof, arranged in chronological order, traceable, and accountable.

[0081] Through the collaboration of the lifecycle state management module and the event hash and anchor verification module, the collected event data can be structured and encapsulated into hash events, and path legitimacy comparison and time sequence verification can be performed based on the preset lifecycle state map. At the same time, multi-device cross-verification is achieved with the help of the double-point anchoring mechanism, thereby ensuring that all reported events have chain integrity in structure and comply with the lifecycle compliance logic in status, improving the credibility of event identification and the intelligence level of path verification, and preventing abnormal events from bypassing the chain and entering the warehouse.

[0082] Embodiment 2: This embodiment should be understood to include all the features of any of the above embodiments and further improve upon them. Figure 1 、 Figure 2 、 Figure 3,as well as Figure 4 As shown, the traceability management system based on the breeding industry service platform also includes a platform service management module, which opens a visual tracking platform to consumers and regulatory authorities to display the label life cycle event chain, abnormal behavior, and responsible person path.

[0083] Among them, an individual life cycle map is generated in the platform service management module to show the event chain, state evolution, responsible personnel and equipment experienced by the tag.

[0084] The platform service management module includes a life cycle graph builder, an abnormal event layer overlay, a responsibility chain path aggregator, a supervision interface server, a consumer visualization display terminal and a risk push service unit; The lifecycle graph builder parses the historical events and status change information of each tagged individual from the blockchain data, and constructs an interactive lifecycle traceability graph in a graph structure; The abnormal event layer overlay visually overlays abnormal events recorded in the blockchain (such as state jumps, illegal disassembly, and reverse behavior) on the graph using icons, colors, and path weightings. The responsibility chain path aggregator is used to extract the information of the responsible party based on the operating device ID and personnel account in the event structure, and construct the behavior responsibility path in the graph; The supervision interface server is used to provide auditors with functions such as label map export, historical anomaly download, and responsibility tracing; The consumer display terminal combines the label QR code recognition results to show users the complete life cycle status map of the individual, risk markers and traceability path of responsible personnel, ensuring the transparency and visibility of the source of food products; The risk push service supports setting subscription conditions for abnormal behavior events and pushes high-risk behavior event alerts to responsible personnel, making management responsibilities traceable and event information verifiable.

[0085] The platform service management module further includes a responsibility path deviation analysis unit. The responsibility path deviation analysis unit constructs the deviation Ri between each responsible person and the average behavior path of the node group based on the mapping trajectory of the node in the individual life cycle graph: ; Where, L i The number of lifecycle event nodes in which the responsible person participates. is the mapping coordinate of the responsible person's operation event in the jth event node, is the average mapping position of all responsible behaviors in the jth node, is the geometric deviation between the responsible person and the average behavior position in the jth node, and its value is calculated according to the following formula: ; When R i When it exceeds the system-set threshold SETing, the platform will mark the responsible person's behavior as a deviation risk for priority review by regulators.

[0086] The system setting threshold SETing is set by the system according to actual conditions and input from a human-machine interface. This is a technical means well known to those skilled in the art, and therefore will not be described in detail in this embodiment.

[0087] In this embodiment, an example of a value of the system setting threshold SETing is provided, specifically: 1) In the breeding stage (feeding and pen transfer) scenario (all operations take place in a fixed area, with little spatial variation and the smaller the deviation, the better), the system sets the threshold SETing = 5; 2) In the scenario of slaughter transportation (where the geographical coordinates span a large area, the paths are dispersed, and the tolerance is increased), the system sets the threshold SETing=15; 3) In the accountability audit scenario (when conducting a targeted investigation, the suspected responsible party must be accurately identified), the system sets the threshold SETing = 3; 4) In the epidemic prevention inspection scenario (epidemic prevention actions should have the same behavior path for the same group of people), the system sets the threshold SETing=6; In summary, the specific system setting threshold SETing needs to select an appropriate value in combination with the specific usage scenario and input it from the human interaction interface. This is a technical means well known to technicians in this field, so it will not be described in detail in this embodiment.

[0088] Through the cooperation of the event hash and anchor verification module and the platform service management module, each verified anchor event is encapsulated as a chain data node and automatically appended to the life cycle graph. When displaying the graph, the system can simultaneously display the event structure summary, location anchor record and device information, thereby providing consumers and regulators with a more structured, trustworthy and chained tag event tracking method.

[0089] The contents disclosed above are only preferred feasible embodiments of the present invention and do not limit the scope of protection of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention description and drawings are included in the scope of protection of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. A traceability management system based on aquaculture industry service platform, comprising a server and a mobile data anchoring device, characterized in that: The traceability management system based on the aquaculture industry service platform also includes a detachable traceability label module, a life cycle status management module, an event hash and anchor point verification module, and a blockchain intelligent verification module. The detachable traceability tag module is used to identify the identity and life cycle status of the breeding individual and trigger a state change event during the disassembly behavior; The mobile data anchoring device collects data of key nodes and forms anchor point records; The lifecycle state management module maintains the lifecycle logical state diagram of each individual and verifies whether all event uploads are compliant; The event hash and anchor point verification module encapsulates all behavior nodes into structured hash events, compares and verifies them with the current state graph, and forms a trusted anchor point; The blockchain intelligent verification module performs contract-level verification on the event hash and state path, and only after passing the verification can it be stored on the blockchain to form a traceability chain.

2. The traceability management system based on the aquaculture industry service platform according to claim 1 is characterized in that: The detachable traceability tag module includes a tag structure unit, a status chip, a unique ID encoder, and an anti-tampering detection unit. The tag structure unit constructs a physical tag structure, allowing the tag to be firmly bound to the individual during the breeding stage and to be disassembled after market release, retaining some information for product stage display and traceability. The status chip records the current life cycle state of the tag and automatically switches the status bit when the physical behavior changes. The unique ID encoder assigns a unique identity number to each tag, ensuring that it is uniquely bound to the individual animal file in the database. The anti-tampering detection unit is used to identify whether the tag has been illegally disassembled or destructively removed. If illegal disassembly or destructive removal occurs, the system should be able to identify and mark it as a risk event. The label structure unit includes a first label segment and a second label segment. The first label segment is bound to the animal during the breeding period and has an internal integrated status chip and a unique ID encoder. The second label segment can be disassembled from the first label segment and retains traceability information.

3. The traceability management system based on the aquaculture industry service platform according to claim 2 is characterized in that: The life cycle state management module includes a state path diagram modeling unit, a state flow control unit, an illegal state identifier, and a risk recorder. The state path diagram modeling unit is used to preset and maintain the life cycle logical state map of the farmed animal individual, including the state nodes of each stage and their legal flow paths; the state flow control unit records the current life cycle state of the tag based on the event data uploaded by the current tag, and calls the state path diagram every time an event is uploaded to perform a legality comparison on the path relationship between the current event target state and its historical predecessor state; If the comparison result is an illegal state jump, state rollback, or path break, the illegal state identifier will mark the event as an illegal state change behavior; the risk recorder receives the illegal mark, generates an abnormal event risk report, and submits its structure summary to the blockchain to form a risk mark node for subsequent regulatory evidence collection and consumer visual traceability display; If the comparison result is a legal state flow, the state flow control unit will synchronously update the life cycle status of the current tag and transfer the compliance event to the subsequent verification process to achieve dynamic state maintenance and continuous data compliance.

4. The traceability management system based on the aquaculture industry service platform according to any one of claims 1 or 3, characterized in that: The mobile data anchoring device includes a tag identification unit, a locator, a collection unit, a data storage device and a communication unit; the tag identification unit is used to read the current tag ID and the status data of the tag at key life cycle nodes, the locator is used to record the geographical location coordinates and timestamp when the event occurs, and the collection unit is used to collect breeding indicators of the environment, animal signs, and breeding process in the breeding area; the data storage device is used to store the tag ID, status data and breeding indicators obtained by identification and collection; the communication unit uploads the data stored in the data storage device to the event hash and anchor point verification module, the life cycle status management module and the blockchain intelligent verification module for subsequent event legitimacy judgment and chain processing.

5. The traceability management system based on the aquaculture industry service platform according to claim 4 is characterized in that: The event hash and anchor point verification module includes an event structure construction unit, a hash generation unit, a two-point anchor comparison unit, and an abnormal jump detection unit. The event structure construction unit generates an original event structure based on a specific format; the hash generation unit encrypts the generated original event structure using a hash algorithm to form an event hash; the two-point anchor comparison unit implements a dual physical verification mechanism for the event source by performing consistency verification on the device ID, event type, time, and location fields of data uploaded by different devices for the same tag event; the abnormal jump detection unit determines whether there is an illegal state switch or reverse behavior by reading the tag state diagram path and the previous event time. If it is abnormal, the data will be rejected from being uploaded to the chain.

6. The traceability management system based on the aquaculture industry service platform according to claim 5 is characterized in that: The blockchain intelligent verification module includes a contract scheduling unit, a lifecycle rule engine, a logic judgment unit, and a result feedback unit. The contract scheduling unit calls the corresponding pre-deployed smart contract according to the event type and its hash value as the entry point of the verification process; the lifecycle rule engine is used to maintain the lifecycle state diagram of the animal or product within the contract and determine whether the current event is a legal successor event of the current state; the logic judgment unit performs a comprehensive judgment based on event double-point anchor matching, state compliance, disassembly legality, and time sequence; The result feedback unit performs corresponding operations based on the judgment result: if the verification passes, the event data is written to the blockchain and the lifecycle status is updated; if it fails, an alarm is triggered and the event is recorded in the abnormal chain segment pool for subsequent review and accountability.

7. The traceability management system based on the aquaculture industry service platform according to any one of claims 1 or 6, characterized in that: The logic judgment unit includes a path disturbance detection subunit, which performs ordered event mapping conflict disturbance index D based on the historical event mapping trajectory and the current event mapping position, and judges whether the current event causes conflict disturbance of the life cycle path according to the conflict index. If the conflict disturbance index D exceeds the monitoring evaluation threshold Monitor set by the system, it is marked as an abnormal event and rejected from being uploaded to the chain.

8. A traceability management method based on aquaculture industry service platform, applied to the traceability management system based on aquaculture industry service platform according to claim 7, characterized in that: The traceability management method comprises the following steps: S1. At the initial stage of animal breeding, the operator uses a mobile data anchoring device to read the unique ID of the detachable traceability tag. The system then binds the ID to the individual's profile in the database and sets the tag's initial lifecycle state to "breeding"; S2. At key stages in the individual life cycle, the mobile data anchoring device collects data for each operation event. The collected data includes tag ID, event type, collection time, geographic location, current status value, and breeding environment indicators. At the same time, the mobile data anchoring device uploads the collected data to the event hash and anchor point verification module, the life cycle state management module, and the blockchain intelligent verification module via the communication unit; S3. The event hash and anchor point verification module constructs the collected data into an original event structure according to a preset format, performs a hash algorithm on the original event structure, and forms an event hash value. At the same time, the event hash and anchor point verification module transmits the hash value to the contract scheduling unit in the blockchain intelligent verification module for subsequent lifecycle compliance judgment and event legitimacy verification processes; S4. The event hash and anchor verification module performs consistency check on the event fields uploaded by the two independent MDA devices, and determines whether the current event has abnormal evolution in time or path structure in combination with the life cycle state diagram. If an abnormality is found, the event is marked as illegal; S5. The blockchain intelligent verification module extracts the mapping coordinate sequence from the historical events that have been uploaded to the chain, and calculates the disturbance index based on the current event mapping value. If the SECI value is less than the system's preset monitoring threshold Monitor, the current event path evolution is deemed legal. Otherwise, it is considered a path conflict event, and the system refuses to enter the chain process, triggering an alarm and risk recording. S6. The blockchain intelligent verification module calls the contract to verify whether the event conforms to the legal subsequent path of the current state; S7. The blockchain intelligent verification module performs event writing and status update operations based on the aforementioned contract verification results. When an event passes the lifecycle compliance judgment, two-point anchoring verification, disassembly legality verification, and conflict disturbance index D judgment, the system writes the structured data of the event together with the hash value as a new block to the blockchain, and simultaneously updates the lifecycle status of the individual to the new status corresponding to the current event; If the event does not pass any of the above judgments, the event will be marked as an abnormal event, the abnormal type and triggering cause will be recorded, and the abnormal status will be synchronized to the supervision end.

9. The traceability management method based on the aquaculture industry service platform according to claim 8 is characterized in that: The traceability management method further includes: Consumers can view the complete breeding information and risk warning records of the breeding individuals by scanning the second label section of the code.

10. The traceability management method based on the aquaculture industry service platform according to claim 9 is characterized in that: Traceability management methods also include: In step S3, the preset format includes: tag ID, event type, operation time, geographic location, and device number.

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