A data migration method, related device, equipment and storage medium

Abstract

The embodiment of the application discloses a data migration method, related device, equipment and storage medium, at least related to computer vision and deep learning technology in artificial intelligence, in the scene of changing the target object association mechanism from the second mechanism to the first mechanism, the first mechanism identifies the corresponding local device of the mechanism initiates a feature migration request, then based on the mechanism association relationship, the second mechanism identification associated with the target object identification is determined, the target biological characteristics corresponding to the target object identification are obtained from the information library corresponding to the second mechanism identification, and the target biological characteristics are pushed to the local device of the mechanism corresponding to the first mechanism identification, realizing the automatic migration of the target biological characteristics of the target object from the second mechanism to the first mechanism, avoiding the need for the target object to re-register the object related information for the first mechanism, simplifying the biological characteristic migration operation process when the mechanism is changed, and improving the application experience.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a data migration method, related apparatus, equipment, and storage medium. Background Technology

[0002] In the service sector, the user receiving the service is the object, while the provider of the service is generally a service organization of varying sizes.

[0003] With the development of internet technology, individuals can conveniently enjoy various services provided by service providers by using their biological characteristics as identity information, such as clocking in, checking in, and dining. Before obtaining the above services, individuals need to bind their object identifiers with their biological characteristics, so that service providers can clearly identify which individual the obtained biological characteristics correspond to, thus providing accurate services.

[0004] However, during the process of receiving services from a service provider, changes in the associated service provider are frequent. Once a service provider changes, the object needs to have its biological characteristics collected and linked again at the new service provider, which is a very cumbersome process. Summary of the Invention

[0005] To address the aforementioned technical issues, this application provides a data migration method, related apparatus, equipment, and storage medium, which simplifies the biological characteristic migration process during institutional changes and improves the user experience.

[0006] The embodiments of this application disclose the following technical solutions:

[0007] On one hand, embodiments of this application provide a data migration method, the method comprising:

[0008] Obtain the feature migration request sent by the local device of the organization corresponding to the first organization identifier, wherein the feature migration request includes the target object identifier and the first organization identifier;

[0009] The corresponding organizational relationship is determined based on the target object identifier, and the organizational relationship is used to identify that the target object identifier is associated with the second organizational identifier;

[0010] Obtain the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second institution identifier;

[0011] The target biological features are pushed to the institution's local device, which is used to determine the corresponding object identifier based on the collected biological features.

[0012] On the other hand, embodiments of this application provide a data migration method, the method comprising:

[0013] The target object identifier is obtained through the local device of the organization corresponding to the first organization identifier;

[0014] If it is determined that the target object identifier is not associated with the first organization identifier, the first organization identifier is obtained from the organization's local device;

[0015] Send a feature migration request generated based on the first institution identifier and the target object identifier to the server. The feature migration request is used to request the acquisition of the target biological features corresponding to the target object identifier.

[0016] The information database of the institution's local device is updated based on the target biological characteristics returned by the server, and the institution's local device is used to determine the corresponding object identifier based on the collected biological characteristics.

[0017] On the other hand, embodiments of this application provide a data migration apparatus, the apparatus comprising an acquisition unit, a determination unit, and a push unit:

[0018] The acquisition unit is used to acquire a feature migration request sent by the local device of the organization corresponding to the first organization identifier, wherein the feature migration request includes a target object identifier and a first organization identifier;

[0019] The determining unit is used to determine the corresponding organizational association relationship based on the target object identifier, wherein the organizational association relationship is used to identify that the target object identifier is associated with the second organizational identifier;

[0020] The acquisition unit is further configured to acquire the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second institution identifier;

[0021] The push unit is used to push the target biological features to the local device of the institution, and the local device of the institution is used to determine the corresponding object identifier based on the collected biological features.

[0022] On the other hand, embodiments of this application provide a data migration apparatus, the apparatus comprising an acquisition unit, a sending unit, and an updating unit:

[0023] The acquisition unit is used to acquire the target object identifier through the local device of the organization corresponding to the first organization identifier;

[0024] The acquisition unit is further configured to acquire the first organization identifier from the organization's local device if it is determined that the target object identifier is not associated with the first organization identifier;

[0025] The sending unit is configured to send a feature migration request generated based on the first institution identifier and the target object identifier to the server, wherein the feature migration request is used to request the acquisition of the target biological feature corresponding to the target object identifier;

[0026] The update unit is used to update the information database of the institution's local device according to the target biological characteristics returned by the server, and the institution's local device is used to determine the corresponding object identifier based on the collected biological characteristics.

[0027] On the other hand, embodiments of this application provide a data migration system, the system including an organization's local device and a server corresponding to a first organization identifier:

[0028] The local device of the institution is used to obtain the target object identifier; if it is determined that the target object identifier is not associated with the first institution identifier, the first institution identifier is obtained from the local device of the institution; a feature migration request generated based on the first institution identifier and the target object identifier is sent to the server, the feature migration request being used to request the acquisition of the target biological feature corresponding to the target object identifier;

[0029] The server is configured to: receive a feature migration request sent by the local device of the institution corresponding to the first institution identifier; determine the corresponding institution association relationship based on the target object identifier, wherein the institution association relationship is used to identify that the target object identifier is associated with the second institution identifier; obtain the target biological feature corresponding to the target object identifier from the information database corresponding to the second institution identifier; and push the target biological feature to the local device of the institution.

[0030] The local device of the institution is also used to update the information database of the local device of the institution according to the target biological characteristics returned by the server, and the local device of the institution is used to determine the corresponding object identifier according to the collected biological characteristics.

[0031] On the other hand, embodiments of this application provide a computer device, the computer device including a processor and a memory:

[0032] The memory is used to store program code and transmit the program code to the processor;

[0033] The processor is configured to execute the methods described above according to instructions in the program code.

[0034] On the other hand, embodiments of this application provide a computer-readable storage medium for storing a computer program for performing the methods described above.

[0035] On the other hand, embodiments of this application provide a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods described above.

[0036] As can be seen from the above technical solution, in scenarios where the service provider for the target object changes from the second institution to the first institution, the local device of the institution corresponding to the first institution's identifier initiates a feature migration request. This feature migration request includes the target object identifier and the first institution's identifier. Before the institution change, the target object is an object of the second institution, and the institution association relationship corresponding to the target object identifier is used to identify the association between the target object identifier and the second institution identifier. Based on the institution association relationship, the second institution identifier associated with the target object identifier is determined, the target biological features corresponding to the target object identifier are obtained from the information database corresponding to the second institution identifier, and the target biological features are pushed to the local device of the institution corresponding to the first institution identifier, thus realizing the automatic migration of the target object's target biological features from the second institution to the first institution. Since the local device of the institution can determine the object identifier based on the collected biological features, after the biological feature migration is completed, the local device of the first institution can determine the target object identifier based on the target object's biological features. This avoids the need for the target object to re-register the collected object information for the first institution, simplifies the biological feature migration operation process during institution changes, and improves the user experience. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram illustrating an application scenario of a data migration method provided in an embodiment of this application;

[0039] Figure 2 A flowchart illustrating a data migration method provided in an embodiment of this application;

[0040] Figure 3 A schematic diagram illustrating the framework of a data migration method provided in an embodiment of this application;

[0041] Figure 4 A schematic flowchart illustrating a feature registration method provided in an embodiment of this application;

[0042] Figure 5 A flowchart illustrating a feature value transfer method based on a local device of an organization, provided for an embodiment of this application;

[0043] Figure 6 This is a schematic diagram of the structure of a face recognition device provided in an embodiment of this application;

[0044] Figure 7 This is a schematic flowchart of a data migration apparatus provided in an embodiment of this application;

[0045] Figure 8 This is a schematic flowchart of another data migration apparatus provided in an embodiment of this application;

[0046] Figure 9 This application provides a schematic diagram of the structure of a server according to an embodiment of the present application.

[0047] Figure 10 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0048] The embodiments of this application will now be described with reference to the accompanying drawings.

[0049] To simplify the process of re-collecting biological characteristics of subjects when service providers change, this application provides a data migration method, related apparatus, equipment, and storage medium.

[0050] The data migration method provided in this application is based on artificial intelligence (AI). AI is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results. In other words, AI is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a way similar to human intelligence. AI studies the design principles and implementation methods of various intelligent machines, enabling them to have the functions of perception, reasoning, and decision-making.

[0051] Artificial intelligence (AI) is a comprehensive discipline encompassing a wide range of fields, including both hardware and software technologies. Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies primarily include computer vision, speech processing, natural language processing, and machine learning / deep learning.

[0052] In the embodiments of this application, the main artificial intelligence software technologies involved include the aforementioned computer vision technologies, machine learning / deep learning, and other related fields. For example, it may involve face recognition, fingerprint identification, iris identification, etc. in computer vision (CV), or deep learning in machine learning (ML), including various artificial neural networks (ANNs).

[0053] The data migration method provided in this application can be applied to data migration devices with data processing capabilities, such as terminal devices and servers. Specifically, terminal devices can be smartphones, desktop computers, laptops, tablets, smart speakers, smartwatches, in-vehicle devices, etc., but are not limited to these. Servers can be independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers providing cloud computing services. Terminal devices and servers can be directly or indirectly connected via wired or wireless communication, and this application does not impose any restrictions on this connection.

[0054] The data migration device is capable of implementing computer vision technology. Computer vision technology is a science that studies how to enable machines to "see." More specifically, it refers to machine vision, which uses cameras and computers to replace human eyes for target recognition, tracking, and measurement, and further performs image processing to create images more suitable for human observation or transmission to instruments for detection. As a scientific discipline, computer vision researches related theories and technologies, attempting to establish artificial intelligence systems capable of extracting information from images or multidimensional data. Computer vision technology typically includes image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, 3D object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping (SLAM), and other technologies, as well as common biometric recognition technologies such as facial recognition and fingerprint recognition. In the embodiments of this application, the data migration device can identify collected biological features using biometric technologies such as facial recognition and fingerprint recognition within computer vision technology.

[0055] This data migration device is capable of machine learning. Machine learning is a multidisciplinary field involving probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory, among others. It specifically studies how computers can simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to endow computers with intelligence; its applications span all areas of artificial intelligence. Machine learning and deep learning typically include techniques such as artificial neural networks.

[0056] The artificial intelligence model used in the data migration method provided in this application mainly involves the application of neural networks. Based on the biological characteristics collected from the object by the organization's local equipment, the neural network determines the object's identity information, thereby providing services to the object.

[0057] This data migration method can be applied to blockchain. The blockchain can store data such as object identifiers (e.g., target object identifiers) and biological characteristics (e.g., target biological characteristics) obtained in this application, thereby improving data security. Furthermore, the server acting as the data migration device can also be located within the blockchain system, allowing for loading and transmission of relevant data from the blockchain storage when needed.

[0058] Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying platform, a platform product service layer, and an application service layer.

[0059] The underlying blockchain platform can include processing modules such as user management, basic services, smart contracts, and operational monitoring. The user management module is responsible for managing the identity information of all blockchain participants, including maintaining public and private key generation (account management), key management, and maintaining the correspondence between user real identities and blockchain addresses (access management). Furthermore, under authorization, it monitors and audits transactions of certain real identities and provides risk control rule configuration (risk control audit). The basic services module is deployed on all blockchain node devices to verify the validity of business requests. After consensus is reached on valid requests, they are recorded in storage. For a new business request, the basic services first perform interface adaptation parsing and authentication (interface adaptation), and then encrypt the business information using a consensus algorithm (consensus management). After encryption, the data is transmitted completely and consistently to the shared ledger (network communication) and recorded and stored. The smart contract module is responsible for contract registration, issuance, triggering, and execution. Developers can define contract logic using a programming language and publish it to the blockchain (contract registration). According to the contract terms, the key or other events are invoked to trigger execution and complete the contract logic. It also provides functions for contract upgrades and cancellations. The operation monitoring module is mainly responsible for deployment, configuration modification, contract settings, cloud adaptation, and real-time status visualization output during product release, such as alarms, network monitoring, and monitoring of node device health status.

[0060] In this embodiment, the target student is taken as the target object. Taking the change of the institution where the target student receives education from the second institution to the first institution as an example, this embodiment illustrates how the target biological characteristics of the target student are transferred from the second institution to the first institution. The data migration method provided in this embodiment is described below with reference to the accompanying drawings, using a server as the data migration device.

[0061] See Figure 1 , Figure 1 This is a schematic diagram illustrating an application scenario of the data migration method provided in an embodiment of this application. For example... Figure 1 As shown, the system includes a server 101 and an institution local device 102 corresponding to the first institution identifier. The server 101 is used to implement the migration of biological characteristics. The first institution identifier is used to identify the first institution, which is the changed institution. The institution local device 102 is used to provide services such as clocking in, signing in, and deducting meal fees for the objects by collecting their biological characteristics.

[0062] Generally, educational institutions do not allow students to bring terminal devices, or the students' parents are not familiar with operating the terminal devices. In this case, the data migration method provided in this application embodiment initiates a feature migration request through the local device 102 of the institution corresponding to the first institution identifier, thereby migrating the target biological characteristics corresponding to the target object to the first institution.

[0063] exist Figure 1 In the scenario shown, the institution's local device 102 sends a feature migration request to the server 101, triggering a biological feature migration task. The server 101 receives the feature migration request from the institution's local device 102 and executes the target biological feature migration task. The feature migration request includes a target object identifier and a first institution identifier. The feature migration request is used to request the acquisition of the target object features corresponding to the target object identifier, thereby migrating the target biological features from the second institution to the first institution. For example, when the target object identifier is a target student identifier, it is used to uniquely identify the target student's student identity throughout their entire educational career, and the target student identifier does not change with changes in the institution where the target student receives education.

[0064] Before the organizational change, the target object belonged to the second organization. The organizational association between the target object identifier and the second organization identifier was that the target object identifier was associated with the second organization identifier, where the second organization identifier was used to identify the second organization, which was the organization before the change. Based on this organizational association, server 101 can determine the second organization identifier associated with the target object identifier.

[0065] Since the biological characteristics of the target object are stored in the information database 103 corresponding to the second organization identifier before the organization change, the server 101 can obtain the target biological characteristics corresponding to the target object identifier from the information database 103 corresponding to the second organization identifier. The target biological characteristics refer to the human characteristics that constitute the identity of the target object, including but not limited to facial features, fingerprint features, voiceprint features and iris features.

[0066] Subsequently, server 101 pushes the target biological characteristics of the target object to the local device 102 of the institution, thus realizing the migration of the target biological characteristics of the target object from the second institution to the first institution. After the feature migration is completed, the local device 102 of the institution can determine the target object identifier based on the collected biological characteristics of the target object, and provide services such as clocking in, signing in, and deducting meal expenses for the target object.

[0067] In the scenario described above, where the institution where the target object receives education changes from the second institution to the first institution, a feature migration request is initiated through the local device of the institution corresponding to the first institution's identifier. The target object's biological characteristics are automatically migrated from the second institution to the first institution using the target object's identifier. This avoids the need for the target object to re-register and collect relevant information for the first institution, simplifies the biological characteristic migration process when the institution changes, and improves the user experience.

[0068] The service providers involved in this application embodiment can be of different types, such as various schools, hospitals, companies, factories, etc. Based on the type of service provider, this application embodiment can be applied to different service scenarios. Even when the first and second providers are of different types, this application embodiment can be applied to multiple service scenarios simultaneously, such as a multi-service scenario where the first provider is a hospital and the second provider is a school.

[0069] Correspondingly, the target can also have a corresponding identity based on the type of service provider they receive. For example, when receiving services from an educational institution, the target can be identified as a student, and when receiving services from a hospital, they can be identified as a medical professional or a patient.

[0070] To facilitate the explanation of the data migration scheme provided in the embodiments of this application, the first institution and the second institution will be specifically referred to as educational institutions, the target object as the target student, and the target object identifier as the target student identifier in the following embodiments.

[0071] To better understand, the following section describes, from a system perspective, the process of triggering the server to complete the transfer of biological characteristics through the local device of the institution corresponding to the first institution identifier. See also... Figure 2 , Figure 2 This is a flowchart illustrating a data migration method provided in an embodiment of this application. Figure 2 As shown, this data migration method includes the following steps:

[0072] S201: Obtain the target object identifier through the local device of the organization corresponding to the first organization identifier.

[0073] Generally, students do not have or are not allowed to bring mobile phones, smartwatches, or other terminal devices, or their parents are not familiar with operating such devices. In this scenario, this application embodiment triggers a feature transfer task through the local device of the institution identified by the first institution. That is, the local device of the institution corresponding to the first institution identifier sends a feature transfer request to the server, so that the server transfers the target biological characteristics corresponding to the target student identifier from the second institution to the first institution. Thus, after the target student's educational institution changes from the second institution to the first institution, the first institution continues to provide the target student with services such as attendance tracking, sign-in, and meal fee deduction. The target student can be a student receiving preschool to high school education (K12), a university student, etc., and both the first and second institutions are educational institutions within the education system.

[0074] In practical applications, the target student's identifier is first obtained through the local device of the institution corresponding to the first institution identifier, where the first institution is the institution after the change. The first institution identifier is used to identify the first institution and can be an institution identity number (ID), institution name, etc. The institution's local device is used to determine the corresponding student identifier based on the collected student's biological characteristics, thereby providing students with the aforementioned check-in and attendance services. This can be a biological characteristic collection device such as a face capture device or a fingerprint capture device. The target student identifier is used to uniquely identify the student's student identity throughout their entire educational career and does not change with changes in the institution where the student receives education. The target student identifier is associated with the institution where the target student is currently receiving education. The target student identifier can be generated and assigned by the platform that provides check-in and attendance services for students in educational institutions, and can be a student ID, student code, etc.

[0075] Since the institution where the target student receives education has changed from the second institution to the first institution, and prior to the first institution collecting relevant information about the target student, the local device corresponding to the first institution's identifier does not store any data related to the target student. Therefore, the local device of the first institution can obtain the target object identifier from the target device via Near Field Communication (NFC), where the target device stores the target object identifier.

[0076] In practical applications, the target device can be brought close to the local device of the institution corresponding to the first institution's identifier. A quick NFC connection is then established to retrieve the target student's identifier from the target device. This NFC technology simplifies the process of obtaining the target student's identifier from the target device to the local device of the institution corresponding to the first institution's identifier when the institution changes, thus improving efficiency.

[0077] In some scenarios, users, such as the target student or their parents, possess mobile phones, smartwatches, or other terminal devices with NFC functionality. Therefore, in these scenarios, the target device can be an NFC-enabled terminal device. In other scenarios, schools generally do not allow students to bring mobile phones, tablets, or other terminal devices, and students are usually equipped with corresponding card devices, such as student cards or campus cards, at the educational institutions they receive education from. In this scenario, the target device can also be an NFC-enabled card device.

[0078] In practical applications, parents of the target student can activate the service for the target student using a terminal device, which stores the target student's identifier. When the target student's educational institution changes, based on NFC technology, the card used by the target student at the first institution is brought close to the terminal device containing the target student's identifier. Then, the card is brought close to the local device of the institution corresponding to the first institution's identifier, allowing that institution's local device to acquire the target student's identifier. The specific target device can be determined according to the actual application scenario, and no restrictions are imposed here.

[0079] The above-mentioned method, which uses terminal devices or card devices to transmit the target student's identifier to the local device of the first institution's identifier based on NFC technology, is applicable to a variety of application scenarios. It simplifies the process of obtaining the target student's identifier when the institution changes, and improves the user experience.

[0080] S202: If it is determined that the target object identifier is not associated with the first organization identifier, obtain the first organization identifier from the organization's local device.

[0081] After the local device of the institution corresponding to the first institution identifier obtains the target student identifier, it determines whether the target student identifier is associated with the first institution identifier. If yes, it indicates that the first institution can provide relevant services to the target student based on its local device, meaning that the target biological characteristics corresponding to the target student identifier have been migrated. If no, it indicates that the first institution cannot provide relevant services to the target student through its local device, and the target biological characteristics corresponding to the target student identifier need to be migrated to the first institution. In this case, the first institution identifier is obtained from the institution's local device so that the target biological characteristics corresponding to the target student identifier can be migrated to the first institution based on the first institution identifier, where the first institution identifier can be the first institution ID, the first institution name, etc.

[0082] In practical applications, before the institutional change, the target student was a student of the second institution, and the institutional association between the target student's identifier and the second institution's identifier was related. When the institution where the target student received education changed from the second institution to the first institution, the institutional association between the target student's identifier and the first institution's identifier had not yet been updated. Therefore, after the local device of the first institution's identifier obtained the target student's identifier, it could determine that the target student's identifier and the first institution's identifier were not related. Thus, it obtained the first institution's identifier from the local device of the institution corresponding to the first institution's identifier, so that the server could determine, based on the first institution's identifier, to migrate the target biological characteristics from the second institution to the first institution.

[0083] S203: The local device of the institution corresponding to the first institution identifier sends a feature migration request generated based on the first institution identifier and the target student identifier to the server.

[0084] After the local device of the institution corresponding to the first institution identifier in S201-S202 obtains the target student identifier and the first institution identifier, it can send a feature migration request to the server. This feature migration request includes the target student identifier and the first institution identifier. The feature migration request is used to request the acquisition of the target biological feature corresponding to the target student identifier. Based on this, after the server obtains the feature migration request sent by the local device of the institution corresponding to the first institution identifier, it performs a target biological feature migration task according to the feature migration request, that is, migrating the target biological feature from the second institution to the first institution.

[0085] S204: The server determines the corresponding organizational affiliation based on the target object identifier.

[0086] As mentioned earlier, before the target student's educational institution changed, the target student was a student of the second institution, and the institution association corresponding to the target student's identifier was that the target student's identifier and the second institution's identifier were associated. Based on this, the server can determine the second institution's identifier associated with the target student's identifier based on the target student's identifier in the feature migration request. The second institution is the institution before the change, and the second institution's identifier is used to identify the second institution, which can be the second institution's ID, second institution's name, etc.

[0087] S205: The server retrieves the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second organization identifier.

[0088] Before the institution where the target student receives education changes from the second institution to the first institution, the database corresponding to the second institution's identifier stores the target student's biological characteristics. This database stores the student's biological characteristics, which correspond to the student's identifier. Biological characteristics refer to the human features that constitute a student's identity, including but not limited to facial features, fingerprint features, voiceprint features, and iris features. In practical applications, the database can be categorized according to feature type: face database, fingerprint database, voiceprint database, and iris database. Therefore, the student's biological characteristics can be stored by category, the specifics of which can be determined based on the actual application scenario and are not limited here.

[0089] Since there is a correspondence between a student's biological characteristics and a student identifier, in the scenario where the target biological characteristics need to be migrated in this application, the server can obtain the target biological characteristics corresponding to the target student identifier from the information database corresponding to the second institution identifier based on the target student identifier in the feature migration request. The target biological characteristics are used to identify the biological characteristics of the target student, including any combination of one or more of the target student's facial features, fingerprint features, voiceprint features, or iris features.

[0090] In this embodiment, the server can store information databases of multiple institutions in the form of a database such as SQLite, or it can link multiple institution databases via a network. When the institution where the target student receives education changes, the server retrieves the target biological characteristics corresponding to the target student's identifier from the database corresponding to the second institution's identifier via the network, and sends these target biological characteristics to the first institution. The specific method depends on the actual application scenario and is not limited here. SQLite is a lightweight database and a relational database management system that adheres to the four fundamental elements of database transaction correct execution: Atomicity, Consistency, Isolation, and Durability.

[0091] S206: The server pushes the target biological characteristics to the institution's local device.

[0092] After the server obtains the target student's biological characteristics, it pushes these characteristics to the local device corresponding to the first institution's identifier. The local device then uses these characteristics to determine the corresponding student identifier, enabling it to provide relevant services to the student. Once the biological characteristic transfer is complete, the first institution's local device can determine the corresponding target student identifier based on the collected biological characteristics, thus providing relevant services to the target student within the first institution.

[0093] In practical applications, local devices within an organization can be uniquely identified using a serial number (SN). During the process of pushing target biometric data, the server can determine the local device within the organization to which the target biometric data is to be transferred by identifying the device SN associated with the first organization identifier. The specific determination can be made based on the actual application scenario and is not limited here.

[0094] Based on the above, after automatically migrating the target biological characteristics of the target object from the second institution to the first institution, the institutional association relationship corresponding to the target object identifier can be updated. The updated institutional association relationship is used to identify the association between the target object identifier and the first institution identifier. In practical applications, the association between the target student identifier and the second institution identifier can be removed first, and then the association between the target student identifier and the first institution identifier can be established.

[0095] If the institution where the target student receives education changes again, such as from the first institution to the third institution, the target biological characteristics can be migrated from the first institution to the third institution based on the updated institution relationship. This ensures that the biological characteristics can be migrated multiple times when the institution where the target student receives education changes multiple times, simplifies the feature migration process, and improves the user experience.

[0096] As mentioned earlier, educational institutions typically use databases to store biological characteristics, such as face databases for storing facial features and fingerprint databases for storing fingerprint features. In the scenario where the educational institution for the target student changes in this application embodiment, after the server obtains the target student's target biological characteristics, it can delete the target biological characteristics from the database corresponding to the second institution identifier and update the target biological characteristics in the database corresponding to the first institution identifier. This achieves synchronous updates of the biological characteristics stored in the databases of the first and second institutions during the target student's movement from the second institution to the first institution, avoiding data redundancy in the database corresponding to the first institution identifier, ensuring that the local equipment of the institution corresponding to the second institution identifier can provide services to the target object, and also ensuring automatic migration of the target biological characteristics when the institution receiving services for the target object changes again.

[0097] It is understandable that a student may change their educational institution multiple times throughout their educational career. For example, the target student might change their educational institution from institution two to institution one, and then back again. Therefore, the server can first update the target biological characteristics in the database corresponding to the first institution's identifier, and then push the target biological characteristics to the local device of the institution corresponding to the first institution's identifier based on the updated information in the database.

[0098] Specifically, the server can first determine the updated content of the information database corresponding to the first institution identifier based on the target biological characteristics, and then push the updated content to the local device of the institution corresponding to the first institution identifier. The updated content refers to the amount of data change in the information database corresponding to the first institution when the institution where the target student receives education changes, including adding or deleting biological characteristics.

[0099] In scenarios where the institution where the target student receives education changes from the second institution to the first institution, the target biological characteristics need to be migrated to the information database corresponding to the first institution's identifier. In this case, the update content is to add the target biological characteristics to the information database corresponding to the first institution. Therefore, the local device of the institution corresponding to the first institution's identifier should add the target biological characteristics.

[0100] In a scenario where the institution where the target student receives education changes from the first institution to the third institution, the target biological characteristics need to be migrated out of the information database corresponding to the first institution's identifier. In this case, the update content is to delete the target biological characteristics from the information database corresponding to the first institution. Therefore, the local device of the institution corresponding to the first institution's identifier should delete the target biological characteristics.

[0101] It is understandable that if the information database stores biological features by category, then after the server obtains the target biological features, it can update the corresponding information database with different types of features according to category. For example, the facial features in the target biological features can be stored in the face database, and the fingerprint features can be stored in the fingerprint database. The specifics are determined according to the actual application scenario, and no restrictions are made here.

[0102] The data migration method provided in the above embodiments, in a scenario where the institution where the target student receives education changes from a second institution to a first institution, initiates a feature migration request from the local device of the institution corresponding to the first institution's identifier. This feature migration request includes the target student's identifier and the first institution's identifier. Before the institution change, the target student was a student of the second institution, and the institution association relationship corresponding to the target student's identifier is used to identify the association between the target student's identifier and the second institution's identifier. Based on the institution association relationship, the second institution's identifier associated with the target student's identifier is determined. The target biological characteristics corresponding to the target student's identifier are retrieved from the information database corresponding to the second institution's identifier and pushed to the local device of the institution corresponding to the first institution's identifier, thus achieving automatic migration of the target student's target biological characteristics from the second institution to the first institution. Since the local device of the institution can determine the student's identifier based on the collected biological characteristics, after the biological characteristic migration is completed, the local device of the first institution can determine the target student's identifier based on the target student's biological characteristics. This avoids the need for the target student to re-register and collect student-related information for the first institution, simplifies the biological characteristic migration operation process during institution changes, and improves the user experience.

[0103] To better understand, the following example illustrates the data migration method provided in this application embodiment, using the scenario of providing meal fee deduction services to target students through local equipment of an institution as an example to transfer the facial features of target students from a second institution to a first institution.

[0104] See Figure 3 , Figure 3 This is a schematic diagram of a data migration framework provided for an embodiment of this application. Figure 3 In the scenario of deducting meal expenses as shown, the information database is a face database, and the target biological feature is the face feature corresponding to the target object identifier, including terminal device 301, server 302, face device 303 corresponding to the first institution identifier, face device 304 corresponding to the second institution identifier, and object card 305.

[0105] The terminal device 101 is used to activate the meal payment deduction service for the target user, and can be a mobile phone, smartwatch, etc., used by the target user or their parent. The server 302 is used to provide institutions with facial recognition database storage services, facial recognition database update services, and facial recognition database processing services. Specifically, the facial recognition database storage service provides facial recognition database storage services to educational institutions within the education system. Figure 3 The server 302 shown stores face databases for a first institution, a second institution, and a third institution. The face database update service provides face feature updates when the institution changes. The face database processing service provides feature transfer and feature extraction functions. Face device 303 is used to provide meal payment deduction services for the target object in the first institution, and face device 304 is used to provide meal payment deduction services for the target object in the second institution. Face devices 303 and 304 include an asynchronous deduction module, a face recognition module, a local face database, a 3D camera, and an NFC module. They can provide face database receiving and face update services and store their respective corresponding institution IDs, such as... Figure 3 The face recognition device 303 shown stores the first organization ID. Figure 3 Not all content is shown; it is only used as an example for reference.

[0106] In this embodiment, the platform providing services such as attendance tracking and check-in for individuals within an educational institution based on the institution's local devices can release terminal device applications, such as social or educational applications, to users, such as target individuals or their parents. Users can then activate attendance tracking and other related services through the application and obtain an object identifier assigned by the application. Users register accounts and activate related services through their terminal devices within the application, allowing the institution's local devices to provide services to the target individuals by collecting their biological characteristics. The application can be an application software (APP), mini-program, or similar software corresponding to the institution's local devices, and is not limited in any way here.

[0107] exist Figure 3 In the scenario shown, taking the platform corresponding to the local device of the institution as an example to provide social applications to users, the terminal device 301 includes a social account system, an activation module and an NFC module. The social account system is used for user registration and login to social applications, the activation module is used to provide the function of activating the meal payment service and assigning object identifiers, and the NFC module is used to provide NFC functions.

[0108] During the application process, users register social application accounts through the social account system of terminal device 301, and through the activation module of terminal device 301 and the feature extraction function in the face database processing service provided by server 302, they activate the meal payment deduction service for the target object and assign the target object ID.

[0109] To address the above registration process, this application provides a feature registration method. See also... Figure 4 , Figure 4 This is a flowchart illustrating a feature registration method provided in an embodiment of this application. Figure 4 As shown, the feature registration method includes the following steps:

[0110] S401: Obtain the feature registration request sent by the terminal device.

[0111] When a user registers a social media account for a target student and activates services such as check-in, attendance tracking, and meal payment deductions, the target student is a student of a second institution. In this case, the target student's biological characteristics can be collected using a biometrics collection device and uploaded to the terminal device, or the terminal device can store the target student's biological characteristics, depending on the specific application scenario. Based on this, the terminal device sends a feature registration request to the server through the activation module. This feature registration request includes the target biological characteristics and the second institution's identifier. After receiving the feature registration request from the terminal device, the server extracts and stores the biological characteristics from the request.

[0112] In practical applications, the feature extraction function provided by the server can also be used to extract biological feature data related to the target student carried in the feature registration request through the neural network model in artificial intelligence technology, so as to obtain the target biological features. For example, if the feature registration request includes the target student's face image, the face features of the target student can be obtained by extracting features from the target face image; if the feature registration request includes the target student's audio, the voiceprint features of the target student can be obtained by extracting the target audio, etc.

[0113] by Figure 3 Taking the scenario shown as an example, the terminal device 301 uses its camera to capture a facial image of the target object. The terminal device 301 then sends a feature registration request to the server 302, which includes the facial image of the target object. After receiving the feature registration request from the terminal device 301, the server 302 performs feature extraction on the facial image in the feature registration request, extracts the facial features of the target object, and stores the facial features in the facial database corresponding to the second organization identifier.

[0114] It should be noted that the above are possible implementation methods provided by the embodiments of this application, and the specific implementation can be determined according to the actual application scenario, and no limitation is made here.

[0115] S402: Generate a corresponding target object identifier based on the target biological characteristics, and return the target object identifier to the terminal device.

[0116] Based on the above S401, the server generates a corresponding target student identifier based on the acquired target biological characteristics and returns the target student identifier to the terminal device. After storing the target student identifier, the terminal device can transmit the target student identifier to the local device of the institution corresponding to the first institution identifier via NFC, so that the local device of the institution can generate a feature migration request based on the target student identifier to realize the automatic migration of the target biological characteristics.

[0117] like Figure 3 As shown, the target object has an object card 305 in the first institution, which has an NFC module and provides NFC functionality. When the target object's educational institution changes to the first institution, the object card 305 is brought close to the terminal device 301, and the object card 305 obtains the target object ID from the terminal device 302 via NFC. Based on this, during the feature transfer process, the object card 305 can be brought close to the face recognition device 303 to transmit the target object ID. Subsequently, the face recognition device 303 generates a feature transfer request based on the target object ID and the first institution ID, and sends it to the server 302, so that the server 302 can automatically transfer the target object's facial features based on the feature transfer function of the face database processing service.

[0118] S403: Update the target object identifier to the information database corresponding to the second organization identifier.

[0119] While returning the target student identifier to the terminal device, the server also updates the database corresponding to the second institution identifier. This allows the server to determine the target biological characteristics from the database based on the target student identifier when the institution where the target student receives education changes. In practical applications, after generating the target student identifier, the server also needs to establish an association between the target student identifier and the second institution identifier, i.e., establish an institutional association relationship corresponding to the target student identifier. Therefore, after receiving a feature migration request from the terminal device, the server can determine the second institution identifier corresponding to the target student identifier based on the institutional association relationship.

[0120] Based on the feature registration method provided in the above embodiments, after activating relevant services for target students, the institution's local equipment can be used to provide these services to the target students. Figure 3 In the scenario shown, before the institution where the target object receives education changes, the target object is an object of the second institution. At this time, the face device 304 corresponding to the identifier of the second institution can be used to provide relevant services to the target object.

[0121] When the institution where the target object receives education changes to the first institution, server 302 receives a feature migration request sent by face recognition device 303. This feature migration request includes the target object ID and the first institution ID. Based on the face update service, server 302 migrates the target object's facial features from the second institution's face database to the first institution's face database. In the actual storage process, the first institution identifier, the target object identifier, and the target biological characteristics are stored in the first institution's face database accordingly. Figure 3In the first institution's face database shown, there is a corresponding relationship between the first institution ID, the A object ID, and the A object's facial features. After the facial feature migration is completed, the target object's facial features are deleted from the second institution's face database and the second institution's face device 304. The face device 303 receives the target object's facial features pushed by the server 302 based on the face database receiving service and stores them in the local face database.

[0122] Based on the data migration method provided in the above embodiments, after migrating the target biological characteristics of the target object to the local device of the institution corresponding to the first institution identifier, the biological characteristics of the target object can be collected through the local device of the institution, and services such as clocking in, signing in, and deducting meal expenses can be provided to the target object. Figure 3 In the scenario shown, after the target's biological characteristics are transferred, the facial recognition device 303 can be used to collect the target's facial features and provide the target with a meal deduction service in the first institution.

[0123] To better understand, the following will use... Figure 3 This paper uses an example of an application scenario that provides meal payment deduction services for a target object, with the server as the execution entity, to introduce the application process of the local device corresponding to the first institution identifier. It should be noted that the meal payment deduction service refers to deducting meal fees from the application corresponding to the target object identifier after determining the target object identifier through the institution's local device.

[0124] The following is combined Figure 5 right Figure 3 This section introduces the application scenarios for automatic meal payment deductions. (See also...) Figure 5 , Figure 5 This is a flowchart illustrating a feature value transfer method based on a local device of an organization, as provided in an embodiment of this application. Figure 5 The method shown above Figure 2 Based on the method shown, the following steps are included:

[0125] S501: Obtain the feature value transfer request sent by the local device of the organization.

[0126] After the target student selects their food at the institution's cafeteria or other locations offering automatic meal payment, a feature value transfer request is triggered by the institution's local device. Upon receiving this request, the server provides the automatic meal payment service to the target student. The feature transfer request includes the target student's identity information corresponding to their biological characteristics and the feature value to be transferred, used to request the transfer of the feature value to the institution's account corresponding to the first institution's identifier. The identity information corresponding to the target student's biological characteristics refers to the student's relevant information within the first institution, such as their student ID or code. In the meal payment scenario, the feature value to be transferred identifies the price of the food to be paid.

[0127] In practical applications, the institution's local devices can be based on Internet of Things (IoT) technology, including at least one biometric data acquisition device, such as a 3D camera, fingerprint scanner, or voice recorder. The 3D camera, analogous to a traditional camera, incorporates liveness detection hardware and software, including depth and infrared cameras, enhancing information security. Based on this, the institution's local devices collect the biological characteristics of the target student through the biometric data acquisition device, determining the corresponding identity information based on these characteristics. These biological characteristics can be any combination of one or more of the following: facial features, voiceprint features, fingerprint features, or iris features collected specifically for the target student.

[0128] In the meal payment deduction scenario described in this application embodiment, to enhance facial recognition security, the IoT-based facial recognition device 303 uses a 3D camera to capture the facial image of the target object and determines the identity information corresponding to the facial features of the target object through a facial recognition application (APP). The facial recognition device 303 includes a facial recognition module and an asynchronous deduction module, wherein the facial recognition module is used for facial acquisition, facial selection, and feature extraction.

[0129] exist Figure 3 In the scenario shown, the face recognition device 303 is specifically as follows: Figure 6 As shown in Figure 600, the face recognition device 600 includes a 3D camera 601 and a touch screen 602, wherein the 3D camera is used to capture facial images, and the touch screen 602 is used for touch operation and displaying information related to automatic deduction of meal fees. Figure 6 A schematic diagram of a touch screen 602 showing a successful automatic deduction of meal fees is provided. Figure 6 The facial recognition device shown is merely an example, and the specific device can be configured according to the actual application scenario. It should be noted that, in the embodiments of this application, the local device of the institution can also be other biological acquisition devices such as fingerprint acquisition devices, voiceprint acquisition devices, and iris acquisition devices, without any limitation.

[0130] During face capture, the face recognition device uses a 3D camera to capture the face of the target object, obtaining a face image including RGB image stream, depth image stream, and infrared image stream. Then, the acquired face image undergoes optimization processing, specifically selecting the optimal face image for the target object based on a comprehensive evaluation of factors such as face size, face angle, image contrast, and sharpness coefficient. Subsequently, the face recognition module extracts features from the optimized face image, or performs face representation, to determine the identity information of the target object. Face representation is the process of modeling facial features. This application provides two face feature extraction methods: a knowledge-based representation method and a representation method based on algebraic features or statistics.

[0131] The aforementioned knowledge-based representation method primarily obtains feature data helpful for face classification based on the shape description of facial organs and the distance characteristics between them. Its feature components include Euclidean distance, curvature, and angle between feature points. A face is composed of parts such as the eyes, nose, mouth, and chin. The geometric description of these parts and the structural relationships between them can serve as important features for face recognition; these features are called geometric features. Knowledge-based face representation mainly includes methods based on geometric features and template matching methods. In this embodiment, it refers to converting facial image information into feature string information that uniquely identifies the user.

[0132] In practical applications, any of the above methods can be used to extract features from a facial image, and then match them with facial features stored in the biological features of the facial recognition device. If no facial features identical or similar to those of the target object are found, it indicates that the facial recognition device does not store the target object's identity information. In this case, the facial recognition device returns a failure and cannot provide the automatic payment service for the target. If a match is successful, it indicates that the facial recognition device stores the target object's identity information. In this case, the identity information corresponding to the target object is determined based on the matching result.

[0133] It should be noted that the above embodiment takes the facial recognition device as an example of collecting the facial features of the target object to determine the identity information of the target object as a local device of the institution. In practical applications, other biological feature collection devices can also be used to collect other biological features of the target object for determination, such as voiceprint features, fingerprint features, iris features, etc. The specific process is similar to the above process and will not be repeated here.

[0134] S502: Determine the social media account associated with the target object identifier based on the identity information.

[0135] Based on the above S501, after the biological characteristics of the target student are collected by the institution's local device to determine the corresponding identity information, the social account associated with the target student's identifier is determined based on the identity information. This social account is the social account used when the terminal device activates the service. It can be registered by the user corresponding to the target student's identifier, that is, the social account registered and used by the target student himself, or it can be registered by the parent of the user corresponding to the target student's identifier, that is, the account registered and used by the target student's parent. The specific determination depends on the actual application scenario and is not limited here.

[0136] S503: Transfer the feature value from the social account to the institutional account corresponding to the first institutional identifier.

[0137] Once the server identifies the social media account, it can transfer the feature value from the social media account to the institutional account corresponding to the first institutional identifier, thus enabling the automatic deduction of meal fees. In practical applications, as shown in Figure 602, information such as payment success can be displayed on the institution's local device, indicating to the user that the feature value transfer was successful.

[0138] Compared to traditional payment methods, students do not need to carry meal cards, cash, or terminal devices. Furthermore, during the payment process, automatic deduction service can be achieved without manual operation, simplifying the user operation process and improving the user experience.

[0139] It should be noted that the above embodiments use the scenario of providing meal fee deduction for students based on facial features as an example to combine the data migration method provided in the embodiments of this application. In practical applications, it is also possible to provide various services such as check-in and attendance for teachers, enterprise employees and other types of objects based on other biological features. The specific implementation process is similar to the above process and will not be repeated here.

[0140] Taking the scenario of student Xiaoming transferring from Elementary School A to Elementary School B as an example, the above-mentioned meal fee deduction process will be explained. Xiaoming's parents register a social media account on a mobile social media app and activate the meal fee deduction service through the app's mini-program. During the service activation process, a facial image of Xiaoming is captured using a camera and uploaded to a server. The server extracts features from Xiaoming's facial image to obtain Xiaoming's facial features, generates a Xiaoming ID based on these features, and returns the Xiaoming ID to the phone. Subsequently, the Xiaoming ID is linked to Elementary School A, and Xiaoming's facial features and Xiaoming ID are stored in the corresponding information database 'a' of Elementary School A.

[0141] After Xiaoming transferred to Elementary School B, he placed his student card (which he used at Elementary School B) near his parent's mobile phone, and then near the facial recognition device at Elementary School B. The facial recognition device sent a feature migration request to the server, triggering the server to migrate Xiaoming's facial features from Elementary School A to Elementary School B. This feature migration request included Xiaoming's ID and Elementary School B. During the facial feature migration process, the server determined Xiaoming's previous school, Elementary School A, based on his ID. It then retrieved Xiaoming's facial features from the facial database 'a' corresponding to Elementary School A, updated these features in Elementary School B's facial database 'b' and the facial recognition devices included in Elementary School B, deleted Xiaoming's facial features from facial database 'a', severed the association between Xiaoming's ID and Elementary School A, and re-established the association between Xiaoming's ID and Elementary School B.

[0142] While Xiaoming was attending Elementary School B, during the process of paying for his meal at the school cafeteria, a facial recognition system in the cafeteria used a 3D camera to capture Xiaoming's face. After verifying Xiaoming's identity, the system transferred the money Xiaoming had spent at the cafeteria from his parents' social media account to the cafeteria's official account.

[0143] The above embodiments utilize NFC-enabled student cards, written with the student ID, to enable students to quickly re-bind their institution ID and complete feature migration, thereby achieving offline facial recognition and asynchronous deduction. Furthermore, when a student transfers or advances to a new institution, their facial feature data is pre-sent to the new institution's equipment, avoiding the need for re-collecting, registering, and binding facial data, and the need for parents to actively delete the student's facial data from the old institution. This improves the efficiency of facial feature migration during institution changes, enhances student payment efficiency, and improves the user experience.

[0144] In addition to the data migration method provided in the above embodiments, this application also provides a data migration apparatus.

[0145] See Figure 7 , Figure 7 This is a schematic diagram of a data migration device provided in an embodiment of this application. Figure 7 As shown, the data migration device 700 includes an acquisition unit 701, a determination unit 702, and a push unit 703:

[0146] The acquisition unit 701 is used to acquire a feature migration request sent by the local device of the organization corresponding to the first organization identifier. The feature migration request includes the target object identifier and the first organization identifier.

[0147] The determining unit 702 is used to determine the corresponding organizational association relationship based on the target object identifier, wherein the organizational association relationship is used to identify that the target object identifier is associated with the second organizational identifier;

[0148] The acquisition unit 701 is further configured to acquire the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second institution identifier;

[0149] The push unit 703 is used to push the target biological features to the local device of the institution, and the local device of the institution is used to determine the corresponding object identifier based on the collected biological features.

[0150] In one possible implementation, the device 700 further includes an update unit:

[0151] The updating unit is used to update the organization association relationship, and the updated organization association relationship is used to identify that the target object identifier is associated with the first organization identifier.

[0152] In one possible implementation, the device 700 further includes a deletion unit:

[0153] The deletion unit is used to delete the target biological feature from the information database corresponding to the second institution identifier;

[0154] The updating unit is further configured to update the target biological characteristics to the information database corresponding to the first institution identifier.

[0155] In one possible implementation, the push unit 703 is specifically used for:

[0156] The updated content of the information database corresponding to the first institution identifier is determined based on the target biological characteristics;

[0157] The updated content is pushed to the local device of the organization corresponding to the first organization identifier.

[0158] In one possible implementation, the device 700 further includes a transfer unit:

[0159] The acquisition unit 701 is further configured to acquire a feature value transfer request sent by the local device of the institution, wherein the feature value transfer request includes the identity information corresponding to the target biological feature and the feature value to be transferred;

[0160] The determining unit 702 is further configured to determine the social media account associated with the target object identifier based on the identity information;

[0161] The transfer unit is used to transfer the feature value from the social account to the institutional account corresponding to the first institutional identifier.

[0162] In one possible implementation, the device 700 further includes a generation unit:

[0163] The acquisition unit 701 is further configured to acquire a feature registration request sent by the terminal device, the feature registration request including the target biological feature and the second institution identifier;

[0164] The generation unit is used to generate a corresponding target object identifier based on the target biological characteristics, and return the target object identifier to the terminal device.

[0165] The update unit is further configured to update the target object identifier to the information database corresponding to the second organization identifier.

[0166] In one possible implementation, the target object is a student, and the social media account is registered either by the user corresponding to the target object identifier or by the parent of the user corresponding to the target object identifier.

[0167] In one possible implementation, the target biological feature includes any one or more of facial features, fingerprint features, voiceprint features, or iris features.

[0168] This application also provides another data migration apparatus. See [link to previous document]. Figure 8 , Figure 8 This is a schematic diagram of another data migration device provided in an embodiment of this application. Figure 8 As shown, the data migration device 800 includes an acquisition unit 801, a sending unit 802, and an update unit 803:

[0169] The acquisition unit 801 is used to acquire the target object identifier through the local device of the organization corresponding to the first organization identifier;

[0170] The acquisition unit 801 is further configured to acquire the first organization identifier from the organization's local device if it is determined that the target object identifier is not associated with the first organization identifier;

[0171] The sending unit 802 is used to send a feature migration request generated based on the first institution identifier and the target object identifier to the server. The feature migration request is used to request the acquisition of the target biological feature corresponding to the target object identifier.

[0172] The update unit 803 is used to update the information database of the institution's local device according to the target biological characteristics returned by the server, and the institution's local device is used to determine the corresponding object identifier according to the collected biological characteristics.

[0173] In one possible implementation, the acquisition unit 801 is used to acquire the target object identifier from the target device via the local device of the organization using near-field communication.

[0174] In one possible implementation, the target device includes a card device or a terminal device with near-field communication capabilities.

[0175] This application embodiment also provides a data migration system, the system including an organization local device and a server corresponding to a first organization identifier:

[0176] The local device of the institution is used to obtain the target object identifier; if it is determined that the target object identifier is not associated with the first institution identifier, the first institution identifier is obtained from the local device of the institution; a feature migration request generated based on the first institution identifier and the target object identifier is sent to the server, the feature migration request being used to request the acquisition of the target biological feature corresponding to the target object identifier;

[0177] The server is configured to: receive a feature migration request sent by the local device of the institution corresponding to the first institution identifier; determine the corresponding institution association relationship based on the target object identifier, wherein the institution association relationship is used to identify that the target object identifier is associated with the second institution identifier; obtain the target biological feature corresponding to the target object identifier from the information database corresponding to the second institution identifier; and push the target biological feature to the local device of the institution.

[0178] The local device of the institution is also used to update the information database of the local device of the institution according to the target biological characteristics returned by the server, and the local device of the institution is used to determine the corresponding object identifier according to the collected biological characteristics.

[0179] The data migration apparatus or system provided in the above embodiments, in a scenario where the institution receiving the service for the target object changes from a second institution to a first institution, initiates a feature migration request from the local device of the institution corresponding to the first institution's identifier. This feature migration request includes the target object identifier and the first institution's identifier. Before the institution change, the target object is an object of the second institution, and the institution association relationship corresponding to the target object identifier is used to identify the association between the target object identifier and the second institution identifier. Based on the institution association relationship, the second institution identifier associated with the target object identifier is determined. The target biological feature corresponding to the target object identifier is obtained from the information database corresponding to the second institution identifier, and the target biological feature is pushed to the local device of the institution corresponding to the first institution identifier, thus realizing the automatic migration of the target object's target biological feature from the second institution to the first institution. Since the local device of the institution can determine the object identifier based on the collected biological features, after the biological feature migration is completed, the local device of the first institution can determine the target object identifier based on the target object's biological features. This avoids the need for the target object to re-register the collected object information for the first institution, simplifies the biological feature migration operation process during institution changes, and improves the user experience.

[0180] This application also provides a computer device, which will be described below from the perspective of hardware implementation.

[0181] See Figure 9 , Figure 9 This is a schematic diagram of a server structure provided in an embodiment of this application. The server 1400 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 1422 (e.g., one or more processors) and memory 1432, and one or more storage media 1430 (e.g., one or more mass storage devices) for storing application programs 1442 or data 1444. The memory 1432 and storage media 1430 can be temporary or persistent storage. The program stored in the storage media 1430 may include one or more modules (not shown in the diagram), each module may include a series of instruction operations on the server. Furthermore, the CPU 1422 may be configured to communicate with the storage media 1430 and execute the series of instruction operations in the storage media 1430 on the server 1400.

[0182] Server 1400 may also include one or more power supplies 1426, one or more wired or wireless network interfaces 1450, one or more input / output interfaces 1458, and / or one or more operating systems 1441, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0183] The steps performed by the server in the above embodiments can be based on this Figure 9 The server structure shown.

[0184] CPU 1422 is used to perform the following steps:

[0185] Obtain the feature migration request sent by the local device of the organization corresponding to the first organization identifier, wherein the feature migration request includes the target object identifier and the first organization identifier;

[0186] The corresponding organizational relationship is determined based on the target object identifier, and the organizational relationship is used to identify that the target object identifier is associated with the second organizational identifier;

[0187] Obtain the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second institution identifier;

[0188] The target biological features are pushed to the institution's local device, which is used to determine the corresponding object identifier based on the collected biological features.

[0189] Alternatively, CPU1422 can be used to perform the following steps:

[0190] The target object identifier is obtained through the local device of the organization corresponding to the first organization identifier;

[0191] If it is determined that the target object identifier is not associated with the first organization identifier, the first organization identifier is obtained from the organization's local device;

[0192] Send a feature migration request generated based on the first institution identifier and the target object identifier to the server. The feature migration request is used to request the acquisition of the target biological features corresponding to the target object identifier.

[0193] The information database of the institution's local device is updated based on the target biological characteristics returned by the server, and the institution's local device is used to determine the corresponding object identifier based on the collected biological characteristics.

[0194] Optionally, the CPU 1422 can also execute the data migration method provided in the above embodiments, which will not be described in detail here.

[0195] In addition to the data migration method described above, this application also provides a terminal device for data migration, so that the above data migration method can be implemented and applied in practice.

[0196] See Figure 10 , Figure 10 This is a schematic diagram of a terminal device provided in an embodiment of this application. For ease of explanation, only the parts related to the embodiments of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of this application. The terminal device can be any terminal device, including mobile phones, tablet computers, personal digital assistants (PDAs), etc. Taking a mobile phone as an example:

[0197] Figure 10 This diagram illustrates a partial structural representation of a mobile phone related to the terminal device provided in this embodiment. (Reference) Figure 10 The mobile phone includes components such as a radio frequency (RF) circuit 1510, a memory 1520, an input unit 1530, a display unit 1540, a sensor 1550, an audio circuit 1560, a wireless fidelity (WiFi) module 1570, a processor 1580, and a power supply 1590. Those skilled in the art will understand that... Figure 10 The mobile phone structure shown does not constitute a limitation on the mobile phone and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0198] The following is combined Figure 10 A detailed introduction to each component of a mobile phone:

[0199] RF circuit 1510 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and processes it with processor 1580; additionally, it transmits uplink data to the base station. Typically, RF circuit 1510 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier (LNA), and a duplexer. Furthermore, RF circuit 1510 can also communicate wirelessly with networks and other devices. The aforementioned wireless communication can use any communication standard or protocol, including but not limited to Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, and Short Messaging Service (SMS).

[0200] The memory 1520 can be used to store software programs and modules. The processor 1580 runs the software programs and modules stored in the memory 1520 to realize various functions and data migration of the mobile phone. The memory 1520 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 1520 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0201] The input unit 1530 can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of the mobile phone. Specifically, the input unit 1530 may include a touch panel 1531 and other input devices 1532. The touch panel 1531, also known as a touch screen, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel 1531), and drive the corresponding connection devices according to a pre-set program. Optionally, the touch panel 1531 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 1580, and can also receive and execute commands sent by the processor 1580. In addition, the touch panel 1531 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 1531, the input unit 1530 may also include other input devices 1532. Specifically, other input devices 1532 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0202] The display unit 1540 can be used to display information input by the user or information provided to the user, as well as various menus of the mobile phone. The display unit 1540 may include a display panel 1541, which may optionally be configured as a Liquid Crystal Display (LCD), Organic Light-Emitting Diode (OLED), or similar display panel. Further, a touch panel 1531 may cover the display panel 1541. When the touch panel 1531 detects a touch operation on or near it, it transmits the information to the processor 1580 to determine the type of touch event. Subsequently, the processor 1580 provides corresponding visual output on the display panel 1541 based on the type of touch event. Although in Figure 10 In this embodiment, the touch panel 1531 and the display panel 1541 are two separate components to realize the input and output functions of the mobile phone. However, in some embodiments, the touch panel 1531 and the display panel 1541 can be integrated to realize the input and output functions of the mobile phone.

[0203] The mobile phone may also include at least one sensor 1550, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 1541 according to the ambient light level, and the proximity sensor can turn off the display panel 1541 and / or the backlight when the phone is moved to the ear. As a type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition-related functions (such as pedometer, tapping), etc. Other sensors that may be configured in the mobile phone, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0204] Audio circuit 1560, speaker 1561, and microphone 1562 provide an audio interface between the user and the mobile phone. Audio circuit 1560 converts received audio data into electrical signals and transmits them to speaker 1561, where speaker 1561 converts them into sound signals for output. On the other hand, microphone 1562 converts collected sound signals into electrical signals, which are received by audio circuit 1560, converted into audio data, and then processed by processor 1580 before being transmitted via RF circuit 1510 to, for example, another mobile phone, or the audio data can be output to memory 1520 for further processing.

[0205] WiFi is a short-range wireless transmission technology. Through the WiFi module 1570, mobile phones can help users send and receive emails, browse web pages, and access streaming media, providing users with wireless broadband internet access. Although Figure 10 WiFi module 1570 is shown, but it is understood that it is not an essential component of a mobile phone and can be omitted as needed without changing the essence of the invention.

[0206] The processor 1580 is the control center of the mobile phone, connecting various parts of the phone through various interfaces and lines. It performs various functions and processes data by running or executing software programs and / or modules stored in the memory 1520 and calling data stored in the memory 1520. Optionally, the processor 1580 may include one or more processing units; preferably, the processor 1580 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 1580.

[0207] The mobile phone also includes a power supply 1590 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 1580 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system.

[0208] Although not shown, mobile phones may also include a camera, Bluetooth module, etc., which will not be described in detail here.

[0209] In this embodiment of the application, the memory 1520 included in the mobile phone can store program code and transmit the program code to the processor.

[0210] The processor 1580 included in the mobile phone can execute the data migration method provided in the above embodiments according to the instructions in the program code, which will not be described in detail here.

[0211] This application also provides a computer-readable storage medium for storing a computer program that performs the data migration method provided in the above embodiments.

[0212] This application also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the data migration method provided in various optional implementations of the above aspects.

[0213] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium can be at least one of the following media: read-only memory (ROM), RAM, magnetic disk or optical disk, and other media capable of storing program code.

[0214] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0215] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data migration method, characterized in that, The method includes: When the organization where the target object is located changes, obtain the feature migration request sent by the local device of the organization corresponding to the first organization identifier. The feature migration request includes the target object identifier and the first organization identifier. The corresponding organizational relationship is determined based on the target object identifier, and the organizational relationship is used to identify that the target object identifier is associated with the second organizational identifier; Obtain the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second institution identifier; The target biological features are pushed to the local device of the institution, which is used to determine the corresponding object identifier based on the collected biological features; Update the organization association relationship, and the updated organization association relationship is used to identify that the target object identifier is associated with the first organization identifier; The target biological characteristic is deleted from the information database corresponding to the second institution's identifier; and The target biological characteristics are updated in the information database corresponding to the first institution identifier.

2. The method according to claim 1, characterized in that, Pushing the target biological features to the local device of the institution corresponding to the first institution identifier includes: The updated content of the information database corresponding to the first institution identifier is determined based on the target biological characteristics; The updated content is pushed to the local device of the organization corresponding to the first organization identifier.

3. The method according to claim 1, characterized in that, After pushing the target biological feature to the institution's local device, the method further includes: Obtain a feature value transfer request sent by the institution's local device, the feature value transfer request including the identity information corresponding to the target biological feature and the feature value to be transferred; Based on the identity information, determine the social media account associated with the target object identifier; The feature value is transferred from the social media account to the institutional account corresponding to the first institutional identifier.

4. The method according to claim 1, characterized in that, The method further includes: Obtain a feature registration request sent by the terminal device, the feature registration request including the target biological feature and the second institution identifier; Generate a corresponding target object identifier based on the target biological characteristics, and return the target object identifier to the terminal device; Update the target object identifier to the information database corresponding to the second organization identifier.

5. The method according to claim 3, characterized in that, The target audience is students, and the social media accounts are registered either through the user corresponding to the target audience identifier or through the parent of the user corresponding to the target audience identifier.

6. The method according to claim 1, characterized in that, The target biological features include any combination of one or more of the following: facial features, fingerprint features, voiceprint features, or iris features.

7. A data migration method, characterized in that, The method includes: When the organization where the target object is located changes, the target object identifier is obtained through the local device of the organization corresponding to the first organization identifier; the first organization identifier is used to identify the first organization, which is the organization after the change. If it is determined that the target object identifier is not associated with the first organization identifier, the first organization identifier is obtained from the organization's local device; A feature migration request generated based on the first institution identifier and the target object identifier is sent to the server. The feature migration request is used to request the acquisition of the target biological feature corresponding to the target object identifier based on the institution association relationship. The institution association relationship is used to identify the mapping relationship between the target object identifier and the second institution identifier, the second institution identifier is used to identify the second institution, and the second institution is the institution before the change. The local device updates the information database of the institution based on the target biological features returned by the server, and deletes the target biological features from the information database corresponding to the second institution identifier. The local device of the institution is used to determine the corresponding object identifier based on the collected biological features.

8. The method according to claim 7, characterized in that, The step of obtaining the target object identifier through the local device of the institution corresponding to the first institution identifier includes: The target object identifier is obtained from the target device via the local device of the institution using near-field communication.

9. The method according to claim 8, characterized in that, The target device includes a card device or a terminal device with near-field communication functionality.

10. A data migration device, characterized in that, The device includes an acquisition unit, a determination unit, and a push unit: The acquisition unit is used to acquire a feature migration request sent by the local device of the organization corresponding to the first organization identifier when the organization where the target object is located changes. The feature migration request includes the target object identifier and the first organization identifier. The determining unit is used to determine the corresponding organizational association relationship based on the target object identifier, wherein the organizational association relationship is used to identify that the target object identifier is associated with the second organizational identifier; The acquisition unit is further configured to acquire the target biological characteristics corresponding to the target object identifier from the information database corresponding to the second institution identifier; The push unit is used to push the target biological features to the local device of the institution, and the local device of the institution is used to determine the corresponding object identifier based on the collected biological features; The device also includes an update unit: The updating unit is used to update the organization association relationship, and the updated organization association relationship is used to identify that the target object identifier is associated with the first organization identifier; The device also includes a deletion unit: The deletion unit is used to delete the target biological feature from the information database corresponding to the second institution identifier; The updating unit is further configured to update the target biological characteristics to the information database corresponding to the first institution identifier.

11. The apparatus according to claim 10, characterized in that, The push unit is specifically used for: The updated content of the information database corresponding to the first institution identifier is determined based on the target biological characteristics; The updated content is pushed to the local device of the organization corresponding to the first organization identifier.

12. The apparatus according to claim 10, characterized in that, The device also includes a transfer unit: The acquisition unit is further configured to acquire a feature value transfer request sent by the institution's local device, the feature value transfer request including the identity information corresponding to the target biological feature and the feature value to be transferred; The determining unit is further configured to determine the social media account associated with the target object identifier based on the identity information; The transfer unit is used to transfer the feature value from the social account to the institutional account corresponding to the first institutional identifier.

13. The apparatus according to claim 10, characterized in that, The device further includes a generation unit: The acquisition unit is further configured to acquire a feature registration request sent by the terminal device, the feature registration request including the target biological feature and the second institution identifier; The generation unit is used to generate a corresponding target object identifier based on the target biological characteristics, and return the target object identifier to the terminal device. The update unit is further configured to update the target object identifier to the information database corresponding to the second organization identifier.

14. The apparatus according to claim 12, characterized in that, The target audience is students, and the social media accounts are registered either through the user corresponding to the target audience identifier or through the parent of the user corresponding to the target audience identifier.

15. The apparatus according to claim 10, characterized in that, The target biological features include any combination of one or more of the following: facial features, fingerprint features, voiceprint features, or iris features.

16. A data migration device, characterized in that, The device includes an acquisition unit, a transmission unit, and an update unit: The acquisition unit is used to acquire the target object identifier through the local device of the organization corresponding to the first organization identifier when the organization where the target object is located changes; the first organization identifier is used to identify the first organization, and the first organization is the organization after the change; The acquisition unit is further configured to acquire the first organization identifier from the organization's local device if it is determined that the target object identifier is not associated with the first organization identifier; The sending unit is configured to send a feature migration request generated based on the first institution identifier and the target object identifier to the server. The feature migration request is used to request the acquisition of the target biological feature corresponding to the target object identifier based on the institution association relationship. The organizational association is used to identify the mapping relationship between the target object identifier and the second organizational identifier, where the second organizational identifier is used to identify the second organizational entity, which is the organizational entity before the change. The update unit is used to update the information database of the institution's local device according to the target biological characteristics returned by the server, and to delete the target biological characteristics from the information database corresponding to the second institution identifier. The institution's local device is used to determine the corresponding object identifier based on the collected biological characteristics.

17. The apparatus according to claim 16, characterized in that, The acquisition unit is used to acquire the target object identifier from the target device through the local device of the institution based on near-field communication.

18. The apparatus according to claim 17, characterized in that, The target device includes a card device or a terminal device with near-field communication functionality.

19. A computer device, characterized in that, The computer device includes a processor and memory: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the method according to any one of claims 1-6, or to execute the method according to any one of claims 7-9, based on instructions in the program code.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for performing the method according to any one of claims 1-6, or for performing the method according to any one of claims 7-9.

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