An old-age pension credit right clearing system based on edge trust and blockchain oracle

Abstract

The application provides an old-age pension credit right clearing system based on edge credibility and a blockchain oracle, which comprises a data collection unit: deployed on an old-age robot edge side TEE security chip, used for collecting multi-modal service completion original sensing data of the robot in real time at two nodes of old-age service starting and ending, and storing all the original sensing data in the TEE security chip in isolation. The old-age pension credit right clearing system based on edge credibility and the blockchain oracle provided by the application can encrypt the original data of the old-age service by setting the data collection unit, a data management unit, an old-age pension credit auditing unit and a record tracking unit, so that the leakage of privacy information in plaintext is prevented. Meanwhile, by building diversified credit exchange channels, the operation cost of manual auditing, data statistics, account settlement and the like of the old-age institution is reduced, and the intelligent operation level of the old-age service credit management is improved.

Description

Technical Field

[0001] This application relates to the field of smart elderly care technology, and in particular to an elderly care points confirmation and settlement system based on edge trust and blockchain oracles. Background Technology

[0002] With the rapid development of the smart elderly care industry, elderly care service robots such as companionship, nursing, and cleaning have been widely used in home-based and community-based elderly care scenarios. Elderly care service robots integrate multiple functions such as vital sign monitoring, daily living assistance, safety warning, rehabilitation companionship, and intelligent voice interaction. They are adapted to the physiological characteristics of the elderly, such as limited mobility, declining self-care ability, and susceptibility to sudden health conditions. They can autonomously complete various elderly care assistance tasks, effectively make up for the shortage of nursing manpower, and are intelligent devices for addressing population aging.

[0003] Existing smart elderly care point-based incentive systems primarily collect data on elderly service behaviors and care details through elderly care terminal devices. A backend server then tracks service frequency and duration, manually calculating and distributing points according to fixed standards. However, to achieve traceable verification of elderly care service behaviors, it is necessary to upload and store raw business data such as elderly person's identity information, health data, and care operation details in plaintext. Some solutions even store the complete raw data on the blockchain, which can easily lead to the leakage of user privacy information. Furthermore, existing technologies struggle to verify the authenticity of elderly care service completion and effectiveness while protecting privacy, making it impossible to objectively measure the actual value of elderly care services. This reduces the acceptance and willingness to participate in the elderly care point-based incentive system among both the elderly and caregivers. Summary of the Invention

[0004] This application aims to at least partially solve one of the technical problems in the aforementioned technologies.

[0005] Therefore, one objective of this application is to propose a pension points confirmation and settlement system based on edge trust and blockchain oracles, which can encrypt the original data of pension services to prevent the leakage of privacy information in plaintext. At the same time, by building diversified points redemption channels, it can reduce the operating costs of pension institutions such as manual review, data statistics, and accounting settlement, and improve the intelligent operation level of pension service points management.

[0006] To achieve the above objectives, the first aspect of this application proposes a pension points confirmation and settlement system based on edge trust and blockchain oracles, comprising: a data collection unit: deployed on the TEE security chip at the edge of the pension robot, used to collect the robot's multimodal service completion raw sensor data in real time at the two nodes of pension service initiation and termination. All raw sensor data is isolated and stored within the TEE secure chip, generating a local session identifier that binds the robot to a unique hardware identifier and the chip's trusted clock. The data management unit verifies the integrity and authenticity of the collected raw sensor data using a built-in trusted measurement program, eliminating abnormal and tampered data. It generates an immutable global timestamp signature using the TEE's built-in trusted clock and performs desensitization and encryption operations on sensitive privacy data in the raw data using a built-in zero-knowledge proof circuit, outputting a desensitized and encrypted data packet that can be securely transmitted on the blockchain. The elderly care points auditing unit uses a dynamic weighting algorithm to update the points calculation mapping rules for various elderly care services in real time. Based on the updated rules, it calculates the points for each elderly care service, and an oracle cluster verifies the legality of the calculation results through multi-signature verification, generating a points calculation certificate carrying the oracle's collective digital signature. This certificate, along with the desensitized and encrypted data packet, is then synchronously transmitted back to the consortium blockchain to complete pre-confirmation and notarization. The record tracking unit uses a triple verification mechanism to verify the notarized data and aggregates the valid service points for each service into the corresponding elderly person's on-chain account.

[0007] In addition, the pension points rights confirmation and settlement system based on edge trust and blockchain oracles proposed in this application may also have the following additional technical features:

[0008] Specifically, it also includes: a clearing and redemption unit: used to open a family objection freeze window when the accumulated points in the elderly's account reach the preset redemption threshold. If there is no valid objection during the objection window or the objection is rejected after verification, the clearing and redemption will be carried out through the real-time points redemption exchange rate of the oracle; and a data security management unit: used to summarize the data of the entire business chain after the clearing and redemption process is completed, and package, archive and encrypt the data for storage, so as to provide audit and traceability certificates for regulatory agencies and elderly care institutions.

[0009] Specifically, the raw sensor data includes physical parameter change data of nursing devices, interactive behavior data of companion devices, and environmental monitoring data of cleaning devices.

[0010] Specifically, the data collection unit includes: a control module for issuing collection signals at the start and end of elderly care services; a collection module for receiving collection signals from the control module and synchronously collecting multimodal raw sensor data corresponding to nursing equipment, companion equipment, and cleaning equipment; a data storage module for receiving multimodal raw sensor data collected by the collection module, encrypting and isolating the multimodal raw sensor data for storage, and prohibiting the robot's rich operating system from reading or modifying the stored data; and a generation module for generating a uniquely bound local session identifier for each elderly care service based on the trusted clock built into the TEE chip and the robot's fixed unique hardware identifier, and synchronously pushing the encrypted raw sensor data and the local session identifier to the data management unit.

[0011] Specifically, the workflow of the data management unit is as follows: S1: Using a trusted measurement program embedded in the TEE security domain, the encrypted original sensor data and local session identifier are verified, and abnormal sensor data that is distorted, tampered with, or out of sequence is identified and eliminated; S2: The verified sensor data and local session identifier are signed using the robot's TEE private key to generate a global timestamp signature with tamper-proof and globally verifiable attributes; S3: The encrypted operation is completed in the TEE security domain through the built-in zero-knowledge proof circuit to remove sensitive privacy plaintext from the original data and generate a ZKP service certificate and an irreversible service type hash value; S4: The ZKP service certificate, type hash value, global timestamp signature, and robot's unique hardware identifier are uniformly encrypted and encapsulated to generate a desensitized encrypted data package for use by the pension points audit unit.

[0012] Specifically, the elderly care points auditing unit includes: an information announcement module for connecting to a decentralized oracle cluster to obtain external multi-source data in real time and perform noise reduction and weighted preprocessing on the multi-source data; a calculation module for iteratively updating the points calculation mapping rules corresponding to each category of elderly care services based on the preprocessed multi-source authoritative data; a points calculation module for matching the corresponding points calculation mapping rules according to the service type hash value in the desensitized encrypted data packet to calculate the rights points that can be issued for this elderly care service; a verification module for using the oracle cluster to perform distributed multi-signature verification on the calculation results, and generating a points calculation certificate with the collective digital signature of the oracle cluster after the verification is passed; and a storage module for packaging and uploading the desensitized encrypted data packet and the points calculation certificate with the collective signature to the consortium blockchain node for pre-confirmation and notarization, and sending the notarization receipt returned by the consortium blockchain to the record tracking unit.

[0013] Specifically, the external multi-source data includes the Civil Affairs Bureau's guidance price for elderly care services, community family satisfaction votes, long-term care insurance subsidy standards, and the elderly care service market.

[0014] Specifically, the real-time acquisition of external multi-source data and the denoising and weighted preprocessing of the multi-source data include: using the 3σ confidence interval anomaly detection method to perform steady-state filtering on the collected multi-source raw data, calculating the mean and standard deviation of a single data source, and removing abrupt abnormal data, duplicate dirty data, and lagging invalid data that exceed three times the standard deviation interval, thereby denoising the multi-source raw data; using the Analytic Hierarchy Process (AHP) multidimensional weighting algorithm to assign weights to the denoised data, and generating a service value coefficient of a unified dimension through multi-level weight normalization operations, providing a standardized quantitative input basis for the dynamic weight calculation module to update the integral accrual mapping rules.

[0015] Specifically, the record tracking unit includes: a data receiving module for receiving pre-confirmation and evidence storage data packets returned by the consortium blockchain in real time; a document management module for verifying the ZKP service certificate, type hash value, and global timestamp signature in the pre-confirmation and evidence storage data packets; if any one of the verifications fails, the service points confirmation is rejected, and if all verifications pass, the elderly care service is deemed authentic and valid; and an accounting module for automatically transferring the rights and interests points corresponding to a single service to the elderly person's personal points account after successful verification, thus completing the irreversible real-time points confirmation and accounting.

[0016] Specifically, the record tracking unit also includes a data maintenance module for real-time updating and archiving of the points confirmation transaction records of elderly accounts; and a data distribution module for real-time synchronous push of the confirmed elderly points account data and valid service evidence transaction records to the clearing and redemption unit, providing reliable on-chain data support for subsequent points redemption threshold determination, objection freezing, and clearing and redemption.

[0017] Compared with existing technologies, this application has the following beneficial effects: The elderly care points confirmation and settlement system based on edge trust and blockchain oracles in this application encrypts the original data of elderly care services by setting up a data collection unit, a data management unit, an elderly care points audit unit, and a record tracking unit to prevent the leakage of privacy information in plaintext. In the service quantification and points confirmation process, dynamic weighting algorithms and oracle multi-source data correction mechanisms are combined to improve the fairness and credibility of points confirmation. At the same time, by building diversified points redemption channels, the operating costs of elderly care institutions such as manual review, data statistics, and accounting settlement are reduced, and the intelligent operation level of elderly care service points management is improved.

[0018] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0019] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0020] Figure 1 This is a schematic diagram of a pension points confirmation and settlement system module based on edge trust and blockchain oracle according to an embodiment of this application;

[0021] Figure 2 This is a diagram of the data collection unit architecture.

[0022] Figure 3 This is a diagram of the pension points-based audit unit architecture. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0024] The following describes an embodiment of the pension points confirmation and settlement system based on edge trust and blockchain oracle, with reference to the accompanying drawings.

[0025] like Figures 1-3 As shown in the figure, an embodiment of this application provides a pension points rights confirmation and settlement system based on edge trust and blockchain oracles, comprising:

[0026] Data collection unit: Deployed on the TEE security chip at the edge of the elderly care robot, it is used to collect the original sensor data of the robot's multimodal service completion in real time at the two nodes of the start and end of the elderly care service, and store all the original sensor data in isolation within the TEE security chip, generating a local session identifier that binds the robot's unique hardware identifier and the chip's trusted clock.

[0027] The raw sensor data includes physical parameter change data of nursing devices, interactive behavior data of companion devices, and environmental monitoring data of cleaning devices.

[0028] The data collection unit includes: a control module for sending collection signals at the start and end of elderly care services; a collection module for receiving collection signals from the control module and synchronously collecting multimodal raw sensor data corresponding to nursing equipment, companion equipment, and cleaning equipment; a data storage module for receiving multimodal raw sensor data collected by the collection module, encrypting and isolating the multimodal raw sensor data for storage, and prohibiting the robot's rich operating system from reading or modifying the stored data; and a generation module for generating a uniquely bound local session identifier for each elderly care service based on the trusted clock built into the TEE chip and the robot's fixed unique hardware identifier, and synchronously pushing the encrypted raw sensor data and the local session identifier to the data management unit.

[0029] For example, based on the real-time monitoring of the elderly care robot service scheduling instructions by the control module, when starting and stopping, the system collects data on changes in physical parameters such as changes in the weight of waste, nursing operation time, and frequency of limb assistive movements for nursing equipment; it collects data on interactive behaviors such as the number of voice interaction rounds, human body sensing duration, and response effectiveness for companionship equipment; and it collects environmental monitoring data such as the infrared turbidity difference of the dust box, the coverage area of ​​the cleaning area, and the equipment's operating trajectory for cleaning equipment, thus achieving multi-dimensional quantitative evidence collection of the effectiveness of elderly care services.

[0030] Data Management Unit: The unit verifies the integrity and authenticity of the collected raw sensor data through a built-in trusted measurement program, removes abnormal and tampered data, generates an immutable global timestamp signature using the TEE's built-in trusted clock, and performs desensitization and encryption operations on sensitive privacy data in the raw data through a built-in zero-knowledge proof circuit, outputting a desensitized and encrypted data packet that can be securely transmitted to the blockchain.

[0031] The workflow of the data management unit is as follows: S1: Using the trusted measurement program embedded in the TEE security domain, the encrypted original sensor data and local session identifier are verified, and abnormal sensor data that is distorted, tampered with, or out of sequence is identified and eliminated; S2: The verified sensor data and local session identifier are signed using the robot's TEE private key to generate a global timestamp signature with tamper-proof and globally verifiable attributes; S3: The encrypted operation is completed in the TEE security domain through the built-in zero-knowledge proof circuit to remove sensitive privacy plaintext from the original data and generate ZKP service proof and irreversible service type hash value; S4: The ZKP service proof, type hash value, global timestamp signature, and robot's unique hardware identifier are uniformly encrypted and encapsulated to generate a de-identified encrypted data package for use by the pension points audit unit.

[0032] To illustrate, the Trusted Execution Environment (TEE) security domain enables closed-loop data processing throughout the entire process. All calculations and processing flows are completed within an independent security domain, avoiding security risks such as data tampering and data leakage from the upper-level operating system. At the same time, the built-in trusted measurement program can identify various invalid and abnormal data, such as abnormal jumps in sensor data, manual batch tampering, and disordered business service timing, and automatically filter and remove them to ensure the authenticity, validity, and reliability of the collected data.

[0033] At the same time, trusted verification under privacy protection is achieved through zero-knowledge proof circuits. Without disclosing sensitive and private plaintext data such as elderly people's identity information, health data, and nursing service details, it generates publicly verifiable service validity certificates and service type hash values. This ensures that the business requirements of data verifiability, traceability, and immutability in the consortium blockchain notarization scenario are met, and achieves full-process isolation and protection of user privacy data.

[0034] The elderly care points audit unit uses a dynamic weighting algorithm to update the points calculation mapping rules corresponding to various elderly care services in real time. Based on the updated points calculation mapping rules, it completes the points calculation for a single elderly care service. The oracle cluster performs multi-signature legality verification on the points calculation results, generates points calculation vouchers carrying the collective digital signature of the oracles, and synchronously transmits the points calculation vouchers and desensitized encrypted data packets back to the consortium blockchain to complete the pre-confirmation of rights and evidence storage.

[0035] The elderly care points auditing unit includes: an information announcement module (for connecting to a decentralized oracle cluster to acquire external multi-source data in real time and perform noise reduction and weighted preprocessing on the multi-source data); a calculation module (for iteratively updating the points calculation mapping rules corresponding to each category of elderly care services based on the preprocessed multi-source authoritative data); a points calculation module (for matching the service type hash value in the desensitized encrypted data packet with the corresponding points calculation mapping rule to calculate the points that can be issued for this elderly care service); a verification module (for using the oracle cluster to perform distributed multi-signature verification on the calculation results, and generating a points calculation voucher with the collective digital signature of the oracle cluster after successful verification); and a storage module (for packaging and uploading the desensitized encrypted data packet and the points calculation voucher with the collective signature to the consortium blockchain node for pre-confirmation and notarization, and sending the notarization receipt returned by the consortium blockchain to the record tracking unit).

[0036] External multi-source data includes the Civil Affairs Bureau's guidance price for elderly care services, community family satisfaction votes, long-term care insurance subsidy standards, and the elderly care service market.

[0037] The system acquires external multi-source data in real time and performs denoising and weighted preprocessing on the multi-source data. This includes: using the 3σ confidence interval anomaly detection method to perform steady-state filtering on the collected multi-source raw data; calculating the mean and standard deviation of a single data source; and removing abrupt abnormal data, duplicate dirty data, and lagging invalid data that exceed three times the standard deviation interval to denoise the multi-source raw data. The system also uses the Analytic Hierarchy Process (AHP) multidimensional weighting algorithm to assign weights to the denoised data and generate a unified-dimensional service value coefficient through multi-level weight normalization operations. This provides a standardized quantitative input basis for the dynamic weight calculation module to update the integral calculation mapping rules.

[0038] To illustrate with an example, the system acquires multi-source data, including current service benchmark prices released by the civil affairs department, monthly family satisfaction scores, long-term care insurance subsidy levels, and market service supply and demand. It then uses the 3σ confidence interval anomaly detection method to filter out invalid and corrupt data left over from network fluctuations, duplicate voting, and policy lags. Finally, it uses the AHP (Analytic Hierarchy Process) algorithm to perform weighted normalization on the compliant data, generating standardized value coefficients for the corresponding services.

[0039] Record Tracking Unit: Utilizing a triple verification mechanism, the stored data is verified, and the points for each valid service are collected and credited to the corresponding elderly person's on-chain account.

[0040] The record tracking unit includes: a data receiving module for receiving pre-confirmation and evidence storage data packets returned by the consortium blockchain in real time; a document management module for verifying the ZKP service certificate, type hash value, and global timestamp signature in the pre-confirmation and evidence storage data packets; if any one of the verifications fails, the service points confirmation is rejected, and if all verifications pass, the elderly care service is deemed authentic and valid; and an accounting module for automatically transferring the rights and points corresponding to a single service to the elderly person's personal points account after successful verification, completing the irreversible real-time points confirmation and accounting.

[0041] The record tracking unit also includes a data maintenance module: used to update and archive the points confirmation and transaction records of elderly accounts in real time; and a data distribution module: used to push the data of elderly points accounts with completed confirmation and valid service evidence records to the clearing and redemption unit in real time, providing reliable on-chain data support for subsequent points redemption threshold determination, objection freezing and clearing and redemption.

[0042] To illustrate with an example, a multi-verification mechanism is used to sequentially verify the validity of the ZKP service certificate, the consistency of the service type hash value, and the authenticity of the global timestamp signature within the data packet. If any one of the verifications fails, the application for points confirmation is rejected and the service is deemed invalid. Only after all three verifications pass can the authenticity and compliance of the elderly care service be determined, providing reliable data support for subsequent determination of points redemption thresholds, freezing of disputed data, and compliant liquidation and redemption.

[0043] A pension points rights confirmation and settlement system based on edge trust and blockchain oracles also includes: a settlement and exchange unit: used to open a family objection freeze window when the accumulated points in the elderly's account reach the preset redemption threshold. If there is no valid objection within the objection window or the objection is rejected after verification, the points are redeemed through the real-time points rights exchange rate of the oracle; and a data security management unit: used to summarize the data of the entire business chain after the settlement process is completed, and package, archive and encrypt the data for storage, providing audit and traceability certificates for regulatory agencies and elderly care institutions.

[0044] For example, the system monitors the accumulated amount in the elderly's on-chain points account in real time. When the account points reach the system's preset redemption threshold, an objection freeze mechanism is automatically triggered, opening a window period for family members to file objections. During this window period, family members can view the anonymized service record summary information through their terminal devices. If they have any objections to the authenticity of the service or the amount of points, they can submit an appeal application to trace and verify the entire chain of record data. Furthermore, the unit retrieves the points redemption exchange rate updated in real time by the oracle cluster and executes compliant points redemption operations. It supports two redemption modes that can be switched freely: one is to redeem points for electronic vouchers from partner elderly care merchants and supermarkets, and the other is to directly deduct points from the elderly's next long-term care insurance personal payment, ensuring that the funds and rights redemption comply with the regulatory standards of civil affairs and medical insurance.

[0045] In summary, this application's elderly care points confirmation and settlement system based on edge trust and blockchain oracles encrypts the original data of elderly care services by setting up a data collection unit, a data management unit, an elderly care points audit unit, and a record tracking unit, preventing the leakage of privacy information in plaintext. Furthermore, in the service quantification and points confirmation stages, it combines dynamic weighting algorithms and oracle multi-source data correction mechanisms to enhance the fairness and credibility of points confirmation. At the same time, by building diversified points redemption channels, it reduces the operating costs of elderly care institutions for manual review, data statistics, and accounting settlement, thereby improving the intelligent operation level of elderly care service points management.

[0046] In the description of this specification, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0047] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0048] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles, characterized in that, include: Data collection unit: Deployed on the TEE security chip at the edge of the elderly care robot, it is used to collect the original sensor data of the robot's multimodal service completion in real time at the two nodes of the start and end of the elderly care service, and store all the original sensor data in isolation in the TEE security chip, and generate a local session identifier that binds the robot's unique hardware identifier and the chip's trusted clock. Data Management Unit: The built-in trusted measurement program verifies the integrity and authenticity of the collected raw sensor data, removes abnormal and tampered data, generates an immutable global timestamp signature using the built-in trusted clock of the TEE, and performs desensitization and encryption operations on sensitive privacy data in the raw data through the built-in zero-knowledge proof circuit, outputting a desensitized and encrypted data packet that can be securely transmitted on the blockchain. Elderly care points audit unit: The dynamic weight algorithm is used to update the points calculation mapping rules corresponding to various elderly care services in real time. Based on the updated points calculation mapping rules, the points calculation of a single elderly care service right is completed. The oracle cluster performs multi-signature legality verification on the points calculation results, generates points calculation vouchers carrying the collective digital signature of the oracles, and synchronously transmits the points calculation vouchers and desensitized encrypted data packets back to the consortium blockchain to complete the pre-confirmation of rights and evidence storage. Record Tracking Unit: Utilizing a triple verification mechanism, the stored data is verified, and the points for each valid service are collected and credited to the corresponding elderly person's on-chain account.

2. The pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 1, characterized in that, Also includes: Clearing and redemption unit: When the accumulated points in the elderly person's account reach the preset redemption threshold, a family objection freeze window period is opened. If there is no valid objection during the objection window period or the objection is rejected after verification, the clearing and redemption will be carried out through the real-time points rights exchange rate of the oracle. Data security management unit: After the liquidation process is completed, it is used to summarize the data of the entire business chain, package and archive it with encryption and storage, and provide audit traceability credentials for regulatory agencies and elderly care institutions.

3. The pension points confirmation and settlement system based on edge trust and blockchain oracles according to claim 2, characterized in that, The raw sensor data includes physical parameter change data of nursing devices, interactive behavior data of companion devices, and environmental monitoring data of cleaning devices.

4. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 3, characterized in that, The data collection unit includes, Control module: Used to send collection signals when elderly care services are started and ended; Acquisition module: Used to receive acquisition signals from the control module and synchronously acquire multimodal raw sensor data corresponding to nursing equipment, companion equipment, and cleaning equipment; Data storage module: Used to receive multimodal raw sensor data collected by the acquisition module, encrypt and isolate the multimodal raw sensor data for storage, and prohibit the robot's rich operating system from reading or modifying the stored data; Generation module: Based on the trusted clock built into the TEE chip and the robot's fixed unique hardware identifier, a unique local session identifier is generated for each elderly care service, and the encrypted original sensor data and the local session identifier are pushed to the data management unit simultaneously.

5. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 4, characterized in that, The workflow of the data management unit is as follows: S1: Using a trusted measurement program embedded in the TEE security domain, the encrypted raw sensor data and local session identifier are verified to identify and eliminate abnormal sensor data that is distorted, tampered with, or out of sequence. S2: Use the robot's TEE private key to perform a signature operation on the verified sensor data and local session identifier to generate a global timestamp signature with tamper-proof and globally verifiable attributes; S3: The built-in zero-knowledge proof circuit performs encrypted operations within the TEE security domain, stripping sensitive privacy plaintext from the original data and generating ZKP service proof and irreversible service type hash value; S4: Unify and encrypt the ZKP service certificate, type hash value, global timestamp signature and robot's unique hardware identifier to generate a de-identified encrypted data package for use by the pension points audit unit.

6. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 5, characterized in that, The pension points auditing unit includes... Information announcement module: used to connect to a decentralized oracle cluster, obtain external multi-source data in real time, and perform noise reduction and weighted preprocessing on the multi-source data; The calculation module: Based on preprocessed multi-source authoritative data, iteratively updates the points calculation mapping rules corresponding to each category of elderly care services in real time; Points Calculation Module: Based on the service type hash value in the de-identified encrypted data packet, match the corresponding points accrual mapping rule to calculate the points that can be issued for this elderly care service; The verification module uses an oracle cluster to perform distributed multi-signature verification on the calculation results. After the verification is successful, an points calculation certificate with a collective digital signature of the oracle cluster is generated. Storage module: Used to package and upload de-identified encrypted data packets and collectively signed points calculation vouchers to the consortium blockchain node for pre-confirmation and notarization, and to send the notarization receipt returned by the consortium blockchain to the record tracking unit.

7. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 6, characterized in that, The external multi-source data includes the Civil Affairs Bureau's guidance price for elderly care services, community family satisfaction votes, long-term care insurance subsidy standards, and the elderly care service market.

8. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 7, characterized in that, The real-time acquisition of external multi-source data and the denoising and weighted preprocessing of the multi-source data include: Using the 3σ confidence interval anomaly detection method, steady-state filtering is performed on the collected multi-source raw data. The mean and standard deviation of a single data source are calculated, and jump anomaly data, duplicate dirty data and hysteresis failure data exceeding three times the standard deviation are removed, thereby denoising the multi-source raw data. By utilizing the Analytic Hierarchy Process (AHP) multidimensional weighting algorithm, weights are assigned to the denoised data. Through multi-level weight normalization operations, a service value coefficient with a unified dimension is generated, providing a standardized quantitative input basis for the dynamic weight calculation module to update the integral accrual mapping rules.

9. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 8, characterized in that, The recording and tracking unit includes, Data receiving module: used to receive pre-confirmed rights and evidence storage data packets returned by the consortium blockchain in real time; Document Management Module: Verifies the ZKP service certificate, type hash value, and global timestamp signature in the pre-confirmation and evidence storage data package. If any one of the verifications fails, the service points confirmation is rejected. If all verifications pass, the elderly care service is deemed authentic and valid. Accounting module: After successful verification, the points corresponding to each service will be automatically credited to the senior's personal points account, completing the irreversible real-time points confirmation and crediting.

10. A pension points rights confirmation and settlement system based on edge trust and blockchain oracles according to claim 9, characterized in that, The recording and tracking unit also includes, Data maintenance module: used for real-time updating and archiving of the points confirmation records for elderly accounts; Data delivery module: Used to push the data of the elderly points account after the rights have been confirmed and the valid service record to the clearing and redemption unit in real time, so as to provide reliable on-chain data support for subsequent points redemption threshold determination, objection freezing and clearing and redemption.

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