Data management method, device and equipment serving community pension and medium

Abstract

The invention discloses a data management method, device and equipment serving for community old-age care and a medium, relates to the technical field of data processing, is applied to a cloud data center, and comprises the following steps: acquiring original data related to target personnel in a community through sensor equipment; the original data comprises physiological data, behavior data and environment data; encrypting the original data through the edge node corresponding to the community, and obtaining the encrypted data; storing the encrypted data to the target block chain, so that the client provides remote service for the target personnel based on the encrypted data in the target block chain; the target block chain comprises a first block chain corresponding to the medical data type and a second block chain corresponding to the non-medical data type. Therefore, the accuracy of expressing the actual state of the target person can be improved by combining the physiological data, the behavior data and the environmental data; and the edge node performs encryption transmission, and double-chain architecture data storage is combined, so that the data processing efficiency and security can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a data management method and device for community pension services, equipment and medium. BACKGROUND

[0002] The current smart community pension solution has some problems, such as collecting physiological data (such as heart rate, blood oxygen) through wearable devices, and using fixed threshold early warning, which may cause errors in the judgment result and the actual situation, such as high temperature environment, and heart rate is easy to be misjudged as health abnormality, etc. And in terms of data storage, the medical data and business data of the elderly are mixed, the sharing of emergency medical data is delayed, and the real-time demand of the emergency scene cannot be met.

[0003] Therefore, how to optimize the data management method related to community elderly is a problem to be solved in the field. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a data management method and device for community pension services, which can combine physiological data, behavior data and environmental data to improve the accuracy of expressing the actual state of the target personnel. The edge node performs encrypted transmission, and the data storage is combined with a double-chain architecture to improve data processing efficiency and security. The specific scheme is as follows:

[0005] In a first aspect, the present application provides a data management method for community pension services, applied to a cloud data center, comprising:

[0006] Collecting raw data related to target personnel in the community through sensor devices; the raw data includes physiological data, behavior data and related environmental data of the target personnel; the target personnel is a community resident whose age meets the preset old person determination condition;

[0007] Encrypting the raw data through the edge node corresponding to the community, and obtaining the encrypted data transmitted by the edge node;

[0008] Storing the encrypted data to a target blockchain, so that a client provides remote services for the target personnel based on the encrypted data in the target blockchain; the target blockchain includes a first blockchain corresponding to medical data types and a second blockchain corresponding to non-medical data types.

[0009] Optionally, the raw data related to the target personnel in the community is collected through sensor devices, comprising:

[0010] Collecting physiological data of the target personnel through wearable devices with a sensing system worn by the target personnel in the community;

[0011] facilitating a robot with a sensing system pre-set in the community to collect behavior data of the target person through a picture or a sound;

[0012] collecting corresponding environment data by using a target sensor matched with a real-time position of the target person; the target sensor is a sensor pre-installed at a fixed position in the community.

[0013] Optionally, the encryption of the original data by the edge node corresponding to the community comprises:

[0014] receiving, by the edge node corresponding to the community, the original data sent by the sensor device;

[0015] preprocessing the original data by using the edge node to obtain corresponding preprocessed data; the preprocessing comprises data cleaning and data denoising;

[0016] encrypting the preprocessed data based on a preset encryption mode by using the edge node to obtain corresponding encrypted data; the preset encryption mode comprises a first encryption mode corresponding to a medical data type and a second encryption mode corresponding to a non-medical data type.

[0017] Optionally, before the encryption of the original data by the edge node corresponding to the community, the method further comprises:

[0018] risk scoring the original data based on a preset risk scoring formula by using the edge node to obtain a scoring result;

[0019] if the scoring result is greater than a preset scoring threshold, marking the original data as risk data and triggering an alarm operation for the risk data;

[0020] if the scoring result is not greater than the preset scoring threshold, marking the original data as safe data so as to encrypt the safe data.

[0021] Optionally, the storage of the encrypted data into a target blockchain comprises:

[0022] dividing the encrypted data into first data corresponding to the medical data type and second data corresponding to the non-medical data type;

[0023] storing the first data into the first blockchain and storing the second data into the second blockchain; the first blockchain is a main chain constructed based on a practical Byzantine fault tolerance algorithm, and the second blockchain is a side chain constructed based on a hash evidence technology.

[0024] Optionally, the client provides remote services to the target person based on the encrypted data in the target blockchain, including:

[0025] Obtaining, through a client, an access request for the target blockchain;

[0026] If the access request corresponds to the first blockchain, a biometric information recognition operation is performed on the current user corresponding to the client based on the access request, and after the biometric information recognition operation is successful, a key corresponding to the access request is issued to the client, so that the current user can access the target data in the first blockchain through the client using the key, and provide telemedicine services to the target person based on the target data;

[0027] If the access request corresponds to the second blockchain, a dynamic identity authentication operation is performed on the current user corresponding to the client based on the access request, and a session channel is established between the sensor device and the client after the dynamic identity authentication operation is passed, so that the current user can provide remote interactive services to the target person through the session channel.

[0028] Optionally, the method further includes:

[0029] Determining a current instruction representing metaverse social interaction in the encrypted data;

[0030] If the current instruction is an instruction for the first social interaction in the metaverse, the corresponding operation guidance mode is triggered;

[0031] The target person is guided to complete the operation tutorial of the operation guidance mode by a robot pre-set in the community, and the corresponding metaverse social service is provided to the target person by the robot.

[0032] In a second aspect, the present application provides a data management device for community elderly care, which is applied to a cloud data center and includes:

[0033] A data acquisition module is used to collect raw data related to target persons in the community through sensor equipment; the raw data includes physiological data, behavioral data and related environmental data of the target persons; the target persons are community residents whose ages meet the preset elderly determination criteria;

[0034] A data encryption transmission module, configured to encrypt the original data through an edge node corresponding to the community and obtain the encrypted data transmitted by the edge node;

[0035] The data storage module is configured to store the encrypted data to a target blockchain, so that a client provides remote service for the target person based on the encrypted data in the target blockchain; and the target blockchain includes a first blockchain corresponding to medical data and a second blockchain corresponding to non-medical data.

[0036] In a third aspect, the present application provides an electronic device, comprising:

[0037] a memory configured to store a computer program;

[0038] a processor configured to execute the computer program to implement the data management method for serving community pension as described above.

[0039] In a fourth aspect, the present application provides a computer readable storage medium configured to store a computer program, which is executed by a processor to implement the data management method for serving community pension as described above.

[0040] Therefore, in the present application, the cloud data center can collect the original data related to the target person in the community through the sensor device; the original data includes the physiological data, behavior data and related environmental data of the target person; then the original data is encrypted by the corresponding edge node of the community, and the encrypted data transmitted by the edge node is obtained; and the encrypted data is stored to a target blockchain, so that a client provides remote service for the target person based on the encrypted data in the target blockchain; and the target blockchain includes a first blockchain corresponding to medical data and a second blockchain corresponding to non-medical data. In this way, the present application can combine the physiological data, behavior data and environmental data related to the target person, improve the accuracy of data expression on the actual state of the target person; and the edge node can realize data encryption transmission, improve the data transmission efficiency and security; and the related data is stored by a double-chain architecture according to the medical data type, which can further improve the data processing efficiency and security. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on the provided drawings.

[0042] Figure 1 A data management method for serving community pension disclosed in the present application is shown in the flowchart;

[0043] Figure 2A specific data risk assessment process flowchart disclosed in the present application;

[0044] Figure 3 Another specific data risk assessment process flowchart disclosed in the present application;

[0045] Figure 4 A specific data storage flowchart disclosed in the present application;

[0046] Figure 5 A specific client authentication flowchart disclosed in the present application;

[0047] Figure 6 A specific data management method flowchart for community pension service disclosed in the present application;

[0048] Figure 7 A specific social service flowchart disclosed in the present application;

[0049] Figure 8 A specific meta-universe social service flowchart disclosed in the present application;

[0050] Figure 9 A specific data management device structure schematic diagram for community pension service disclosed in the present application;

[0051] Figure 10 A specific electronic device structure diagram disclosed in the present application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0053] Referring to Figure 1 The embodiments of the present application disclose a data management method for community pension service, applied to a cloud data center, comprising:

[0054] In step S11, raw data related to a target person in the community is collected by a sensor device; the raw data includes physiological data, behavior data and related environmental data of the target person; the target person is a community resident whose age meets a preset old person determination condition.

[0055] In the present application, in order to more accurately express the state of the target person, the physiological data, behavior data and environment data of the surrounding environment associated with the person can be collected. It can be understood that the target person related to community care for the elderly is usually a community resident whose age meets the preset old person determination condition. The relevant raw data of the target person can be collected by a sensor device.

[0056] In a specific embodiment, the collection of raw data of the target person in the community by the sensor device can include: collecting physiological data of the target person by a wearable device with a sensing system worn by the target person in the community; collecting behavior data of the target person by a robot with a sensing system pre-set in the community through pictures or sound; collecting corresponding environment data by a target sensor matched with the real-time position of the target person; the target sensor is a sensor pre-installed in a fixed position in the community. Specifically, for the physiological data of the target person, the sensing system of the wearable device is used to collect, such as heart rate, blood oxygen, etc.; for the behavior data of the target person, the video picture or sound voice can be used to collect, and the robot with a sensor can be used to track the position of the person to collect the corresponding behavior data in real time; further, for the environment data, the sensor pre-set in the environment can be used to collect the environment data, and the real-time position of the person is combined to collect the surrounding environment data by a plurality of target sensors matched with the position.

[0057] In step S12, the raw data is encrypted by the edge node corresponding to the community, and the encrypted data transmitted by the edge node is obtained.

[0058] In the present application, the raw data corresponding to the target person collected by the sensor through the above steps; then the sensor can transmit the collected raw data to the edge node corresponding to the current community, and the edge node realizes data transfer; specifically, the edge node can encrypt the raw data received from the sensor, and transmit the encrypted data to the cloud data center; that is, the data received by the cloud data center is the data encrypted by the edge node on the raw data collected by the sensor.

[0059] In a specific embodiment, the encryption of the original data by the edge node corresponding to the community can include: receiving, by the edge node corresponding to the community, the original data sent by the sensor device; preprocessing the original data by the edge node to obtain corresponding preprocessed data; the preprocessing includes data cleaning and data denoising; encrypting the preprocessed data based on a preset encryption mode by the edge node to obtain corresponding encrypted data; the preset encryption mode includes a first encryption mode corresponding to a medical data type and a second encryption mode corresponding to a non-medical data type. Specifically, after the edge node corresponding to the community receives the original data related to the target person from the sensor, the data can be preprocessed, the data can be cleaned and noise data can be removed; then a pre-set encryption mode can be used to encrypt different types of preprocessed data to obtain corresponding encrypted data; different encryption modes can be used for medical data types and non-medical data types, such as SM4 (symmetric encryption) + homomorphic encryption, AES-256 (a 256-key symmetric encryption algorithm), etc.

[0060] In another specific embodiment, before the original data is encrypted by the edge node corresponding to the community, the edge node can also be used to score the original data based on a preset risk scoring formula to obtain a score result; if the score result is greater than a preset score threshold, the original data is marked as risk data and an alarm operation for the risk data is triggered; if the score result is not greater than the preset score threshold, the original data is marked as safe data so that the safe data can be encrypted. Specifically, after the edge node receives the original data of the target person from the sensor, the original data can be preliminarily judged to determine whether the state of the target person is at risk; the original data can be scored based on a preset risk scoring formula to determine whether the state of the target person represented by the original data is at risk according to the relationship between the corresponding score result and the preset score threshold; each data can be calculated by a dynamic weighting algorithm, such as risk score = 0.4 * sigmoid (temperature-28) + 0.3 * relu (heart rate-100) + 0.3 * tanh (exercise-0.5). If there is a risk, the corresponding original data can be marked as risk data and the corresponding alarm operation can be triggered to remind the relevant personnel to check the condition of the target person in time; accordingly, if the state of the target person represented by the original data is not at risk, the corresponding original data can be marked as safe data, which can be encrypted and transmitted later. In this way, the waiting time before the target person at risk is rescued can be shortened as much as possible, and the reliability of community care for the elderly can be improved.

[0061] In specific embodiments, asFigure 2 For the processing flow of evaluating data risk, for the data received from the sensor, the data can be divided into emergency data (risk data) and regular data (safe data) according to the data risk; the emergency data can be processed by the edge node in real time, such as triggering an alarm; the regular data can be uploaded to the cloud, and the data center in the cloud can process the data asynchronously, and store the data in different blockchains according to different data types.

[0062] Further, as Figure 3 For another processing flow of evaluating data risk, the environment sensor, smart bracelet and robot can transmit the collected environment data (temperature / light) of the target person, physiological data (heart rate / oxygen) and behavior data (gait / voice) to the edge node; then the edge node can perform dynamic weighted calculation on the data, evaluate the relationship between the data risk score and the corresponding threshold, trigger the alarm of the corresponding cloud data center for the data with the risk score greater than the threshold, and store the data with the risk score not greater than the threshold regularly.

[0063] Step S13, store the encrypted data to the target blockchain, so that the client provides remote service for the target person based on the encrypted data in the target blockchain; the target blockchain includes a first blockchain corresponding to medical data type and a second blockchain corresponding to non-medical data type.

[0064] In the present application, the above steps can be used to encrypt the original data received from the sensor by the edge node corresponding to the community, the cloud data center can store the encrypted data transmitted by the edge node to the target blockchain, realize the safe storage of the data, and the client can provide remote service for the target person based on the data in the target blockchain. Further, the blockchains include blockchains corresponding to different data types respectively, realizing the classified storage of the data, which can improve the data processing efficiency and optimize the quality of the subsequent remote service.

[0065] In a specific embodiment, the storing the encrypted data to the target blockchain can include: dividing the encrypted data into first data corresponding to the medical data type and second data corresponding to the non-medical data type; storing the first data to the first blockchain and storing the second data to the second blockchain; the first blockchain is a main chain constructed based on a practical Byzantine fault tolerance algorithm, and the second blockchain is a side chain constructed based on a hash storage technology. Specifically, after the cloud data center receives the encrypted data from the edge node, the encrypted data can be stored to the target blockchain. First, the encrypted data is divided. Based on the medical data type, the first data corresponding to the medical data type and the second data corresponding to the non-medical data type can be obtained. Further, in order to ensure the sharing efficiency of the medical data and facilitate the subsequent provision of medical services based on the medical data, the first data can be stored to the first blockchain based on the practical Byzantine fault tolerance algorithm. Correspondingly, in order to ensure the non-tamperability of the data, the second data can be stored to the second blockchain based on the hash storage technology. In a specific embodiment, a special verification node group can be set for the medical data, and a dynamic timeout mechanism can be set to optimize the consensus delay. Further, as shown in FIG. 8, the data storage process is shown. The edge node can submit the encrypted data to the cloud data center, and the routing controller can store the data to the main chain or the medical side chain according to the data type. The main chain stores the data hash every 10 minutes to ensure that the data is non-tamperable. The side chain is a special channel for medical data, which optimizes the consensus mechanism and supports real-time sharing of emergency data. Figure 4

[0066] ​In another specific embodiment, the client provides remote services for the target person based on the encrypted data in the target blockchain, which can include: the client acquires an access request for the target blockchain; if the access request corresponds to the first blockchain, the client performs a biological information identification operation on the current user corresponding to the client based on the access request, and after the biological information identification operation passes, the client is issued a key corresponding to the access request, so that the current user accesses the target data in the first blockchain through the client using the key, and provides remote medical services for the target person based on the target data; if the access request corresponds to the second blockchain, the client performs a dynamic identity verification operation on the current user corresponding to the client based on the access request, and after the dynamic identity verification operation passes, a session channel is established between the sensor device and the client, so that the current user provides remote interactive services for the target person through the session channel. Specifically, the client can provide remote services for the target person based on the data in the blockchain, and the staff can issue an access request for the target blockchain through the client. Then determine whether the access request corresponds to the first blockchain or the second blockchain. It can be understood that the first blockchain corresponds to medical data, and the identity of the person providing remote medical services needs to be verified, so the biological information identification operation can be performed on the current user of the client to determine the identity, and then the key corresponding to the access request is issued to the client, so that the current user provides remote medical services for the target person through the client. Further, if the access request corresponds to the second blockchain, the dynamic identity verification of the current user of the client can be performed, such as verification code and other verification methods, and after verification, a session channel can be established between the sensor device and the client, so that the current user provides remote interactive services for the target person through the session channel. For example Figure 5 the authentication process of the client as shown in FIG. 8, the current user of the client has not been authenticated, and the authentication method can be determined according to the type of data to be accessed; medical data corresponds to biological identification, iris verification and other authentication methods, and after passing, the corresponding key can be issued; and for ordinary social login of non-medical data, dynamic authentication methods such as SMS verification and token can be used, and after passing, a session channel can be established.

[0067] In yet another specific embodiment, it can also include: determining the current instruction for performing metaverse socialization in the encrypted data; if the current instruction is the instruction for performing metaverse socialization for the first time, triggering the corresponding operation guidance mode; guiding the target person to complete the operation tutorial of the operation guidance mode through the robot pre-set in the community, and providing the target person with corresponding metaverse socialization services through the robot. Specifically, the target person can perform metaverse socialization through behavior or voice, etc., and the cloud data center can analyze the current instruction for performing metaverse socialization from the encrypted data; if it is the first time to perform metaverse socialization, the corresponding operation guidance mode can be triggered to help the target person adapt to the operation mode; here, the robot near the target person can be used to realize the interaction with the target person, guide the completion of the operation tutorial of the operation guidance mode, and the corresponding metaverse socialization services can be provided for the target person through the robot; for example, the target person interacts with the robot through voice, and the robot can feedback the instruction execution result through voice.

[0068] Therefore, the application can combine the physiological data, behavior data and environmental data related to the target person to improve the accuracy of the data in expressing the actual state of the target person; the edge node can realize encrypted data transmission to improve the data transmission efficiency and security; the edge node can also score the raw data collected by the sensor to timely trigger an alarm for the data with security risks and optimize the rescue efficiency; further, the relevant data can be stored in the blockchain through the double-chain architecture according to the medical data type, which can further improve the data processing efficiency and security.

[0069] As shown in Figure 6 The embodiment of the application discloses a data management method for community pension service, which involves a perception layer, an edge computing layer, a data layer and an application layer, and specifically includes:

[0070] For the perception layer, the data related to the old people can be collected through different sensor devices. The environmental data can be collected through environmental sensors, and the data transmission can be realized through Bluetooth-Wi-Fi communication. The physiological data can be collected through smart bracelets using PPG-ECG (photoplethysmography-electrocardiogram) technology, which can eliminate motion artifacts as much as possible and ensure the accuracy of the physiological data. The behavior data can be collected through robots in the form of video and voice. The robots can be equipped with lightweight models for recognizing various human behaviors.

[0071] The edge computing layer can clean the raw data collected by the perception layer and remove noise data. Then, the SSL / TLS (Secure Sockets Layer / Transport Layer Security, a protocol system) encryption protocol can be used to encrypt different types of data in layers. The encrypted data is then transmitted to the cloud data center. In specific embodiments, the edge node can automatically offload non-real-time tasks (such as historical data aggregation) to the cloud data center according to real-time load, to ensure that the processing delay of real-time data (such as fall warning) is within a small range.

[0072] Further, at the data layer, the cloud data center can perform main chain-side chain routing according to the data type. The PBFT (Practical Byzantine Fault Tolerance) side chain is used to store medical data to ensure efficient storage and sharing of medical data, and the Fabric (a blockchain architecture) main chain is used to store other data to ensure safe storage of data. In specific embodiments, a differential algorithm can be used to store data increments to reduce storage overhead.

[0073] Then, at the application layer, in combination with the medical data at the data layer, remote medical services can be provided to the relevant target personnel, or meta-universe social services can be provided. For the meta-universe social services, a simple and easy-to-use operation interface suitable for the elderly can be set for the elderly.

[0074] Further, as shown in the social service flow shown in Figure 7 , the old person can issue a voice command for meta-universe social interaction. If it is the first use, a guide mode can be started, and interaction can be performed through the buttons on the robot or through voice. If it is not the first use, the corresponding scene can be directly entered according to the command, and then interaction can be performed in combination with gesture control. During this process, operation delay data can be recorded, and the overall User Interface (UI) layout can be optimized. The interaction specifications involved are as follows:

[0075] protobuf

[0076] messageElderlyUI{

[0077] requireduint32button_size=1[default=50]; / / pixel unit

[0078] optionalboolvoice_guide=2[default=true];

[0079] repeatedstringgesture_map = 3; / / preset 5 basic gestures

[0080] The meta-universe interaction protocol defines a minimum operation unit of 50px, 5 basic gestures, and default voice guidance. Correspondingly, the scene can involve three-dimensional modeling of the offline activity center, and highlight identification can be added to key facilities such as seats and service counters. In addition, the social service can set up a remote assistance interface for relatives, and after a certain period of operation hesitation, the relative assistance interface can be triggered.

[0081] Correspondingly, as shown in the meta-universe social service flow shown in Figure 8 , the old person can interact with the robot through voice instructions (participate in chess and card activities) to perform meta-universe social services. The robot can send standardized requests (JSON, lightweight data exchange format) to the meta-universe platform based on the instructions issued by the old person. If the old person uses it for the first time, a guidance mode can be started, and operation guidance can be completed through voice or magnification UI. If it is not used for the first time, i.e., the old person is skilled in using it, the old person can directly enter the chess and card room. The meta-universe platform returns the operation log to the robot, so that the robot can voice feedback the execution result of the instructions to the old person.

[0082] As can be seen, the present application can combine the physiological data, behavior data and environmental data of the target person to improve the accuracy of the data in expressing the actual state of the target person. Moreover, the edge node can realize data preprocessing and encrypted transmission, improving data transmission efficiency and security, and providing reliable data support for upper-layer applications. By combining medical data types and using a double-chain architecture to store related data in a blockchain, the data processing efficiency and security can be further improved, and the time requirement for emergency treatment can be met.

[0083] As shown in Figure 9 , the present application discloses a data management device for community care for the elderly, which is applied to a cloud data center and includes:

[0084] A data acquisition module 11 is configured to acquire raw data related to a target person in a community through a sensor device; the raw data includes physiological data, behavior data, and related environmental data of the target person; the target person is a community resident who meets a predetermined old person determination condition;

[0085] A data encryption transmission module 12 is configured to encrypt the raw data through an edge node corresponding to the community, and obtain encrypted data transmitted by the edge node;

[0086] The data storage module 13 is used to store the encrypted data in a target blockchain so that the client can provide remote services to the target person based on the encrypted data in the target blockchain; the target blockchain includes a first blockchain corresponding to medical data types and a second blockchain corresponding to non-medical data types.

[0087] It can be seen that this application can combine the physiological data, behavioral data and environmental data related to the target person, thereby improving the accuracy of the data's expression of the target person's actual status; and, the edge node can realize data encryption transmission, improving data transmission efficiency and security; combining medical data types through a dual-chain architecture to store relevant data on the blockchain can further improve data processing efficiency and security.

[0088] In a specific embodiment, the data acquisition module 11 may include:

[0089] A physiological data collection unit, configured to collect physiological data of a target person in the community through a wearable device equipped with a sensor system worn by the target person;

[0090] A behavior data collection unit, configured to facilitate a robot equipped with a sensor system pre-installed in the community to collect the behavior data of the target person through images or sounds;

[0091] The environmental data collection unit is used to collect corresponding environmental data using a target sensor that matches the real-time position of the target person; the target sensor is a sensor pre-installed at a fixed position in the community.

[0092] In a specific embodiment, the data encryption transmission module 12 may include:

[0093] A raw data receiving unit, configured to receive the raw data sent by the sensor device through an edge node corresponding to the community;

[0094] A preprocessing unit, configured to preprocess the raw data using the edge node to obtain corresponding preprocessed data; the preprocessing includes data cleaning and data denoising;

[0095] A data encryption unit is used to use the edge node to encrypt the preprocessed data based on a preset encryption method to obtain corresponding encrypted data; the preset encryption method includes a first encryption method corresponding to the medical data type and a second encryption method corresponding to the non-medical data type.

[0096] In a specific embodiment, the device may further include:

[0097] The scoring module is configured to score the original data based on a preset risk scoring formula by using the edge node to obtain a scoring result.

[0098] The first marking module is configured to mark the original data as risk data when the scoring result is greater than a preset scoring threshold, and trigger an alarm operation for the risk data.

[0099] The second marking module is configured to mark the original data as safe data when the scoring result is not greater than the preset scoring threshold, so as to encrypt the safe data.

[0100] In a specific embodiment, the data storage module 13 can include:

[0101] The data division unit is configured to divide the encrypted data into first data corresponding to the medical data type and second data corresponding to the non-medical data type.

[0102] The data storage unit is configured to store the first data to the first blockchain and store the second data to the second blockchain; the first blockchain is a main chain constructed based on a practical Byzantine fault tolerance algorithm, and the second blockchain is a side chain constructed based on a hash evidence technology.

[0103] In a specific embodiment, the data storage module 13 can include:

[0104] The access request acquisition unit is configured to acquire an access request for the target blockchain through a client;

[0105] The key issuing unit is configured to, when the access request corresponds to the first blockchain, perform a biological information identification operation on a current user corresponding to the client based on the access request, and issue a key corresponding to the access request to the client after the biological information identification operation passes, so that the current user accesses target data in the first blockchain by using the key through the client, and provides remote medical services for the target person based on the target data;

[0106] The session establishment unit is configured to, when the access request corresponds to the second blockchain, perform a dynamic identity verification operation on a current user corresponding to the client based on the access request, and establish a session channel between the sensor device and the client after the dynamic identity verification operation passes, so that the current user provides remote interaction services for the target person through the session channel.

[0107] In a specific embodiment, the apparatus can further include:

[0108] An instruction determining module is configured to determine a current instruction for performing metaverse socialization in the encrypted data;

[0109] A guiding module is configured to trigger a corresponding operation guiding mode when the current instruction is an instruction for performing metaverse socialization for the first time.

[0110] A social service module is configured to guide the target person to complete an operation tutorial of the operation guiding mode through a robot pre-set in the community, and provide corresponding metaverse social service for the target person through the robot.

[0111] Further, the embodiment of the present application further discloses an electronic device, Figure 10 The electronic device 20 is shown in the structure diagram according to an exemplary embodiment, and the content in the diagram cannot be considered as any limitation on the use range of the present application.

[0112] Figure 10 The electronic device 20 provided by the embodiment of the present application is shown in the structure diagram. The electronic device 20 specifically can include at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25 and a communication bus 26. The memory 22 is used to store a computer program, the computer program is loaded and executed by the processor 21, so as to realize the related steps in the method disclosed in any of the preceding embodiments. In addition, the electronic device 20 in the embodiment can be an electronic computer.

[0113] In the embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol followed by the communication interface 24 can be any communication protocol applicable to the technical solution of the present application, which is not limited here; the input / output interface 25 is used to obtain external input data or output data to the outside, and the specific interface type can be selected according to the specific application needs, which is not limited here.

[0114] In addition, the memory 22 as the carrier of resource storage can be a read-only memory, a random access memory, a magnetic disk or an optical disk, etc., and the resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage mode can be temporary storage or permanent storage.

[0115] The operating system 221 is configured to manage and control each hardware device on the electronic device 20 and the computer program 222, which can be Windows Server, Netware, Unix, Linux, etc. The computer program 222 can further include computer programs capable of performing other specific work in addition to the computer program capable of performing the data management method for serving community pension disclosed by the electronic device 20 in any of the foregoing embodiments.

[0116] Further, the present application also discloses a computer readable storage medium for storing a computer program; wherein the computer program is executed by a processor to implement the data management method for serving community pension disclosed above. For the specific steps of the method, please refer to the corresponding content disclosed in the foregoing embodiments, which will not be repeated here.

[0117] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant part can be referred to the method part.

[0118] The skilled person can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly show the interchangeability of hardware and software, the composition and steps of each example have been described in the above description. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0119] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, software modules executed by a processor, or a combination of both. The software modules can be placed in random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art.

[0120] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0121] The above is a detailed introduction to the technical solution provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the ideas of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A data management method serving community elderly care, characterized in that: Applied to cloud data centers, including: Collecting raw data related to target persons in the community through sensor equipment; the raw data includes physiological data, behavioral data and related environmental data of the target persons; the target persons are community residents whose ages meet the preset criteria for determining elderly people; Encrypting the original data through an edge node corresponding to the community, and obtaining the encrypted data transmitted by the edge node; The encrypted data is stored in a target blockchain so that the client can provide remote services to the target person based on the encrypted data in the target blockchain; the target blockchain includes a first blockchain corresponding to the medical data type and a second blockchain corresponding to the non-medical data type.

2. The data management method for serving community elderly care according to claim 1, characterized in that: The raw data related to target persons in the community collected by sensor devices includes: collecting physiological data of target persons in the community through wearable devices equipped with sensor systems worn by target persons; A robot equipped with a sensor system pre-installed in the community collects behavioral data of the target person through images or sounds; Corresponding environmental data is collected using a target sensor that matches the real-time location of the target person; the target sensor is a sensor pre-installed at a fixed location in the community.

3. The data management method for serving community elderly care according to claim 1, characterized in that: The encrypting the original data by the edge node corresponding to the community includes: receiving, through an edge node corresponding to the community, the raw data sent by the sensor device; Preprocessing the raw data using the edge node to obtain corresponding preprocessed data; the preprocessing includes data cleaning and data denoising; The edge node is used to encrypt the preprocessed data based on a preset encryption method to obtain corresponding encrypted data; the preset encryption method includes a first encryption method corresponding to the medical data type and a second encryption method corresponding to the non-medical data type.

4. The data management method for serving community elderly care according to claim 1, characterized in that: Before encrypting the original data through the edge node corresponding to the community, the method further includes: Using the edge node, the original data is risk-scored based on a preset risk scoring formula to obtain a scoring result; If the scoring result is greater than a preset scoring threshold, the original data is marked as risky data, and an alarm operation for the risky data is triggered; If the scoring result is not greater than the preset scoring threshold, the original data is marked as safe data so as to encrypt the safe data.

5. The data management method for serving community elderly care according to claim 1 is characterized in that: Storing the encrypted data in the target blockchain includes: dividing the encrypted data into first data corresponding to the medical data type and second data corresponding to the non-medical data type; The first data is stored in the first blockchain, and the second data is stored in the second blockchain; the first blockchain is a main chain built based on the practical Byzantine fault tolerance algorithm, and the second blockchain is a side chain built based on hash evidence technology.

6. The data management method for serving community elderly care according to any one of claims 1 to 5, characterized in that: The client provides remote services to the target person based on the encrypted data in the target blockchain, including: Obtaining, through a client, an access request for the target blockchain; If the access request corresponds to the first blockchain, a biometric information recognition operation is performed on the current user corresponding to the client based on the access request, and after the biometric information recognition operation is successful, a key corresponding to the access request is issued to the client, so that the current user can access the target data in the first blockchain through the client using the key, and provide telemedicine services to the target person based on the target data; If the access request corresponds to the second blockchain, a dynamic identity authentication operation is performed on the current user corresponding to the client based on the access request, and a session channel is established between the sensor device and the client after the dynamic identity authentication operation is passed, so that the current user can provide remote interactive services to the target person through the session channel.

7. The data management method for serving community elderly care according to claim 1, characterized in that: Also includes: Determining a current instruction representing metaverse social interaction in the encrypted data; If the current instruction is an instruction for the first social interaction in the metaverse, the corresponding operation guidance mode is triggered; The target person is guided to complete the operation tutorial of the operation guidance mode by a robot pre-set in the community, and the corresponding metaverse social service is provided to the target person by the robot.

8. A data management device serving community elderly care, characterized in that: Applied to cloud data centers, including: A data acquisition module is used to collect raw data related to target persons in the community through sensor equipment; the raw data includes physiological data, behavioral data and related environmental data of the target persons; the target persons are community residents whose ages meet the preset elderly determination criteria; A data encryption transmission module, configured to encrypt the original data through an edge node corresponding to the community and obtain the encrypted data transmitted by the edge node; A data storage module is used to store the encrypted data in a target blockchain so that the client can provide remote services to the target person based on the encrypted data in the target blockchain; the target blockchain includes a first blockchain corresponding to medical data types and a second blockchain corresponding to non-medical data types.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the data management method for serving community elderly care as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Used to store a computer program, which, when executed by a processor, implements the data management method for serving community elderly care as described in any one of claims 1 to 7.

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