An intelligent management method for postpartum care data based on the Internet of Things

Abstract

The present invention discloses an intelligent management method for postpartum care data based on the Internet of Things, which includes obtaining the postpartum care data of patients uploaded by the first node in the blockchain, classifying the data according to the importance level of the data to match the corresponding encryption level; encrypting the postpartum care data according to different encryption levels, generating a medical electronic file for the patient's personal postpartum care based on the encrypted data, encrypting and storing the file version number of the medical electronic file by using the AES algorithm, and reading the storage location and index information; encrypting the storage location and index information by using the key of the first node, and storing the encrypted storage location, index information and medical electronic file in the data block of the blockchain for data sharing of the medical electronic file. The present invention can perform hierarchical encryption on postpartum care medical data of different importance levels, and store and share them through the blockchain, improving the security of data and the credibility of medical data sharing.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data management, and in particular to an intelligent management method for postpartum care data based on the Internet of Things. Background Art

[0002] With the popularization of electronic health records, the digitization of postpartum care data has brought the risk of data leakage. Hacker attacks, internal misoperations or system vulnerabilities may all threaten the privacy and security of patients. Especially in the context of the increasing growth of cloud computing and telemedicine services, how to ensure encryption and access control during data transmission and storage has become an urgent problem to be solved. Summary of the Invention

[0003] In order to solve at least one of the above-mentioned technical problems, the present invention provides an intelligent management method for postpartum care data based on the Internet of Things.

[0004] In a first aspect, the present invention provides an intelligent management method for postpartum care data based on the Internet of Things, and the method includes:

[0005] Obtain the postpartum care data of patients uploaded by the first node in the blockchain, classify the postpartum care data according to the importance of the data, and match the corresponding encryption level according to the classification result;

[0006] Encrypt the postpartum care data according to different encryption levels to generate encrypted data, including:

[0007] When it is determined that the encryption level is first-level encryption, use the hash encryption model to encrypt the postpartum care data:

[0008]

[0009] In the formula, X represents the encryption key, Hash(·) represents the hash function, a represents the random number seed of the ciphertext stream J, d and n respectively represent the length and quantity of the postpartum care data to be encrypted; ε1 and ε2 respectively represent the security level index of the storage end and the security level index of the client; s represents the importance of the data; e represents the base of the natural logarithm;

[0010] When it is determined that the encryption level is second-level encryption, use the RSA algorithm to encrypt the postpartum care data;

[0011] Generate a medical electronic file for the patient's personal postpartum care, use the AES algorithm to encrypt the file version number of the medical electronic file, store the encrypted medical electronic file, and read the storage location and index information;

[0012] Use the private key of the first node in the blockchain to encrypt the storage location and index information, and store the encrypted storage location, index information, and medical electronic files in the data block of the blockchain for data sharing of medical electronic files.

[0013] Preferably, the method further includes:

[0014] In response to the user's access request, identify and verify the user's identity information. When the verification is passed, respond to the user's data query request; query the user's medical electronic file according to the user's identity information;

[0015] Decrypt the user's medical electronic file and read the postpartum care data in the user's historical diagnosis and treatment process. The postpartum care data of the historical diagnosis and treatment includes the health status and corresponding care plans of each stage of the user's history;

[0016] Obtain the user's current health status information and generate a query keyword according to the current health status information;

[0017] Calculate the matching degree between the health status of each stage of the user's history and the current health status according to the query keyword. When the matching degree meets the preset condition, filter out the corresponding stage of the care plan and push it to the user.

[0018] Preferably, after obtaining the postpartum care data of the patient uploaded by the first node in the blockchain, it further includes:

[0019] According to the sensitivity index, timeliness index, and usage frequency index of the postpartum care data, calculate the importance degree of the postpartum care data, including:

[0020]

[0021] In the formula, f represents the importance degree of the data, x1, x2, and x3 respectively represent the sensitivity index, timeliness index, and usage frequency index, w1, w2, and w3 respectively represent the weight factors, k1 represents the offset constant of the sensitivity index, α represents the penalty factor of timeliness, and e represents the base of the natural logarithm.

[0022] Preferably, the storage - side security degree index and the client - side security degree index are respectively:

[0023]

[0024] In the formula, ε1 and ε2 respectively represent the storage - side security degree index and the client - side security degree index, c1 and c2 respectively represent the security attribute assignment levels of the storage side and the client side, respectively represent the reliability deviation level indexes of the storage side and the client side, and β represents the penalty factor of the security attribute assignment level.

[0025] In a second aspect, the present invention also provides an intelligent management system for postpartum care data based on the Internet of Things. The system includes:

[0026] A classification module, configured to obtain the postpartum care data of a patient uploaded by a first node in the blockchain, classify the postpartum care data according to the importance of the data, and match the corresponding encryption level according to the classification result;

[0027] An encryption module, configured to encrypt the postpartum care data according to different encryption levels to generate encrypted data, including:

[0028] A first-level encryption unit, configured to, when determining that the encryption level is first-level encryption, encrypt the postpartum care data using a hash encryption model:

[0029]

[0030] In the formula, X represents the encryption key, Hash(·) represents the hash function, a represents the random number seed of the ciphertext stream J, d and n respectively represent the length and quantity of the postpartum care data to be encrypted; ε1 and ε2 respectively represent the security level index of the storage end and the security level index of the client end; s represents the importance of the data; e represents the base of the natural logarithm;

[0031] A second-level encryption unit, configured to, when determining that the encryption level is second-level encryption, encrypt the postpartum care data using the RSA algorithm;

[0032] A storage module, configured to generate a medical electronic file for the patient's personal postpartum care according to the encrypted data, encrypt the file version number of the medical electronic file using the AES algorithm, store the encrypted medical electronic file, and read the storage location and index information;

[0033] A sharing module, configured to encrypt the storage location and index information using the key of the first node in the blockchain, and store the encrypted storage location, index information, and medical electronic file in the data block of the blockchain for data sharing of the medical electronic file.

[0034] Preferably, the system further includes a recommendation module, configured to:

[0035] Respond to a user's access request, identify and verify the user's identity information, and when the verification is passed, respond to the user's data query request; query the user's medical electronic file according to the user's identity information;

[0036] Decrypt the user's medical electronic file, and read the postpartum care data in the user's historical diagnosis and treatment process. The postpartum care data of the historical diagnosis and treatment includes the health status and corresponding care plans of the user at each historical stage;

[0037] Obtain the current health status information of the user, and generate a query keyword according to the current health status information;

[0038] Calculate the matching degree between the health status of each historical stage of the user and the current health status according to the query keyword. When the matching degree meets the preset conditions, filter out the corresponding stage of the nursing plan and push it to the user.

[0039] Preferably, the classification module is further configured to:

[0040] Calculate the importance degree of the postpartum nursing data according to the sensitivity index, timeliness index and usage frequency index of the postpartum nursing data, including:

[0041]

[0042] In the formula, f represents the importance degree of the data, x1, x2, and x3 respectively represent the sensitivity index, timeliness index and usage frequency index, w1, w2, and w3 respectively represent the weight factors, k1 represents the offset constant of the sensitivity index, α represents the penalty factor of timeliness, and e represents the base of the natural logarithm.

[0043] Preferably, the storage - side security degree index and the client - side security degree index are respectively:

[0044]

[0045] In the formula, ε1 and ε2 respectively represent the storage - side security degree index and the client - side security degree index, C1 and c2 respectively represent the security attribute assignment levels of the storage side and the client side, respectively represent the reliability deviation level indexes of the storage side and the client side, and β represents the penalty factor of the security attribute assignment level.

[0046] In a third aspect, the present invention further provides an electronic device, including: a processor and a memory. The memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes the method according to the first aspect and any one of its possible implementation manners as described above.

[0047] In a fourth aspect, the present invention further provides a computer - readable storage medium. The computer - readable storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by the processor of the electronic device, the processor is caused to execute the method according to the first aspect and any one of its possible implementation manners as described above.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0049] 1) The present invention first obtains the postpartum care data of patients uploaded by the first node in the blockchain, classifies the postpartum care data according to the importance of the data, and matches the corresponding encryption level according to the classification result; encrypts the postpartum care data according to different encryption levels to generate encrypted data, including when it is determined that the encryption level is first-level encryption, using a hash encryption model to encrypt the postpartum care data, and when it is determined that the encryption level is second-level encryption, using the RSA algorithm to encrypt the postpartum care data. Different encryption methods are adopted for data of different importance levels, rationally allocating encryption resources and avoiding using the highest-level encryption for all data, which helps to simplify the key management process. When constructing the hash encryption model for first-level encryption, the influences of the data length, quantity, storage-end security degree index, and client security degree index are considered, thereby improving the encryption strength of the encryption algorithm and providing higher security for highly sensitive important data.

[0050] 2) The present invention generates a medical electronic file for the patient's personal postpartum care based on the encrypted data, encrypts the file version number of the medical electronic file using the AES algorithm for storing the encrypted medical electronic file, reads the storage location and index information; encrypts the storage location and index information using the key of the first node in the blockchain, and stores the encrypted storage location, index information, and medical electronic file in the data block of the blockchain for data sharing of the medical electronic file. By encrypting the file version number of the medical electronic file, the security of data transmission and storage is enhanced. Encrypted storage in the form of a medical electronic file is equivalent to systematically organizing fragmented multi-source data, facilitating data storage management and subsequent data sharing processes.

[0051] 3) When the user accesses data, the present invention first identifies and verifies the user's identity information, and only responds to the user's data query request when the verification is passed. Through this access permission management method, the risk of data leakage can be reduced. When the user calls historical medical data, the current health status information of the user is obtained, and query keywords are generated according to the current health status information; the matching degree between the health status of each historical stage of the user and the current health status is calculated according to the query keywords. When the matching degree meets the preset conditions, the corresponding stage of the care plan is screened out and pushed to the user. In this way, the user can refer to the historical diagnosis and treatment care data to find a suitable care plan for the current health problem by himself, avoiding the overuse of medical resources and improving the energy efficiency of medical data management.

[0052] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the following will describe the drawings required for use in the embodiments of the present invention or the background art.

[0054] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification. These drawings show embodiments consistent with the present disclosure and, together with the specification, are used to illustrate the technical solutions of the present disclosure.

[0055] Figure 1 It is a schematic flowchart of an intelligent management method for postpartum care data based on the Internet of Things provided by an embodiment of the present invention;

[0056] Figure 2 It is a schematic structural diagram of an intelligent management system for postpartum care data based on the Internet of Things provided by an embodiment of the present invention;

[0057] Figure 3 It is a schematic structural diagram of another intelligent management system for postpartum care data based on the Internet of Things provided by an embodiment of the present invention. Detailed implementation manners

[0058] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0059] The terms "first", "second", etc. in the specification and claims of the present invention and the above accompanying drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0060] The term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein represents any one of a plurality or any combination of at least two of a plurality. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set composed of A, B, and C.

[0061] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the invention. The phrase occurring in various places in the specification is not necessarily referring to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0062] In addition, for a better illustration of the present invention, numerous specific details are given in the following detailed description. Those skilled in the art should understand that the present invention can still be implemented without some of these specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art are not described in detail so as to highlight the gist of the present invention.

[0063] Currently, there is a relatively high risk of data leakage in the postpartum care data of user consultations, and the data sharing mechanism is not perfect, resulting in the medical data management efficiency falling short of expectations. For this reason, the present invention provides an intelligent management method for postpartum care data based on the Internet of Things, which can classify and encrypt user postpartum care data according to the importance of the data, and store it in the blockchain as a medical electronic file, achieving the security and reliability of data sharing, improving the utilization rate of medical resources, and increasing the management efficiency of medical data.

[0064] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of an intelligent management method for postpartum care data based on the Internet of Things provided by an embodiment of the present invention. As Figure 1 shown, the method includes the following steps:

[0065] S10. Obtain the postpartum care data of a patient uploaded by a first node in the blockchain, classify the postpartum care data according to the importance of the data, and match the corresponding encryption level according to the classification result.

[0066] In one embodiment, after obtaining the postpartum care data of a patient uploaded by a first node in the blockchain, it further includes:

[0067] Calculate the importance of the postpartum care data according to the sensitivity index, timeliness index, and usage frequency index of the postpartum care data, including:

[0068]

[0069] In the formula, f represents the importance of the data, x1, x2, and x3 respectively represent the sensitivity index, timeliness index, and usage frequency index, w1, w2, and w3 respectively represent the weight factors, k1 represents the offset constant of the sensitivity index, α represents the penalty factor of timeliness, and e represents the base of the natural logarithm.

[0070] In this embodiment, the sensitivity indicators generally include sensitive data item indicators, semantic intensity indicators, text strength indicators, and structural feature indicators, and these indicators together determine the magnitude of sensitivity. The timeliness indicator is used to measure the freshness of the data and its relevance at the current time point. It can be the age of the data (such as the number of days since generation), and the newer the data, the more important it may be. The value range and conversion method need to be defined according to the specific scenario. The usage frequency indicator represents the frequency of data access or use, which can be obtained through means such as log analysis. The more frequently used the data, the higher the usage value of the medical data usually is. Preferably, in this embodiment, the analytic hierarchy process is used to determine the weight factors w1, w2, and w3 of the sensitivity indicator, timeliness indicator, and usage frequency indicator of the postpartum care data.

[0071] Specifically, the sensitivity indicator can generally be determined in the following ways:

[0072] 1) Sensitive data item indicator:

[0073] Keyword matching: Search for a pre-defined sensitive vocabulary list. For example, data such as personal identity information (name, ID number, phone number, etc.), health status, diagnosis and treatment, and nursing history can be set as sensitive data items.

[0074] Entity recognition: Use natural language processing technology to automatically detect sensitive data items in the text.

[0075] 2) Semantic intensity indicator:

[0076] Sentiment analysis: Evaluate the intensity of the sentiment expressed in the text. The intensity of positive or negative emotions may affect the sensitivity determination, especially extreme emotion expressions may indicate sensitive content.

[0077] Context relevance: Consider the meaning of words in a specific context. The sensitivity of the same word may be different in different contexts, and it is necessary to understand the overall context of the text to accurately evaluate.

[0078] Metaphor and implication recognition: Identify sensitive information that may be conveyed in the text through metaphors, similes, implications, etc. This part often requires advanced semantic understanding capabilities.

[0079] 3) Text strength indicator:

[0080] Degree of emphasis: Analyze whether words with an intensified tone (such as "absolutely", "must") or symbols such as exclamation marks are used in the text. Such expressions may enhance the sensitivity of the information.

[0081] Propagation potential: Evaluate the spreadability of the text, such as sharing appeals, requests for forwarding, etc. Texts with high propagation potential may require a higher sensitivity score because they may rapidly expand the scope of influence.

[0082] 4) Structural feature indicators:

[0083] Text length: Long texts may contain more information, but not necessarily be more sensitive; short texts such as tweets may be highly sensitive due to their conciseness and power.

[0084] Format and structure: Specific text formats (such as emails, document templates) may imply the formality or sensitivity of the information.

[0085] In one embodiment, the storage - end security level index and the client - end security level index are respectively:

[0086]

[0087] In the formula, ε1 and ε2 respectively represent the storage - end security level index and the client - end security level index, c1 and c2 respectively represent the security attribute assignment levels of the storage end and the client end, respectively represent the reliability deviation level indices of the storage end and the client end, and β represents the penalty factor of the security attribute assignment level.

[0088] In this embodiment, the security attribute assignment level is a numerical value used to measure the security level of data or systems. It can help determine the sensitivity of data or systems, thereby formulating protection strategies. Specifically, for the two systems of the storage end and the client end, when calculating the size of the security attribute assignment level, the client can be marked based on the user role. For example, different security levels can be assigned according to the user's role (such as administrator, ordinary user, etc.). When the administrator is the user end, the security attribute assignment level is of a higher security level, while ordinary users are marked as having a lower security level. The storage end is mainly marked according to the data access frequency. For example, if a certain storage - end server is frequently accessed, it indicates that the security attribute assignment level of this storage end is of a lower security level.

[0089] The reliability deviation level index is usually associated with the system violation level. If a violation may lead to a large amount of data loss, the reliability deviation level index will be very high. On the contrary, if a violation only causes some minor problems, the reliability deviation level index will be relatively low. When calculating the value, the following deviation metrics can be used, for example: failure rate deviation, which represents the difference between the actual failure rate and the expected failure rate; MTTF deviation, which represents the gap between the actual mean time to failure and the designed or expected MTTF; availability deviation, which represents the proportional difference between the actual system available time and the expected available time. Further, according to the severity and impact degree of the deviation metrics, the deviations are divided into different levels, so as to obtain reliability deviation level indices of different magnitudes.

[0090] The penalty factor of the security attribute assignment level is used to characterize the penalty score for some behaviors that violate security rules. If a system does not adopt sufficient security measures, its security level will be reduced. On the contrary, if a system adopts appropriate security measures, its security level will be increased. In this embodiment, when constructing the penalty factor β, exponential or logarithmic constants can be considered, for example, taking lg5. Assuming that a system violates 2 security rules, its security level will be reduced by lg3.

[0091] Therefore, this embodiment takes into account the security factors of both the storage side and the client side, combines the reliability deviation level index, the security attribute assignment level and its penalty factor, and can quickly and effectively calculate the security level index of the storage side and the client side for use in the encryption process of the subsequent hash encryption model, thereby increasing the strength of the encryption algorithm.

[0092] S20. Encrypt the postpartum care data according to different encryption levels to generate encrypted data, including:

[0093] S201. When it is determined that the encryption level is first-level encryption, use the hash encryption model to encrypt the postpartum care data:

[0094]

[0095] In the formula, X represents the encryption key, Hash(·) represents the hash function, a represents the random number seed of the ciphertext stream J, d and n respectively represent the length and quantity of the postpartum care data to be encrypted; ε1 and ε2 respectively represent the security level index of the storage side and the security level index of the client side; s represents the importance degree of the data; e represents the base of the natural logarithm;

[0096] S202. When it is determined that the encryption level is second-level encryption, use the RSA algorithm to encrypt the postpartum care data.

[0097] In this embodiment, two encryption levels are matched mainly according to the importance of data. An importance threshold can be defined. If the importance of the data calculated in the previous step is greater than the threshold, such as identity information, medical diagnosis, nursing plan, financial information, etc. in postpartum care data, a first-level encryption algorithm is matched for this information, that is, the above-mentioned hash encryption model is used. If the importance of the data is less than or equal to the threshold, it means that the data importance is relatively low, such as general medical knowledge information, basic operation data of hospitals or health centers (number of beds, number of patients, number of equipment in operation), etc. Then, a second-level encryption algorithm is used for this part of the data, that is, the RSA algorithm is used. S30. Generate a medical electronic file for the patient's personal postpartum care based on the encrypted data, and use the AES algorithm to encrypt the file version number of the medical electronic file to store the encrypted medical electronic file and read the storage location and index information.

[0098] In the above steps, classification and hierarchical encryption are performed for different data types. For the convenience of data storage management and subsequent access processes, in this embodiment, based on the encrypted data, several medical electronic files are integrated according to the identity information of different patients and stored in the form of electronic files. After obtaining the electronic file, to further ensure the security of uploading to the blockchain, the symmetric encryption algorithm AES is used to encrypt the file version number of the medical electronic file. It can be understood that the file version number is usually a unique digital sequence, which can be randomly generated by a random number generator or encoded according to the identity information of different patients (such as ID number). When encrypting the version number, AES-128 is preferably used, which can be a preferred way to balance efficiency and security performance for non-critical data. After the version number is encrypted, the encrypted medical electronic file is stored and the storage location and index information are read.

[0099] It should be noted that the index information refers to the key identifiers and descriptive metadata used to quickly locate and retrieve postpartum care-related records. These index information are crucial for ensuring the accessibility and usability of data, and can specifically include but are not limited to the patient's basic identity information, delivery information, postpartum health assessment index, core nursing measures, etc.

[0100] S40. Use the key of the first node in the blockchain to encrypt the storage location and index information, and store the encrypted storage location, index information, and medical electronic file in the data block of the blockchain for data sharing of the medical electronic file.

[0101] Therefore, the intelligent management method for postpartum care data provided in this embodiment adopts different encryption methods for data of different importance levels, reasonably allocates encryption resources, avoids using the highest-level encryption for all data, and helps to simplify the key management process. When constructing the hash encryption model for first-level encryption, the influences of data length, quantity, storage-side security level index, and client-side security level index are considered, thereby enhancing the encryption strength of the encryption algorithm and providing higher security for highly sensitive important data. In addition, in this embodiment, the security of data transmission and storage is enhanced by encrypting the file version number of the medical electronic file. Encrypted storage is performed in the form of a medical electronic file, thereby systematically organizing fragmented multi-source postpartum care data, facilitating data storage management and subsequent data sharing processes.

[0102] In one embodiment, the method further includes:

[0103] 1) In response to a user's access request, identify and verify the user's identity information. When the verification is passed, respond to the user's data query request; query the user's medical electronic file according to the user's identity information.

[0104] When sharing data, it is first necessary to verify the user's identity to determine whether the user has access rights. Specifically, digital certificates and public-key encryption technologies can be used. Each user has a unique public-key and private-key pair in the blockchain system. The public key serves as the identifier of the user's identity and can be publicly shared, while the private key is kept by the user himself / herself for signing transactions and verifying identity. It is also possible to register a decentralized identity and create a credential containing one's own identity attributes. In addition, a smart contract can be invoked to write logic to automatically verify the user's identity. When a user requests access to data, the smart contract checks whether the credentials provided by the user comply with the preset access rules, and only requests that meet the conditions will be approved.

[0105] 2) Decrypt the user's medical electronic file and read the postpartum care data of the user's historical diagnosis and treatment process. The postpartum care data of the historical diagnosis and treatment includes the health status of the user at each historical stage and the corresponding care plan;

[0106] It can be understood that this embodiment is mainly to provide relevant nursing information from historical nursing data. If the user's current health status is poor, the user can match the health status by referring to the historical nursing data, understand the cause of the disease, and thus determine the nursing method to be adopted by referring to the historical nursing plan. In this way, the frequency of going to the hospital on-site can be reduced or avoided, and the ineffective occupation of medical resources can be avoided. Therefore, the postpartum nursing data of historical diagnosis and treatment in this embodiment mainly includes the health status of the user at each historical stage and the corresponding nursing plan. In other scenarios, if the user's access purpose is different, for example, for tracing the nursing data, then the historical nursing data will provide other relevant operation data. For example, if the user wants to search for the expenses, drug information, and nursing plan during the historical nursing process, and analyze whether there are any abnormalities in the previous expenses or whether the nursing plan is inappropriate, etc., the user can also access it.

[0107] 3) Obtain the user's current health status information and generate a query keyword based on the current health status information;

[0108] 4) Calculate the matching degree between the health status of each historical stage of the user and the current health status according to the query keyword. When the matching degree meets the preset condition, filter out the corresponding nursing plan and push it to the user.

[0109] The query keyword is mainly used to represent the user's health status, which can be disease symptoms related to postpartum, or information such as the cause of the disease and the onset time. After generating the query keyword, it is mainly compared with the health status of each historical stage of the user to find similar situations. When the matching degree meets the preset condition, the nursing plan under the corresponding historical health status can be found. In this way, the user can refer to this nursing plan for nursing treatment without re-diagnosis and formulating a plan, saving medical costs and resources.

[0110] In summary, when the user accesses data in this embodiment, the identity information of the user will be first identified and verified, and the data query request of the user will be responded only when the verification is passed. Through this access permission management method, the risk of data leakage can be reduced. When the user calls historical medical data, the current health status information of the user will be obtained, and a query keyword will be generated based on the current health status information; the matching degree between the health status of each historical stage of the user and the current health status will be calculated according to the query keyword. When the matching degree meets the preset condition, the corresponding nursing plan will be filtered out and pushed to the user. In this way, the user can refer to the historical diagnosis and treatment nursing data to find a suitable nursing plan for the current health problem by himself, avoid the over-occupation of medical resources, and greatly improve the energy efficiency of medical data management.

[0111] See Figure 2 , in one embodiment, the present invention also provides an intelligent management system for postpartum nursing data based on the Internet of Things. The system includes:

[0112] The classification module 100 is used to obtain the postpartum care data of patients uploaded by the first node in the blockchain, classify the postpartum care data according to the importance of the data, and match the corresponding encryption level according to the classification result;

[0113] The encryption module 200 is used to encrypt the postpartum care data according to different encryption levels to generate encrypted data, including:

[0114] The first-level encryption unit 201 is used to encrypt the postpartum care data by using the hash encryption model when it is determined that the encryption level is first-level encryption:

[0115]

[0116] In the formula, X represents the encryption key, Hash(·) represents the hash function, a represents the random number seed of the ciphertext stream J, d and n respectively represent the length and quantity of the postpartum care data to be encrypted; ε1 and ε2 respectively represent the security level index of the storage end and the security level index of the client; s represents the importance of the data; e represents the base of the natural logarithm;

[0117] The second-level encryption unit 202 is used to encrypt the postpartum care data by using the RSA algorithm when it is determined that the encryption level is second-level encryption;

[0118] The storage module 300 is used to generate a medical electronic file for the patient's personal postpartum care according to the encrypted data, encrypt the file version number of the medical electronic file by using the AES algorithm, store the encrypted medical electronic file, and read the storage location and index information;

[0119] The sharing module 400 is used to encrypt the storage location and index information by using the key of the first node in the blockchain, and store the encrypted storage location, index information and medical electronic file in the data block of the blockchain for data sharing of the medical electronic file.

[0120] See Figure 3 , in one embodiment, the system further includes a recommendation module 500, which is used for:

[0121] Respond to the user's access request, identify and verify the user's identity information, and when the verification is passed, respond to the user's data query request; query the user's medical electronic file according to the user's identity information;

[0122] Decrypt the user's medical electronic file and read the postpartum care data in the user's historical diagnosis and treatment process, where the postpartum care data of the historical diagnosis and treatment includes the health status and corresponding care plans at each stage of the user's history;

[0123] Obtain the current health status information of the user, and generate a query keyword according to the current health status information;

[0124] Calculate the matching degree between the health status of each historical stage of the user and the current health status according to the query keyword. When the matching degree meets the preset conditions, filter out the corresponding stage of the nursing plan and push it to the user.

[0125] In one embodiment, the classification module 100 is further configured to:

[0126] Calculate the importance degree of the postpartum nursing data according to the sensitivity index, timeliness index and usage frequency index of the postpartum nursing data, including:

[0127]

[0128] In the formula, f represents the importance degree of the data, x1, x2, and x3 respectively represent the sensitivity index, timeliness index and usage frequency index, w1, w2, and w3 respectively represent the weight factors, k1 represents the offset constant of the sensitivity index, α represents the penalty factor of timeliness, and e represents the base of the natural logarithm.

[0129] In one embodiment, the storage - side security degree index and the client - side security degree index are respectively:

[0130]

[0131]

[0132] In the formula, ε1 and ε2 respectively represent the storage - side security degree index and the client - side security degree index, c1 and c2 respectively represent the security attribute assignment levels of the storage side and the client side, respectively represent the reliability deviation level indexes of the storage side and the client side, and β represents the penalty factor of the security attribute assignment level.

[0133] It can be understood that the functions or modules included in the system provided in this embodiment can be used to execute the methods described in the above - mentioned method embodiments. Its specific implementation can refer to the description of the above - mentioned method embodiments. For the sake of brevity, it will not be elaborated here.

[0134] The present invention also provides an electronic device, including: a processor and a memory. The memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes the method in any of the above - mentioned possible implementation manners.

[0135] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions, and when the program instructions are executed by a processor of an electronic device, the processor is caused to execute the method according to any one of the above possible implementation manners.

[0136] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0137] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein. Those skilled in the art can also clearly understand that each embodiment of the present invention has different focuses. For the convenience and brevity of description, the same or similar parts may not be elaborated in different embodiments. Therefore, the parts not described or not elaborated in a certain embodiment can be referred to the descriptions of other embodiments.

[0138] In several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings, direct couplings, or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in an electrical, mechanical, or other form.

[0139] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a digital versatile disc (DVD)), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0141] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware with a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The aforementioned storage medium includes various media that can store program codes, such as read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

Claims

1. A postpartum care data intelligent management method based on the Internet of Things, characterized in that: The method comprises: Obtain the postpartum care data of the patient uploaded by the first node in the blockchain, classify the postpartum care data according to the importance of the data, and match the corresponding encryption level according to the classification results; After obtaining the postpartum care data of the patient uploaded by the first node in the blockchain, the method further includes: The importance of postpartum care data is calculated based on the sensitivity index, timeliness index, and frequency of use index of postpartum care data, including: In the formula, f represents the importance of data, x1, x2, x3 represent the sensitivity index, timeliness index and frequency of use index respectively, w1, w2, w3 represent the weight factors respectively, k1 represents the offset constant of the sensitivity index, α represents the penalty factor of timeliness, and e represents the base of the natural logarithm; The postpartum care data is encrypted according to different encryption levels to generate encrypted data, including: When the encryption level is determined to be level 1, the hash encryption model is used to encrypt the postpartum care data: In the formula, X represents the encryption key, Hash(·) represents the hash function, a represents the random number seed of the ciphertext stream J, d and n represent the length and quantity of the postpartum care data to be encrypted, respectively; ε1 and ε2 represent the security index of the storage end and the security index of the client end, respectively; s represents the importance of the data; e represents the base of the natural logarithm; The storage end security index and the client end security index are respectively: In the formula, ε1 and ε2 represent the security index of the storage end and the client end respectively, c1 and c2 represent the security attribute allocation level of the storage end and the client end respectively. They represent the reliability deviation level index of the storage end and the client end respectively, and β represents the penalty factor of the security attribute allocation level; When the encryption level is determined to be level 2 encryption, the RSA algorithm is used to encrypt the postpartum care data; Generate a medical electronic file of the patient's personal postpartum care based on the encrypted data, encrypt the file version number of the medical electronic file using the AES algorithm, store the encrypted medical electronic file, and read the storage location and index information; The storage location and index information are encrypted using the key of the first node in the blockchain, and the encrypted storage location, index information and medical electronic files are stored in the data block of the blockchain to share the data of the medical electronic files.

2. The method for intelligent management of postpartum care data based on the Internet of Things according to claim 1, characterized in that: The method further comprises: Respond to the user's access request, identify the user's identity information and verify it. When the verification is successful, respond to the user's data query request; query the user's medical electronic file based on the user's identity information; Decrypt the user's electronic medical file and read the postpartum care data of the user's historical diagnosis and treatment process from it, wherein the postpartum care data of the historical diagnosis and treatment includes the health status of the user at each stage of history and the corresponding care plan; Obtain the user's current health status information and generate query keywords based on the current health status information; The matching degree between the user's historical health status at each stage and the current health status is calculated based on the query keywords. When the matching degree meets the preset conditions, the care plan for the corresponding stage is selected and pushed to the user.

3. An intelligent management system for postpartum care data based on the Internet of Things, characterized in that: The system comprises: A classification module is used to obtain the postpartum care data of the patient uploaded by the first node in the blockchain, classify the postpartum care data according to the importance of the data, and match the corresponding encryption level according to the classification results; The classification module is further used for: The importance of postpartum care data is calculated based on the sensitivity index, timeliness index, and frequency of use index of postpartum care data, including: In the formula, f represents the importance of data, x1, x2, x3 represent the sensitivity index, timeliness index and frequency of use index respectively, w1, w2, w3 represent the weight factors respectively, k1 represents the offset constant of the sensitivity index, α represents the penalty factor of timeliness, and e represents the base of the natural logarithm; The encryption module is used to encrypt the postpartum care data according to different encryption levels and generate encrypted data, including: The first-level encryption unit is used to encrypt the postpartum care data using a hash encryption model when the encryption level is determined to be first-level encryption: In the formula, X represents the encryption key, Hash(·) represents the hash function, a represents the random number seed of the ciphertext stream J, d and n represent the length and quantity of the postpartum care data to be encrypted, respectively; ε1 and ε2 represent the security index of the storage end and the security index of the client end, respectively; s represents the importance of the data; e represents the base of the natural logarithm; The storage end security index and the client end security index are respectively: In the formula, ε1 and ε2 represent the security index of the storage end and the client end respectively, c1 and c2 represent the security attribute allocation level of the storage end and the client end respectively. They represent the reliability deviation level index of the storage end and the client end respectively, and β represents the penalty factor of the security attribute allocation level; A secondary encryption unit, used for encrypting the postpartum care data using an RSA algorithm when the encryption level is determined to be secondary encryption; A storage module, used to generate a medical electronic file of the patient's personal postpartum care based on the encrypted data, encrypt the file version number of the medical electronic file using the AES algorithm, store the encrypted medical electronic file, and read the storage location and index information; The sharing module is used to encrypt the storage location and index information using the key of the first node in the blockchain, and store the encrypted storage location, index information and medical electronic files in the data block of the blockchain to share the data of the medical electronic files.

4. The postpartum care data intelligent management system based on the Internet of Things according to claim 3 is characterized in that: The system further comprises a recommendation module, for: Respond to the user's access request, identify the user's identity information and verify it. When the verification is successful, respond to the user's data query request; query the user's medical electronic file based on the user's identity information; Decrypt the user's electronic medical file and read the postpartum care data of the user's historical diagnosis and treatment process from it, wherein the postpartum care data of the historical diagnosis and treatment includes the health status of the user at each stage of history and the corresponding care plan; Obtain the user's current health status information and generate query keywords based on the current health status information; The matching degree between the user's historical health status at each stage and the current health status is calculated based on the query keywords. When the matching degree meets the preset conditions, the care plan for the corresponding stage is selected and pushed to the user.

5. An electronic device, characterized in that: include: A processor and a memory, the memory being used to store computer program codes, the computer program codes comprising computer instructions, and when the processor executes the computer instructions, the electronic device executes the intelligent management method for postpartum care data based on the Internet of Things as described in any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the intelligent management method for postpartum care data based on the Internet of Things as described in any one of claims 1 to 2.

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