Health data conversion method and system for home health Internet of Things devices

Abstract

The present invention discloses a health data conversion method and system for home health IoT devices, the method comprising: constructing symptom conversion rules; obtaining health-related data; querying whether there are symptom conversion rules; extracting symptom conversion rules corresponding to health device IDs, judging whether data content meets the judgment conditions; obtaining the latest health-related data, if the current health device ID meets the next device ID, and the current health-related data acquisition time meets the duration threshold, when the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, setting the condition satisfaction flag and increasing the number of condition satisfaction times; when the number of condition satisfaction times is greater than the condition satisfaction times threshold in the symptom conversion rule, the current symptom conversion rule and the health-related data of each health device are used as health data, and are encoded together with the symptom name and reported. The present invention realizes the conversion of smart home device data into health data, and associates the collected device data with health data.

Description

Technical Field

[0001] The present invention relates to the field of home health technology, and in particular to a health data conversion method and system for home health Internet of Things devices. Background Art

[0002] With the continuous development of science and technology, smart home devices have gradually entered people's daily lives, such as smart air purifiers, smart bracelets and smart sleep pillows. These devices can not only improve the convenience of life, but also generate a large amount of data. If these data are deeply mined, cleaned and analyzed, they can be used to establish a mapping relationship between smart home device data and user health data, which is of great significance for early screening of diseases and analysis of human health status. However, existing technologies face the following major problems when processing these data:

[0003] 1. How to convert IoT appliance data into health data:

[0004] The data generated by smart home devices cannot be directly interpreted as health data. Further processing is required between the two. That is, the device data collected by the device is processed according to certain rules into health data that can be understood and further identified. The existing solution relies on a large pre-established database to obtain health data through query by pre-setting the keyword mapping relationship between data. This method is inefficient on the one hand, and relies on the detail and accuracy of the database on the other hand, and is not suitable for the acquisition and processing of large-scale data.

[0005] 2. Huge data volume and differences in communication protocols:

[0006] The amount of data generated by smart home devices is very large, and these devices usually use different communication protocols. Directly transmitting all device data to the cloud platform for processing and analysis will not only take up a lot of network bandwidth, but also lead to low transmission efficiency. Therefore, it is necessary to filter and clean the data before data transmission, and only transmit health-related data.

[0007] 3. Real-time requirements for health data:

[0008] Health data has high requirements for real-time performance. If it cannot be processed and transmitted in time, it may affect the accuracy and timeliness of health monitoring. Therefore, it is necessary to process the data at the edge where it is generated to ensure the real-time performance of the data. Summary of the invention

[0009] In view of the technical problems existing in the above-mentioned prior art, the present invention proposes a health data conversion method and system for home health IoT devices. The method implements the screening of smart home device data on the edge device, filters out non-health-related data, and only transmits health-related data.

[0010] In order to achieve the above-mentioned invention object, the technical solution provided by the present invention includes:

[0011] The method for converting health data for home health IoT devices comprises the following steps:

[0012] S1. Construct symptom conversion rules and store them as a symptom conversion database; the symptom conversion rules include: current device ID, data content judgment condition, next device ID, duration threshold, repetition number flag, condition satisfaction flag, condition satisfaction number of times and condition satisfaction number threshold;

[0013] S2, obtaining the latest health-related data uploaded by a single health device, wherein the health-related data includes a health device ID and data content; querying whether there is a symptom conversion rule in the symptom conversion database according to the health device ID, and if so, executing the next step;

[0014] S3, extracting the symptom conversion rule corresponding to the health device ID, determining whether the data content meets the determination condition, and if so, recording the health-related data of the current health device, setting the condition satisfaction flag and incrementing the number of condition satisfaction times;

[0015] S4. Obtain the latest health-related data uploaded by a single health device. If the current health device ID meets the next device ID in the symptom conversion rule, and the current health-related data acquisition time meets the duration threshold in the symptom conversion rule, then increase the number of repetitions of this step. When the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, record the health-related data of the current health device, set the condition satisfaction flag and increase the number of condition satisfaction times, otherwise repeat this step;

[0016] S5. Repeat the above step S4. When the number of times the condition is met is greater than the threshold number of times the condition is met in the symptom conversion rule, the current symptom conversion rule and the health-related data of each health device are used as health data, encoded together with the symptom name, and reported.

[0017] Preferably, the symptom conversion rule also includes a data identifier; the data content determination condition includes a data content determination threshold and a Boolean determination condition.

[0018] Preferably, the method for determining whether the data content satisfies the determination condition includes:

[0019] The category of the data content is identified according to the data identifier. If it is continuous data, whether it meets the conditions is determined according to the data content determination threshold; if it is Boolean data, whether it meets the conditions is determined according to the Boolean determination condition.

[0020] Preferably, the method further includes: temporarily storing the health-related data uploaded by the health devices acquired previously in a scan buffer, and clearing the scan buffer after the health data is encoded and reported.

[0021] The present invention also provides a health data conversion system for home health IoT devices, including:

[0022] A storage module, wherein the storage module is configured to have a built-in symptom conversion database, wherein the symptom conversion database is composed of symptom conversion rules, wherein the symptom conversion rules include: current device ID, data content determination condition, next device ID, duration threshold, repetition number flag, condition satisfaction flag, condition satisfaction number of times, and condition satisfaction number threshold;

[0023] A health-related data acquisition module, connected to the home health IoT device and the storage module respectively, and configured to acquire health-related data uploaded by a single health device in a time sequence, wherein the health-related data includes a health device ID and data content;

[0024] The rule determination module is connected to the storage module and the health-related data acquisition module respectively, and is configured to determine whether the health-related data satisfies the symptom conversion rule, and the determination method includes:

[0025] S11, obtaining the latest health-related data uploaded by a single health device, querying whether there is a symptom conversion rule in the symptom conversion database according to the health device ID, if so, extracting the symptom conversion rule corresponding to the health device ID, judging whether the data content meets the determination condition, if so, recording the health-related data of the current health device, setting a condition satisfaction flag and incrementing the number of times the condition is satisfied;

[0026] S22, obtaining the latest health-related data uploaded by a single health device. If the current health device ID meets the next device ID in the symptom conversion rule, and the current health-related data acquisition time meets the duration threshold in the symptom conversion rule, then the number of repetitions of this step is incremented. When the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, the health-related data of the current health device is recorded, the condition satisfaction flag is set, the number of condition satisfaction times is incremented, and step S22 is repeated;

[0027] The conversion module is connected to the rule judgment module and is configured to encode the current symptom conversion rule and the health-related data of each health device as health data together with the symptom name and report them after being encoded when the number of times the condition is met is greater than the threshold number of times the condition is met in the symptom conversion rule.

[0028] Preferably, the symptom conversion rule also includes a data identifier; the data content determination condition includes a data content determination threshold and a Boolean determination condition.

[0029] Preferably, the method by which the rule determination module determines whether the data content satisfies the determination condition includes:

[0030] The category of the data content is identified according to the data identifier. If it is continuous data, whether it meets the conditions is determined according to the data content determination threshold; if it is Boolean data, whether it meets the conditions is determined according to the Boolean determination condition.

[0031] Preferably, the storage module further includes a scan buffer subunit for temporarily storing the health-related data uploaded by the health devices acquired previously.

[0032] Preferably, it also includes a cleaning module, which is connected to the conversion module and the storage module respectively. After the conversion module encodes and reports the current symptom conversion rules and the health-related data of each health device, the scanning buffer subunit of the storage module is cleared.

[0033] Beneficial Effects

[0034] 1. Health data conversion: The conversion of smart home device data into health data is realized on the edge side. The collected device data is associated with the health data through preset symptom conversion rules and symptom conversion database.

[0035] 2. Real-time and accuracy: In the process of data collection and processing, the present invention obtains and analyzes the data uploaded by health devices, and ensures the real-time and accuracy of the data through edge computing. The multi-level conversion mechanism effectively avoids redundant data and abnormal data, and improves the accuracy and reliability of data processing.

[0036] 3. System integration and configurability: The system structure is reasonably designed, and the various modules work together with a high degree of integration. Symptom conversion rules can be remotely configured and updated through the cloud platform, with good flexibility and scalability, and can adapt to the needs of different users and devices, thus improving the scope of application and user experience of the system.

[0037] 4. Reduce network load: Through edge-side cleaning and conversion processing, the amount of data that needs to be transmitted is reduced, which greatly reduces the network bandwidth occupancy and improves the overall network load capacity and response speed, making it suitable for application in home environments with limited resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A schematic flow chart of a method for converting health data for a home health IoT device provided by a preferred embodiment of the present invention;

[0039] Figure 2 A schematic diagram of the structure of a health data conversion system for home health Internet of Things devices provided by a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described below in conjunction with the accompanying drawings. In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside", "outside" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention.

[0041] Example 1.

[0042] like Figure 1 As shown, this embodiment provides a health data conversion method for a home health IoT device, including the steps of:

[0043] S1. Construct symptom conversion rules and store them as a symptom conversion database; the symptom conversion rules include: current device ID, data content judgment conditions, next step device ID, duration threshold, repetition number flag, condition satisfaction flag, condition satisfaction times and condition satisfaction times threshold.

[0044] It should be understood that the symptoms refer to health problems or abnormal manifestations that may occur in the user's daily life, which can be monitored and identified through the data of smart home devices. For example, symptoms such as frequent urination at night, insomnia, and qi deficiency that Chinese medicine pays attention to can be monitored and converted into health-related data through the data of smart home devices. The identification and monitoring of these symptoms helps to evaluate the user's health status and detect potential health problems at an early stage.

[0045] The data storage order of the symptom conversion rules will be set in advance according to the placement of the sensors in the room. By recording the physical position and triggering order of the sensors, it is possible to verify whether certain symptoms are triggered by the same user within a specific time, thereby ensuring the accuracy and consistency of the data, that is, the design of the symptom conversion database has an individual verification mechanism. The symptom conversion rules of the present invention can be constructed by technicians in this field according to actual needs, or they can be customized by technicians in cooperation with medical staff. The present invention does not further limit the construction method of this part.

[0046] In actual application scenarios, there is at least one next-step device. If there are multiple next-step devices, the number of next-step device IDs here should also be multiple, and the subsequent corresponding data and / or labels should also be multiple.

[0047] The duration threshold refers to the time stamp difference between two adjacent devices.

[0048] S2. Obtain the latest health-related data uploaded by a single health device, wherein the health-related data includes a health device ID and data content; query whether there is a symptom conversion rule in the symptom conversion database according to the health device ID, and if so, execute the next step.

[0049] It should be understood that the health device acquires raw device data, which needs to be converted into health-related data through cleaning and screening. On the one hand, it reduces the amount of data transmission, and on the other hand, the data processed in the subsequent steps is more relevant to the target content, that is, health-related content. Then, through further processing in the subsequent steps of the present invention, the health-related data is converted into final health data.

[0050] Among them, the data content refers to the specific data information uploaded by the smart home device. These data usually include but are not limited to various sensor data, status information, timestamps, etc. detected by the device. For example: the data content of the smart pillow includes the bed leaving status and sleep quality data, the data content of the smart toilet includes the usage status and urination status data, and the data content of the smart water cup includes the amount of water consumed, the number of times of drinking water, and the location data. These data contents are collected and uploaded by smart home devices, and can be used for health monitoring and analysis through specific processing and conversion rules. Furthermore, the acquired original device data needs to be cleaned and other pre-processing steps before it can be used. The health data during uploading also needs to be encoded according to the requirements of the receiving terminal, and data encryption and other operations need to be considered for the security of the data during the transmission process. Since these further operations on health data are not the focus of the present invention, they are not repeated here, and can be specifically set by the staff in this field according to actual needs.

[0051] Obviously, the same health device ID may correspond to multiple symptom conversion rules at the same time, and multiple symptom conversion rules need to be processed in parallel.

[0052] S3. Extract the symptom conversion rule corresponding to the health device ID, determine whether the data content meets the judgment condition, and if so, record the health-related data of the current health device, set the condition satisfaction flag and increment the number of times the condition is satisfied. This step is to screen and filter data. Specifically, by setting the judgment condition, data that meets the health monitoring needs can be screened out and irrelevant or abnormal data can be filtered out. For example, only when the data content meets a specific threshold or Boolean condition will it be recorded and further processed, which can avoid the interference of redundant data and improve the accuracy of data processing. Furthermore, the judgment condition helps to establish the association between smart home device data and health-related data. For example, if the heart rate data uploaded by the smart bracelet meets the set threshold, the data can be marked as health-related data, which is further used for the assessment and monitoring of health status. In some preferred embodiments, the symptom conversion rule also includes a data identifier; the data content judgment condition includes a data content judgment threshold and a Boolean judgment condition. At this time, the method for determining whether the data content meets the determination conditions includes: identifying the category of the data content according to the data identifier; if it is continuous data, determining whether it meets the conditions according to the data content determination threshold; if it is Boolean data, determining whether it meets the conditions according to the Boolean determination condition.

[0053] It should be understood that the setting of the condition satisfaction flag includes two operations. On the one hand, when the data content meets the judgment condition, the condition satisfaction flag is set and the number of times the condition is satisfied is incremented. On the other hand, after the increment operation of the number of times the condition is satisfied is completed, the condition satisfaction flag needs to be set to zero, that is, the flag bit is cleared, to facilitate the setting operation when the judgment condition is met next time.

[0054] S4. Obtain the latest health-related data uploaded by a single health device. If the current health device ID meets the next device ID in the symptom conversion rule, and the current health-related data acquisition time meets the duration threshold in the symptom conversion rule, then increase the number of repetitions of this step. When the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, record the health-related data of the current health device, set the condition satisfaction flag and increase the number of condition satisfaction times, otherwise repeat this step.

[0055] It should be noted that when the present invention acquires health-related data uploaded by health devices, it can be acquired sequentially in real time based on the time flow, or it can be acquired sequentially according to the order of timestamps in the stored historical data. The specific acquisition method should be set by technical personnel in this field according to the actual needs of the site.

[0056] The technical considerations for setting this step are as follows:

[0057] 1. Timeliness and order of data: The timeliness and order of health-related data are crucial for accurate identification of health symptoms. By obtaining the latest uploaded health-related data, it can be ensured that the system processes the latest and most relevant data.

[0058] 2. Multi-step judgment of symptom conversion rules: Symptom conversion rules contain multi-step judgments to ensure that a health symptom is identified only when multiple conditions are met. By judging conditions such as device ID, acquisition time, and number of repetitions, data related to health symptoms can be accurately screened out.

[0059] 3. Determine the number of times a single device is used: The setting of the number of times a single device is used can avoid data anomalies caused by accidental factors. By accumulating the number of times a single device is used, the reliability and consistency of the data can be ensured.

[0060] The following is a specific example of the collection of symptoms of frequent nocturia in traditional Chinese medicine:

[0061] 1. Get the latest data: Get the latest data uploaded by single health devices, such as smart pillows, bathroom door magnets, and smart toilets.

[0062] 2. Device ID judgment: judge whether the currently acquired health device ID meets the next device ID in the symptom conversion rule. For example, after the smart pillow triggers the bed leaving state, the next device ID may be the ID of the bathroom door magnet or smart toilet.

[0063] 3. Time threshold judgment: judge whether the acquisition time of the current health-related data is within the specified time threshold. For example, whether the time interval from leaving the bed to the change of the bathroom door magnetic state is within the set time range.

[0064] 4. Determine the number of repetitions of a single device: accumulate the number of repetitions of a single healthy device in the current step. When the number of times a single healthy device is used is greater than the repetition number flag in the symptom conversion rule, record the data of the current healthy device, set the condition satisfaction flag and increment the number of times the condition is satisfied.

[0065] 5. Record and increment: When the above conditions are met, record the data of the current health device, set the condition satisfaction flag, and increment the number of times the condition is satisfied. Otherwise, repeat this step and continue to obtain new data for judgment.

[0066] It should be understood that the number of repetitions in this step refers to the number of times a single device is repeatedly used in a symptom conversion rule, and the initial value of the number should be the target number of uses minus one. For example, in the determination of the symptom of frequent urination at night, after the smart pillow triggers the bed leaving state, the bathroom door magnet or smart toilet is used once, which can be considered that the symptom conversion rule is satisfied once, and the number of repetitions at this time is 0. In the determination of healthy hydration, the smart water cup needs to be used 7 times to be considered that the symptom conversion rule is satisfied once, and the number of repetitions at this time is 6.

[0067] Through the setting and specific operation of the above step S4, the data of smart home devices can be effectively screened and converted to ensure the accuracy and timeliness of the data, and ultimately achieve accurate monitoring and analysis of health symptoms. This not only improves the efficiency of data processing, but also ensures the reliability and practicality of health-related data.

[0068] S5. Repeat the above step S4. When the number of times the condition is met is greater than the threshold number of times the condition is met in the symptom conversion rule, the current symptom conversion rule and the health-related data of each health device are used as health data, encoded together with the symptom name, and reported.

[0069] Taking the above-mentioned frequent urination at night as an example, if the above conditions are met 3 times or more at night, it means that the symptom of frequent urination at night is met. At this time, the symptom name of "frequent urination at night" is encoded and reported. It should be understood that at this time, only the symptom satisfaction data is reported instead of all health-related data. On the one hand, it saves the computing power of encoding and decoding, and on the other hand, it also reduces the capacity of reported data and reduces the network load during data transmission.

[0070] In some preferred embodiments, in order to effectively utilize system resources, avoid problems such as memory overflow or data processing delays, and ensure the stability and efficiency of system operation, it is considered to temporarily store the health-related data uploaded by the health devices acquired previously in the scan buffer, encode the symptom name and report it, and then clear the scan buffer to prepare for subsequent data collection and processing.

[0071] Example 2.

[0072] like Figure 2 As shown, this embodiment provides a health data conversion system for home health IoT devices, including:

[0073] A storage module, wherein the storage module is configured to have a built-in symptom conversion database, wherein the symptom conversion database is composed of symptom conversion rules, wherein the symptom conversion rules include: current device ID, data content determination condition, next device ID, duration threshold, repetition number flag, condition satisfaction flag, condition satisfaction number of times, and condition satisfaction number threshold;

[0074] A health-related data acquisition module, connected to the home health IoT device and the storage module respectively, and configured to acquire health-related data uploaded by a single health device in a time sequence, wherein the health-related data includes a health device ID and data content;

[0075] The rule determination module is connected to the storage module and the health-related data acquisition module respectively, and is configured to determine whether the health-related data satisfies the symptom conversion rule, and the determination method includes:

[0076] S11, obtaining the latest health-related data uploaded by a single health device, querying whether there is a symptom conversion rule in the symptom conversion database according to the health device ID, if so, extracting the symptom conversion rule corresponding to the health device ID, judging whether the data content meets the determination condition, if so, recording the health-related data of the current health device, setting a condition satisfaction flag and incrementing the number of times the condition is satisfied;

[0077] S22, obtaining the latest health-related data uploaded by a single health device. If the current health device ID meets the next device ID in the symptom conversion rule, and the current health-related data acquisition time meets the duration threshold in the symptom conversion rule, then the number of repetitions of this step is incremented. When the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, the health-related data of the current health device is recorded, the condition satisfaction flag is set, the number of condition satisfaction times is incremented, and step S22 is repeated;

[0078] The conversion module is connected to the rule determination module and is configured to encode the current symptom conversion rule and the health-related data of each health device as health data together with the symptom name and report it after encoding when the number of times the condition is satisfied is greater than the condition satisfaction number threshold in the symptom conversion rule. The reporting refers to transmitting the encoded data packet to the execution mechanism of other subsequent steps, such as a cloud server, a user terminal, etc.

[0079] Preferably, the symptom conversion rule also includes a data identifier; the data content determination condition includes a data content determination threshold and a Boolean determination condition.

[0080] Preferably, the method by which the rule determination module determines whether the data content satisfies the determination condition includes:

[0081] The category of the data content is identified according to the data identifier. If it is continuous data, whether it meets the conditions is determined according to the data content determination threshold; if it is Boolean data, whether it meets the conditions is determined according to the Boolean determination condition.

[0082] Preferably, the storage module further includes a scan buffer subunit for temporarily storing the health-related data uploaded by the health devices acquired previously.

[0083] Preferably, it also includes a cleaning module, which is connected to the conversion module and the storage module respectively. After the conversion module encodes and reports the current symptom conversion rules and the health-related data of each health device, the scanning buffer subunit of the storage module is cleared.

[0084] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. Health data conversion method for home health IoT devices, It is characterized in that Includes steps: S1. Construct symptom conversion rules and store them as a symptom conversion database; the symptom conversion rules include: current device ID, data content judgment condition, next device ID, duration threshold, repetition number flag, condition satisfaction flag, condition satisfaction number of times and condition satisfaction number threshold; S2, obtaining the latest health-related data uploaded by a single health device, wherein the health-related data includes a health device ID and data content; querying whether there is a symptom conversion rule in the symptom conversion database according to the health device ID, and if so, executing the next step; S3, extracting the symptom conversion rule corresponding to the health device ID, determining whether the data content meets the determination condition, and if so, recording the health-related data of the current health device, setting the condition satisfaction flag and incrementing the number of condition satisfaction times; S4. Obtain the latest health-related data uploaded by a single health device. If the current health device ID meets the next device ID in the symptom conversion rule, and the current health-related data acquisition time meets the duration threshold in the symptom conversion rule, then increase the number of repetitions of this step. When the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, record the health-related data of the current health device, set the condition satisfaction flag and increase the number of condition satisfaction times, otherwise repeat this step; S5, repeating the above step S4, when the number of times the condition is satisfied is greater than the threshold number of times the condition is satisfied in the symptom conversion rule, the current symptom conversion rule and the health-related data of each health device are used as health data, and are encoded together with the symptom name and reported; The symptom conversion rule also includes a data identifier; the data content determination condition includes a data content determination threshold and a Boolean determination condition; The method for determining whether the data content meets the determination condition includes: Identify the category of the data content according to the data identifier; if it is continuous data, determine whether it meets the condition according to the data content determination threshold; if it is Boolean data, determine whether it meets the condition according to the Boolean determination condition; The health-related data uploaded by the health devices acquired previously are temporarily stored in the scan buffer. When the health data is encoded and reported, the scan buffer is cleared.

2. Health data conversion system for home health IoT devices, It is characterized in that include: A storage module, wherein the storage module is configured to have a built-in symptom conversion database, wherein the symptom conversion database is composed of symptom conversion rules, wherein the symptom conversion rules include: current device ID, data content determination condition, next device ID, duration threshold, repetition number flag, condition satisfaction flag, condition satisfaction number of times, and condition satisfaction number threshold; A health-related data acquisition module, connected to the home health IoT device and the storage module respectively, and configured to acquire health-related data uploaded by a single health device in a time sequence, wherein the health-related data includes a health device ID and data content; The rule determination module is connected to the storage module and the health-related data acquisition module respectively, and is configured to determine whether the health-related data satisfies the symptom conversion rule, and the determination method includes: S11, obtaining the latest health-related data uploaded by a single health device, querying whether there is a symptom conversion rule in the symptom conversion database according to the health device ID, if so, extracting the symptom conversion rule corresponding to the health device ID, judging whether the data content meets the determination condition, if so, recording the health-related data of the current health device, setting a condition satisfaction flag and incrementing the number of times the condition is satisfied; S22, obtaining the latest health-related data uploaded by a single health device. If the current health device ID meets the next device ID in the symptom conversion rule, and the current health-related data acquisition time meets the duration threshold in the symptom conversion rule, then the number of repetitions of this step is incremented. When the number of repetitions is greater than the number of repetitions flag in the symptom conversion rule, the health-related data of the current health device is recorded, the condition satisfaction flag is set, the number of condition satisfaction times is incremented, and step S22 is repeated; a conversion module connected to the rule determination module, configured to encode the current symptom conversion rule and the health-related data of each health device as health data together with the symptom name and report them after encoding when the number of times the condition is satisfied is greater than the threshold number of times the condition is satisfied in the symptom conversion rule; The symptom conversion rule also includes a data identifier; the data content determination condition includes a data content determination threshold and a Boolean determination condition; The method for the rule determination module to determine whether the data content meets the determination condition includes: Identify the category of the data content according to the data identifier; if it is continuous data, determine whether it meets the condition according to the data content determination threshold; if it is Boolean data, determine whether it meets the condition according to the Boolean determination condition; The storage module also includes a scan buffer subunit for temporarily storing the health-related data uploaded by the health devices acquired previously.

3. The health data conversion system for home health IoT devices as claimed in claim 2, Features: It also includes a cleaning module, which is connected to the conversion module and the storage module respectively. After the conversion module encodes and reports the current symptom conversion rules and the health-related data of each health device, the scanning buffer subunit of the storage module is cleared.

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