CN115981756A

CN115981756A - Data processing method, related device and communication system

Info

Publication number: CN115981756A
Application number: CN202111198750.0A
Authority: CN
Inventors: 刘江明
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-10-14
Filing date: 2021-10-14
Publication date: 2023-04-18
Also published as: WO2023061357A1

Abstract

The application provides a data processing method, a related device and a communication system. In the method, the data acquisition equipment can report data to the data display equipment according to the rules of the data dictionary. The data display device can recognize the data according to the rules of the data dictionary, analyze and display the data, synchronize the data to the cloud server and open the data to a three-party application. The cloud server and the three-party application can both recognize the data according to the rules of the data dictionary. The method can facilitate different types of data access data display equipment, cloud servers and codes of the three-party application to be multiplexed according to the rule definition of the data dictionary, so that the workload of developers is reduced, and the data access efficiency is improved.

Description

Data processing method, related device and communication system

Technical Field

The present application relates to the field of terminal technologies, and in particular, to a data processing method, a related apparatus, and a communication system.

Background

Along with the development of the internet of things technology, the types of equipment such as intelligent wearable equipment and intelligent household equipment are more and more. The equipment can collect various data such as exercise health data, family state data and the like of the user. The main function of these devices is to collect data, which may not have the capability of data analysis and display, or may have a weak capability of data analysis and display. The devices can send the collected data to electronic devices with data analysis and display capabilities, such as mobile phones, tablet computers and the like. However, as the types of data acquisition devices increase and the types of data increase, accessing data of the newly added type to the data display device requires a plurality of developers to modify the code logic to ensure that the data of the newly added type can be presented in the data display device and does not conflict with the existing data. This makes the new type of data access inefficient and developer workload high.

Disclosure of Invention

The application provides a data processing method, a related device and a communication system. According to the method, data acquired by data acquisition equipment are defined according to rules of a data dictionary, and different types of data can be multiplexed by accessing data display equipment, a cloud server and codes of three-party application. This can reduce the workload of developers when generating new types of data access data display devices, cloud servers, and three-party applications, and improve the efficiency of data access.

In a first aspect, the present application provides a data processing method. In the method, a first device receives first data from a first data acquisition device. The first data comprises a first data identification and a first sampling value of the first type of data, and conforms to the rules of the first configuration file. The first configuration file is defined according to a first rule. The first configuration file may contain a first data identifier, the first data identifier may be used to identify a first type of data, and the first data identifier may have uniqueness among data identifiers defined according to a first rule. The first device can recognize that the first data belongs to the first type data according to the first data identification and the first configuration file.

The first rule comprises definition and description of one or more of attributes of data identification, data name, data storage mode, data processing mode and the like. I.e. the first rule may be used to provide a uniform way of defining for different types of data. The data identifications defined according to the first rule have uniqueness among all the data identifications defined according to the first rule, and do not conflict with each other. The first rule may be a rule of a data dictionary.

In a possible implementation manner, the first configuration file may include a data type definition rule of the first type data. The data type definition rule may include the first data identifier. The first data may conform to a rule of a first configuration file, and specifically, a rule may be defined for a data type conforming to the first type data. The first data acquisition device may be configured to have data type definition rules for the first type of data. When the first sampling value of the first type of data is acquired, the first data acquisition device may associate the first data identifier with the first sampling value according to a data type definition rule of the first type of data to obtain the first data, and send the first data to the first device.

With reference to the first aspect, in some embodiments, the first device may receive second data from a second data acquisition device, where the second data includes a second data identifier and a second sample value of a second type of data, and conforms to a rule of a second configuration file, where the second configuration file is defined according to the first rule, and the second configuration file includes the second data identifier, where the second data identifier is used to identify the second type of data, and the second data identifier has uniqueness among data identifiers defined according to the first rule. The first device may recognize that the second data belongs to the second type of data according to the second data identification and the second configuration file. Wherein the procedure for identifying the first data in the first device is the same as the procedure for identifying the second data. The program for identifying data in the first device is code for identifying data.

The method for acquiring the second data by the second data acquisition device can refer to the method for acquiring the first data by the first data acquisition device.

In some embodiments, the first configuration file and the second configuration file may be two different configuration files. I.e. there may be one configuration file for each type of data defined according to the rules of the data dictionary. Optionally, the first configuration file and the second configuration file may be different parts in one configuration file. That is, the definition content corresponding to each type of data defined according to the rules of the data dictionary can be written into a configuration file.

As can be seen from the above embodiments, with the rule of the data dictionary, in the case of adding one type of data, the first device may identify the new type of data by using a data program that identifies an existing type. Therefore, the workload of development personnel in the process of accessing the data acquired by the data acquisition equipment into the first equipment can be reduced, and the efficiency of data access is improved.

With reference to the first aspect, in some embodiments, the first configuration file may further include a fusion policy for the first type of data. Such as a multi-source fusion strategy, a homologous fusion strategy.

The first device can perform data fusion on the data acquired by the different data acquisition devices according to a multi-source fusion strategy defined in a configuration file of the data of the same type under the condition of receiving the data of the same type acquired by the different data acquisition devices at the same time.

Specifically, the first sampling value is acquired by the first data acquisition device at a first time. The first device also receives M sample values of the first type of data, the M sample values being acquired by the M data acquisition devices at a first time, respectively. M is a positive integer. The method comprises the steps that a first device determines a data fusion strategy of first type data as a first fusion strategy from a first configuration file, and determines a sampling value from a first sampling value and M sampling values according to the first fusion strategy, wherein the sampling value is used as a sampling value of the first type data at a first time; the first fusion strategy is any one of the following: the method comprises the steps of taking a maximum value, taking a minimum value, taking a value with the earliest time of accessing the first equipment, taking a value with the latest time of accessing the first equipment, and taking a sampling value collected by the equipment with the highest equipment priority in the first data collection equipment and the M data collection equipment.

When the data acquisition device determines that one type of data cannot be acquired immediately to obtain an immediate result and needs to process a plurality of data acquired in a previous period of time to obtain a result, the first device can perform data fusion on the plurality of data acquired by the same data acquisition device according to a homologous fusion strategy defined in a configuration file of the type of data.

In some embodiments, the second configuration file may further include a fusion policy for the second type of data. The first device may further perform data fusion on the sampling value of the second type of data according to a fusion policy in the second configuration file. It can be understood that, since the first type data and the second type data are defined according to the rules of the data dictionary and have different data identifications, in the case that the fusion policy of the first type data is the same as the fusion policy of the second type data, the first device may call the same program for data fusion to perform data fusion on the first type data and the second type data. I.e. the procedures for data fusion of different types of data defined according to the rules of the data dictionary can be multiplexed. This may reduce the workload of the developer and improve the efficiency of the data access to the first device.

In some embodiments, in combination with the first aspect, the first configuration file may further include a statistical policy for the first type of data.

The first device may perform data statistics on sampling values of one type of data in a period of time according to a statistical policy defined in a configuration file of the one type of data.

Specifically, the first device may determine, from the first configuration file, that the data statistical policy of the first type of data is a first statistical policy, where the first statistical policy includes one or more of the following: calculating the maximum value, calculating the minimum value, calculating the mean value, summing, calculating the variance, calculating the number of sampling values and determining the sampling value with the latest acquisition time. The first device may perform data statistics on N sampling values of the first type of data in the first time period at the collection time according to a first statistical strategy, where N is a positive integer.

In some embodiments, the second configuration file may further include a statistical policy for the second type of data. It can be understood that, since the first type data and the second type data are defined according to the rules of the data dictionary and have different data identifiers, in the case that the statistical policy of the first type data is the same as the statistical policy of the second type data, the first device may call the same program for performing data statistics on the first type data and the second type data. I.e. the procedures for data statistics on different types of data defined by the rules of the data dictionary can be multiplexed. This may reduce the workload of the developer and improve the efficiency of the data access to the first device.

In conjunction with the first aspect, in some embodiments, the first type of data may be a single point of data. The single point data may indicate that the data collection device collects only one type of data when collecting data at one time. For example, heart rate data, body temperature data, and weight data are single point data. The single point of data may contain one field. For example, heart rate data contains a field known as heart rate. The single point of data may have a data identification. The fields contained in the single point of data may have field identifications. Since the single-point data only includes one field, the first data identifier for identifying the first type of data may be a data identifier of the first type of data as the single-point data, or may also be a field identifier of a field included in the first type of data.

In other embodiments, the first type of data may be a field in the multipoint data. Multipoint data may indicate that multiple types of data may be available for data acquisition by the data acquisition device at one time. For example, the blood pressure data is multipoint data. The multipoint data may comprise a plurality of fields. For example, blood pressure data may contain two fields: diastolic pressure, systolic pressure. The multipoint data may have a data identification. Each field contained in the multipoint data may have a different field identification. The first data identifier for identifying the first type of data may be a field identifier. Optionally, when sampling values of a plurality of fields included in one multipoint data are collected, the data collecting device may also send the data identifier of the one multipoint data, the field identifiers of the plurality of fields included in the one multipoint data, and the sampling values of the plurality of fields to the first device.

With reference to the first aspect, in some embodiments, the first device includes a display apparatus, the first configuration file includes a first display policy for the first type of data, and the first display policy includes one or more of: a first display form and a first display position. The first device may display, through the display apparatus, the received sampling values of the first type of data on the first user interface according to the first display policy.

With reference to the first aspect, in some embodiments, the second configuration file includes a second display policy for the second type of data, the second display policy being the same as the first display policy. The first equipment can also display the received sampling value of the second type of data on a second user interface according to a first display strategy through a display device; the procedure for displaying the sampling values of the first type of data according to the first display strategy is the same as the procedure for displaying the sampling values of the second type of data according to the first display strategy. For example, the first display form described above is a line graph, and the first device may call the same program for drawing a line graph to draw sample values of the first type data and sample values of the second type data.

It can be seen that the programs for displaying different types of data defined by the rules of the data dictionary can be multiplexed. This may reduce the workload of the developer and improve the efficiency of the data access to the first device.

With reference to the first aspect, in some embodiments, the first configuration file further includes first description information of the first type of data. The first description information may be, for example, a name of the first type of data. The first device may send third data to the cloud server, the third data including the first description information and the sampled value of the first type of data. The cloud server may store the third data. This may enable a first type of data cloud synchronization.

In some embodiments, the second configuration file further comprises second descriptive information for the second type of data. The second description information may be, for example, a name of the second type of data. The first device may transmit data containing the second description information and the sampled value of the second type of data to the cloud server. The cloud server may store the sampled value of the second type of data.

The first device may send the third data and the data including the sampling values of the second description information and the second type data to the cloud server through the same data interaction interface, because the first type data and the second type data are both defined according to rules of a data dictionary and have different data identifiers. That is, when new types of data are generated, a developer may not additionally develop a data interaction interface applicable to the newly added type of data in the first device to access the cloud server. The workload of developers when the newly added type data is accessed to the cloud server can be reduced, and the data access efficiency is improved.

With reference to the first aspect, in some embodiments, a first application program is installed in the first device, the first application program has a right to acquire the first type of data, and the first configuration file includes first description information of the first type of data. The first device may provide the fourth data to the first application in response to a request by the first application to obtain the first type of data. The fourth data contains the first description information and the sample value of the first type of data.

In some embodiments, the first application has permission to obtain the first type of data. The second configuration file comprises second description information of the second type of data. The first device may provide data containing the second description information and the sampled values of the second type of data to the first application in response to a request by the first application to obtain the first type of data.

The first device may provide the fourth data and the data including the sampling values of the second description information and the second type data to the first application program through the same data open interface, because the first type data and the second type data are both defined according to rules of the data dictionary and have different data identifiers. That is, when generating new type data, the developer may not separately develop a data opening interface of the first device, which is suitable for opening the new type data to the first application program. This can reduce the workload of developers when new type data is opened to the first application program, and improve the efficiency of data access.

With reference to the first aspect, in some embodiments, the first device is a cloud server. The cloud server may send fifth data to the data display device, where the fifth data includes the first data identifier and the sampled value of the first type of data. That is, the first data collecting device may transmit the collected data to the cloud server according to the rule of the data dictionary. The cloud server may identify data from the data collection device from a configuration file that follows rules of the data dictionary and send the data from the data collection device to the data display device. The data display device stores therein a configuration file following the rules of the data dictionary. The data display device may identify the received data from a configuration file that follows rules of the data dictionary and process the data according to rules in the configuration file, such as a display policy, a data fusion policy, and a data statistics policy. For example, the data display device may recognize that the fifth data belongs to the first type data according to the first data identifier and the first profile. Further, the data display device may sample values of the first type of data according to a display policy in the first profile.

In some embodiments, the first device is a cloud server. The first configuration file comprises first description information of the first type data. The cloud server may transmit the sixth data to the data display apparatus. The sixth data may contain the first description information and the sample value of the first type of data. And the data display device receives the sixth data, and can determine that the sixth data belongs to the first type of data according to the first description information in the sixth data. That is, the data display apparatus may not recognize the type of the sixth data from the profile following the rule of the data dictionary. Wherein, the data display equipment stores the configuration file following the rule of the data dictionary. The data display device may determine rules such as a display policy, a data statistics policy, and a data fusion policy of the first type of data according to the first configuration file, and process the sampling value of the first type of data.

In some embodiments, the first device is a cloud server. The cloud server may transmit the sixth data to the data display apparatus. In addition, the cloud server can also send the display policy, the data fusion policy, the data statistics policy and other rules in the first configuration file to the data display device. In this way, configuration files that comply with the rules of the data dictionary may not be stored in the data display device. And the data display equipment receives the sixth data and can determine that the sixth data belongs to the first type data according to the first description information in the sixth data. The data display device may process the first type data according to the received rule for processing the first type data.

With reference to the first aspect, in some embodiments, the first data acquisition device may be any one of: intelligence wrist-watch, intelligent bracelet, body fat balance, intelligent glasses, clinical thermometer, sphygmomanometer, rhythm of the heart monitoring facilities.

With reference to the first aspect, in some embodiments, the first type data may be any one of: walking data, running data, swimming data, riding data, sleeping data, weight data, pressure data, heart rate data, blood pressure data, body temperature data, blood oxygen data, blood glucose data.

In a second aspect, the present application provides a data processing method. The first data acquisition equipment can acquire first data, the first data comprise a first data identifier and a first sampling value of first type data, and the first data accord with rules of a first configuration file, the first configuration file is defined according to the first rules, the first configuration file comprises the first data identifier, the first data identifier is used for identifying the first type data, and the first data identifier has uniqueness in the data identifier defined according to the first rules. The first data acquisition equipment sends the first data to the first equipment.

The first rule may be a rule of a data dictionary.

In combination with the second aspect, in some embodiments, the first data acquisition device may be any one of: intelligence wrist-watch, intelligent bracelet, body fat balance, intelligent glasses, clinical thermometer, sphygmomanometer, rhythm of the heart monitoring facilities.

In combination with the second aspect, in some embodiments, the first type of data may be any one of: walking data, running data, swimming data, riding data, sleeping data, weight data, pressure data, heart rate data, blood pressure data, body temperature data, blood oxygen data, blood glucose data.

In a third aspect, the present application provides a communication system. The communication system may include a first data acquisition device and a data display device. The first data acquisition equipment can be used for acquiring first data and sending the first data to the data display equipment; the first data comprises a first data identifier and a first sampling value of the first type of data, and conforms to the rule of a first configuration file, the first configuration file is defined according to the first rule, the first configuration file comprises the first data identifier, the first data identifier is used for identifying the first type of data, and the first data identifier has uniqueness in the data identifier defined according to the first rule. The data display device can be used for recognizing that the first data belongs to the first type data according to the first data identification and the first configuration file.

The first rule may be a rule of a data dictionary.

With reference to the third aspect, in some embodiments, the communication system may further include a cloud server, and the first profile includes first descriptive information of the first type of data. The data display device may be further configured to send third data to the cloud server, where the third data includes the first description information and the sampled value of the first type of data. The cloud server may be operable to store the third data.

In a fourth aspect, the present application provides an apparatus. The above-mentioned apparatus includes: communication means, a memory operable to store a computer program, and a processor operable to invoke the computer program to cause the apparatus to perform a method as any one of the first or second aspects may implement.

In a fifth aspect, the present application provides a chip applied to a device, where the chip includes one or more processors, and the processor is configured to invoke computer instructions to cause the device to execute a method implemented as any one of the first aspect and the second aspect.

In a sixth aspect, the present application provides a computer program product containing instructions, which when run on a device causes the device to perform a method as any one of the first or second possible implementations.

In a seventh aspect, the present application provides a computer-readable storage medium, which includes instructions, and is characterized in that when the instructions are executed on a device, the device is caused to execute the method according to any one of the first aspect and the second aspect.

It is understood that the apparatus provided in the fourth aspect, the chip provided in the fifth aspect, the computer program product provided in the sixth aspect, and the computer-readable storage medium provided in the seventh aspect are all used to execute the method provided in the embodiments of the present application. Therefore, the beneficial effects achieved by the method can refer to the beneficial effects in the corresponding method, and the details are not repeated here.

Drawings

Fig. 1 is a schematic structural diagram of a communication system 10 according to an embodiment of the present application;

fig. 2A is a schematic structural diagram of an electronic device 100 according to an embodiment of the present disclosure;

fig. 2B is a block diagram of a software structure of an electronic device 100 according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of another communication system 30 provided in the embodiment of the present application;

fig. 4 is a schematic structural diagram of another communication system 40 provided in the embodiment of the present application;

fig. 5A to 5C are schematic views of some electronic devices 100 displaying body temperature data according to embodiments of the present disclosure;

fig. 6 is a schematic structural diagram of another communication system 60 according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and exhaustively described below with reference to the accompanying drawings. In the description of the embodiments herein, "/" means "or" unless otherwise specified, for example, a/B may mean a or B; "and/or" in the text is only an association relationship describing an associated object, and means that three relationships may exist, for example, a and/or B may mean: three cases of a alone, a and B both, and B alone exist, and in addition, "a plurality" means two or more than two in the description of the embodiments of the present application.

In the following, the terms "first", "second" are used for descriptive purposes only and are not to be understood as implying or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of embodiments of the application, unless stated otherwise, "plurality" means two or more.

Referring to fig. 1, fig. 1 is a schematic structural diagram of a communication system 10 according to an embodiment of the present disclosure.

As shown in fig. 1, communication system 10 may include an electronic device 100, one or more data collection devices, a cloud server 300, and a three-party application server 301. Wherein:

the one or more data acquisition devices may include a smart watch 201, a smart bracelet 202, a body fat scale 203, smart glasses 204. The device is not limited to the equipment for collecting exercise health data of users, and the data collecting equipment can further comprise intelligent household equipment such as an intelligent air conditioner, an intelligent refrigerator, an air purifier, a water immersion monitor and a gas monitor. The intelligent household equipment can be used for collecting family state data of the user. The data collected by the data collection device may also include configuration data of the device, operating status of the device, and the like, without being limited to the exercise health data and the family status data. The embodiment of the present application does not limit the specific type of the data acquisition device.

The exercise health data may include step number, calories, exercise records, sleep, weight, pressure, heart rate, body temperature, blood glucose, blood pressure, and the like. The home state data may include a temperature of a home, a food material in the smart refrigerator, an air quality index, a water quality, a gas usage state, and the like.

In some embodiments, the area of the data capture device used to display data (e.g., a display screen) is limited in size, and may simply present the data captured by the device and send the data captured by the device to the electronic device 100 (e.g., a cell phone). The electronic device 100 can analyze the data from the data acquisition device and present rich analysis results and related suggestions. For example, the smart watch 201 may be used to collect a heart rate of the user. The smart watch 201 may only display the heart rate of the user at the current time. The smart watch 201 may send the acquired heart rate to the electronic device 100. The electronic device 100 may calculate the result of analysis of the resting heart rate, heart rate range, periods of too high heart rate, periods of too low heart rate, etc. of the user based on the heart rate of the user over a period of time and provide advice for improving the heart health level.

Optionally, the data acquisition device does not have the capability to display data. The data collecting device may collect only data and transmit the collected data to the electronic device 100. The electronic device 100 may analyze and display the received data.

The electronic device 100 can be used as a data display device to analyze data from the data acquisition device and present rich analysis results and related suggestions. The electronic device 100 may have a display device. Such as a display screen. The electronic apparatus 100 may be mounted

Or other operating system, such as a cell phone, tablet, etc., and may also be a laptop computer with a touch-sensitive surface or touch panel(s) (ii)Laptop), desktop computers with touch-sensitive surfaces or touch panels, and the like. The embodiment of the present application does not limit the specific type of the electronic device 100.

An Application (APP) for managing the data acquisition device may be installed in the electronic device 100. For example, in the case where the data collecting apparatus is an apparatus for collecting exercise health data, the apparatus management APP for managing the data collecting apparatus may include an exercise health APP. Under the condition that data acquisition equipment is the equipment of gathering family's state data, above-mentioned equipment management APP for managing data acquisition equipment can include intelligent house APP (like wisdom life APP).

A binding relationship may be established between the electronic device 100 and one or more data collection devices. The electronic device 100 and the data acquisition device may establish a binding relationship through an account. That is, the account number logged in on the APP used for controlling the data acquisition device in the electronic device 100 is the same as the account number logged in on the data acquisition device. Optionally, the electronic device 100 and the data acquisition device may also establish a binding relationship by scanning a two-dimensional code and using a bluetooth peer-to-peer manner. The method for establishing the binding relationship between the electronic device 100 and the data acquisition device in the embodiment of the present application is not particularly limited.

The data acquisition device can send the acquired data to the electronic device (such as the electronic device 100) which is in binding relationship with the data acquisition device. The data acquisition device may send the acquired data to the electronic device 100 through short-distance communication connections such as bluetooth communication connection, wireless fidelity (Wi-Fi) communication connection, and ZigBee communication connection.

The electronic device 100 may also upload data from the data collection device to the cloud server 300. Optionally, the electronic device 100 may further upload an analysis result and a related suggestion of analyzing the data acquired by the data acquisition device to the cloud server 300.

The cloud server 300 may receive and store data from the electronic device 100. The cloud server 300 may be an application server of the device management APP for managing the data acquisition device. The cloud server 300 may store a binding relationship between the electronic device 100 and the data acquisition device. In some embodiments, the cloud server 300 may be used for the electronic device 100 to remotely control the data collection device.

In some embodiments, the data collection device may also upload the data collected by itself to the cloud server 300 via a network. For example, the data collection device may be networked through a network access device. Or, the data acquisition device has a mobile data networking function (for example, a SIM card is inserted into the data acquisition device). The cloud server 300 may store data collected by the data collection device, and send the data collected by the data collection device to a data display device (e.g., the electronic device 100) having a binding relationship with the data collection device. The data display device can analyze the data from the data acquisition device and present the analysis results and related suggestions of the data.

In the following embodiments of the present application, a scenario in which the data acquisition device sends data to the data display device that establishes a binding relationship with the data acquisition device, and the data display device sends the data of the data acquisition device to the cloud server 300 is taken as an example for description.

In some embodiments, the APPs installed in the electronic device 100 may include a device management APP for managing the data acquisition device, and may also include a third party APP. The device management APP can be an APP matched with the data acquisition device. The data acquisition device may send the data acquired by itself to the electronic device 100 for managing its device management APP. The data acquisition device and the device management APP that manages the data acquisition device may be developed and manufactured by the same manufacturer. The three-party APP may be an APP other than the device management APP. The three-party APP can request permission to acquire data acquired by the data acquisition device. After the open authority of the data acquired by the data acquisition equipment is acquired, the three-party APP can acquire the data acquired by the data acquisition equipment through the open interface, and the data acquired by the data acquisition equipment is utilized to realize own services. The open interface may be provided by a device management APP.

Illustratively, the electronic device 100 has an exercise health APP and a YY exercise APP installed therein. The exercise health APP may be a device management APP in the electronic device 100, and may be used to manage a data acquisition device that is in a binding relationship with the electronic device 100. Such as a smart watch 201, a smart bracelet 202, etc. The YY motion APP may be a three-party APP in the electronic device 100. The YY sport APP can acquire data acquired by data acquisition equipment managed by the sport health APP, such as the smart watch 201 and the smart bracelet 202, through an open interface provided by the sport health APP, and the data are utilized to realize own services. For example, provide sports advice to the user, etc.

The three-party APP can acquire data acquired by the data acquisition equipment through an open interface provided by the equipment management APP. The three-party APP may also upload data acquired by the data acquisition device and data generated in the process of implementing relevant services by using the data acquired by the data acquisition device, and the like, to the three-party application server 301. Three-party application server 301 may store the data from three-party APPs described above. The process of sending data from the three-party APP to the three-party application server 301 may specifically be a process of sending data of the three-party APP to the three-party application server 301 by an electronic device (for example, the electronic device 100) equipped with the three-party APP. The embodiment of the present application is not limited to the specific implementation manner of the electronic device 100 sending data to the server (e.g., the cloud server 300 or the three-party application server 301).

Referring to fig. 2A, fig. 2A schematically illustrates a structure of an electronic device 100 according to an embodiment of the present disclosure.

As shown in fig. 2A, the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a Universal Serial Bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, a Subscriber Identity Module (SIM) card interface 195, and the like. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, and the like.

It is to be understood that the illustrated structure of the embodiment of the present invention does not specifically limit the electronic device 100. In other embodiments of the present application, electronic device 100 may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

Processor 110 may include one or more processing units, such as: the processor 110 may include an Application Processor (AP), a modem processor, a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a controller, a video codec, a Digital Signal Processor (DSP), a baseband processor, and/or a neural-Network Processing Unit (NPU), etc. Wherein, the different processing units may be independent devices or may be integrated in one or more processors.

The controller can generate an operation control signal according to the instruction operation code and the timing signal to complete the control of instruction fetching and instruction execution.

A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may hold instructions or data that have just been used or recycled by the processor 110. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. Avoiding repeated accesses reduces the latency of the processor 110, thereby increasing the efficiency of the system.

The USB interface 130 is an interface conforming to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, or the like. The USB interface 130 may be used to connect a charger to charge the electronic device 100, and may also be used to transmit data between the electronic device 100 and a peripheral device. And the earphone can also be used for connecting an earphone and playing audio through the earphone. The interface may also be used to connect other electronic devices, such as AR devices and the like.

The charging management module 140 is configured to receive charging input from a charger. The charger may be a wireless charger or a wired charger. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charging management module 140, and supplies power to the processor 110, the internal memory 121, the display 194, the camera 193, the wireless communication module 160, and the like.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like.

The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 100 may be used to cover a single or multiple communication bands. Different antennas can also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may be multiplexed as a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 150 may provide a solution including 2G/3G/4G/5G wireless communication applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a Low Noise Amplifier (LNA), and the like. The mobile communication module 150 may receive the electromagnetic wave from the antenna 1, filter, amplify, etc. the received electromagnetic wave, and transmit the electromagnetic wave to the modem processor for demodulation. The mobile communication module 150 may also amplify the signal modulated by the modem processor, and convert the signal into electromagnetic wave through the antenna 1 to radiate the electromagnetic wave. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be disposed in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be provided in the same device as at least some of the modules of the processor 110.

The wireless communication module 160 may provide a solution for wireless communication applied to the electronic device 100, including Wireless Local Area Networks (WLANs) (e.g., wireless fidelity (Wi-Fi) networks), bluetooth (bluetooth, BT), global Navigation Satellite System (GNSS), frequency Modulation (FM), near Field Communication (NFC), infrared (IR), and the like. The wireless communication module 160 may be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, performs frequency modulation and filtering processing on electromagnetic wave signals, and transmits the processed signals to the processor 110. The wireless communication module 160 may also receive a signal to be transmitted from the processor 110, perform frequency modulation and amplification on the signal, and convert the signal into electromagnetic waves through the antenna 2 to radiate the electromagnetic waves.

The electronic device 100 implements display functions via the GPU, the display screen 194, and the application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.

The display screen 194 is used to display images, video, and the like. The display screen 194 includes a display panel. The display panel may adopt a Liquid Crystal Display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (active-matrix organic light-emitting diode, AMOLED), a flexible light-emitting diode (FLED), a miniature, a Micro-oeld, a quantum dot light-emitting diode (QLED), and the like. In some embodiments, the electronic device 100 may include 1 or N display screens 194, N being a positive integer greater than 1.

The electronic device 100 may implement a shooting function through the ISP, the camera 193, the video codec, the GPU, the display 194, the application processor, and the like.

The ISP is used to process the data fed back by the camera 193. For example, when a photo is taken, the shutter is opened, light is transmitted to the camera photosensitive element through the lens, the optical signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing and converting into an image visible to naked eyes.

The camera 193 is used to capture still images or video. The object generates an optical image through the lens and projects the optical image to the photosensitive element. The photosensitive element converts the optical signal into an electrical signal, and then transmits the electrical signal to the ISP to be converted into a digital image signal. And the ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into image signal in standard RGB, YUV and other formats. In some embodiments, electronic device 100 may include 1 or N cameras 193, N being a positive integer greater than 1.

The digital signal processor is used for processing digital signals, and can process other digital signals besides digital image signals. For example, when the electronic device 100 selects a frequency bin, the digital signal processor is used to perform fourier transform or the like on the frequency bin energy.

Video codecs are used to compress or decompress digital video. The electronic device 100 may support one or more video codecs. In this way, the electronic device 100 may play or record video in a variety of encoding formats, such as: moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, and the like.

The NPU is a neural-network (NN) computing processor that processes input information quickly by using a biological neural network structure, for example, by using a transfer mode between neurons of a human brain, and can also learn by itself continuously. Applications such as intelligent recognition of the electronic device 100 can be realized through the NPU, for example: image recognition, face recognition, speech recognition, text understanding, and the like.

The internal memory 121 may include one or more Random Access Memories (RAMs) and one or more non-volatile memories (NVMs).

The random access memory may include static random-access memory (SRAM), dynamic random-access memory (DRAM), synchronous dynamic random-access memory (SDRAM), double data rate synchronous dynamic random-access memory (DDR SDRAM), such as fifth generation DDR SDRAM generally referred to as DDR5 SDRAM, and the like;

the nonvolatile memory may include a magnetic disk storage device, a flash memory (flash memory).

The FLASH memory may include NOR FLASH, NAND FLASH, 3D NAND FLASH, etc. according to the operation principle, may include single-level cell (SLC), multi-level cell (MLC), triple-level cell (TLC), quad-level cell (QLC), etc. according to the level order of the memory cell, and may include universal FLASH memory (english: UFS), embedded multimedia memory Card (mc em), etc. according to the storage specification.

The random access memory may be read and written directly by the processor 110, may be used to store executable programs (e.g., machine instructions) of an operating system or other programs in operation, and may also be used to store data of users and applications, etc.

The nonvolatile memory may also store executable programs, data of users and application programs, and the like, and may be loaded in advance into the random access memory for the processor 110 to directly read and write.

The external memory interface 120 may be used to connect an external nonvolatile memory to extend the storage capability of the electronic device 100. The external non-volatile memory communicates with the processor 110 through the external memory interface 120 to implement data storage functions. For example, files such as music, video, etc. are saved in an external nonvolatile memory.

The electronic device 100 may implement audio functions via the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone interface 170D, and the application processor. Such as music playing, recording, etc.

The audio module 170 is used to convert digital audio information into analog audio signals for output, and also used to convert analog audio inputs into digital audio signals. The audio module 170 may also be used to encode and decode audio signals. In some embodiments, the audio module 170 may be disposed in the processor 110, or some functional modules of the audio module 170 may be disposed in the processor 110.

The speaker 170A, also called a "horn", is used to convert the audio electrical signal into an acoustic signal. The electronic apparatus 100 can listen to music through the speaker 170A or listen to a handsfree call.

The receiver 170B, also called "earpiece", is used to convert the electrical audio signal into an acoustic signal. When the electronic apparatus 100 receives a call or voice information, it can receive voice by placing the receiver 170B close to the ear of the person.

The microphone 170C, also referred to as a "microphone," is used to convert sound signals into electrical signals.

The earphone interface 170D is used to connect a wired earphone. The headset interface 170D may be the USB interface 130, or may be a 3.5mm open mobile electronic device platform (OMTP) standard interface, a cellular telecommunications industry association (cellular telecommunications industry association of the USA, CTIA) standard interface.

The pressure sensor 180A is used for sensing a pressure signal, and can convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A may be disposed on the display screen 194.

The gyro sensor 180B may be used to determine the motion attitude of the electronic device 100. In some embodiments, the angular velocity of electronic device 100 about three axes (i.e., the x, y, and z axes) may be determined by gyroscope sensor 180B.

The air pressure sensor 180C is used to measure air pressure. In some embodiments, electronic device 100 calculates altitude from barometric pressure values measured by barometric pressure sensor 180C to assist in positioning and navigation.

The magnetic sensor 180D includes a hall sensor. The electronic device 100 may detect the opening and closing of the flip holster using the magnetic sensor 180D.

The acceleration sensor 180E may detect the magnitude of acceleration of the electronic device 100 in various directions (typically three axes). The magnitude and direction of gravity can be detected when the electronic device 100 is stationary. The method can also be used for recognizing the posture of the electronic equipment, and is applied to horizontal and vertical screen switching, pedometers and other applications.

A distance sensor 180F for measuring a distance. The electronic device 100 may measure the distance by infrared or laser. In some embodiments, taking a picture of a scene, electronic device 100 may utilize range sensor 180F to range for fast focus.

The proximity light sensor 180G may include, for example, a Light Emitting Diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The electronic device 100 emits infrared light to the outside through the light emitting diode. The electronic device 100 detects infrared reflected light from nearby objects using a photodiode. When sufficient reflected light is detected, it can be determined that there is an object near the electronic device 100. When insufficient reflected light is detected, the electronic device 100 may determine that there are no objects near the electronic device 100.

The ambient light sensor 180L is used to sense the ambient light level. Electronic device 100 may adaptively adjust the brightness of display screen 194 based on the perceived ambient light level.

The fingerprint sensor 180H is used to collect a fingerprint. The electronic device 100 may utilize the collected fingerprint characteristics to unlock a fingerprint, access an application lock, photograph a fingerprint, answer an incoming call with a fingerprint, and so on.

The temperature sensor 180J is used to detect temperature. In some embodiments, electronic device 100 implements a temperature processing strategy using the temperature detected by temperature sensor 180J. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold, the electronic device 100 performs a reduction in performance of a processor located near the temperature sensor 180J, so as to reduce power consumption and implement thermal protection.

The touch sensor 180K is also called a "touch device". The touch sensor 180K may be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, which is also called a "touch screen". The touch sensor 180K is used to detect a touch operation applied thereto or nearby. The touch sensor can communicate the detected touch operation to the application processor to determine the touch event type. Visual output associated with the touch operation may be provided via the display screen 194. In other embodiments, the touch sensor 180K may be disposed on a surface of the electronic device 100, different from the position of the display screen 194.

The bone conduction sensor 180M may acquire a vibration signal. In some embodiments, the bone conduction sensor 180M may acquire a vibration signal of the human vocal part vibrating the bone mass. The bone conduction sensor 180M may also contact the human pulse to receive the blood pressure pulsation signal.

The keys 190 include a power-on key, a volume key, and the like. The keys 190 may be mechanical keys. Or may be touch keys. The electronic apparatus 100 may receive a key input, and generate a key signal input related to user setting and function control of the electronic apparatus 100.

The motor 191 may generate a vibration cue. The motor 191 may be used for incoming call vibration cues, as well as for touch vibration feedback.

Indicator 192 may be an indicator light that may be used to indicate a state of charge, a change in charge, or a message, missed call, notification, etc.

The SIM card interface 195 is used to connect a SIM card. The SIM card can be attached to and detached from the electronic device 100 by being inserted into the SIM card interface 195 or being pulled out of the SIM card interface 195. The electronic device 100 may support 1 or N SIM card interfaces, N being a positive integer greater than 1. The SIM card interface 195 may support a Nano SIM card, a Micro SIM card, a SIM card, etc. The same SIM card interface 195 can be inserted with multiple cards at the same time. The types of the plurality of cards may be the same or different. The SIM card interface 195 may also be compatible with different types of SIM cards. The SIM card interface 195 may also be compatible with external memory cards. The electronic device 100 interacts with the network through the SIM card to implement functions such as communication and data communication. In some embodiments, the electronic device 100 employs esims, namely: an embedded SIM card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100.

The software system of the electronic device 100 may employ a layered architecture, an event-driven architecture, a micro-core architecture, a micro-service architecture, or a cloud architecture. The embodiment of the present application takes an Android system with a hierarchical architecture as an example, and exemplarily illustrates a software structure of the electronic device 100.

Fig. 2B is a block diagram of a software structure of the electronic device 100 according to the embodiment of the present application.

The layered architecture divides the software into several layers, each layer having a clear role and division of labor. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, an application layer, an application framework layer, an Android runtime (Android runtime) and system library, and a kernel layer from top to bottom.

The application layer may include a series of application packages.

As shown in fig. 3, the application packages may include camera, gallery, calendar, phone call, map, navigation, WLAN, bluetooth, music, video, sports, etc. applications. In addition to the exercise health APP, the application package may also contain more applications for managing the data collection device.

The application framework layer provides an Application Programming Interface (API) and a programming framework for the application program of the application layer. The application framework layer includes a number of predefined functions.

As shown in FIG. 3, the application framework layers may include a window manager, content provider, view system, phone manager, resource manager, notification manager, and the like.

The window manager is used for managing window programs. The window manager can obtain the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make it accessible to applications. The data may include video, images, audio, calls made and received, data collected from data collection devices (e.g., exercise health data, home status data), and the like.

The view system includes visual controls such as controls to display text, controls to display pictures, and the like. The view system may be used to build applications. The display interface may be composed of one or more views. For example, the display interface including the short message notification icon may include a view for displaying text and a view for displaying pictures.

The phone manager is used to provide communication functions of the electronic device 100. Such as management of call status (including on, off, etc.).

The resource manager provides various resources for the application, such as localized strings, icons, pictures, layout files, video files, and the like.

The notification manager enables the application to display notification information in the status bar, can be used to convey notification-type messages, can disappear automatically after a short dwell, and does not require user interaction. Such as a notification manager used to notify download completion, message alerts, etc. The notification manager may also be a notification that appears in the form of a chart or scrollbar text in a status bar at the top of the system, such as a notification of a running application in the background, or a notification that appears on the screen in the form of a dialog window. For example, prompting text information in the status bar, sounding a prompt tone, vibrating the electronic device, flashing an indicator light, etc.

In some embodiments, the electronic device 100 may store the data sent by the data collection device in the content provider. The exercise health APP may obtain data from the data collection device from the content provider and analyze the data from the data collection device. The exercise health APP can call the view system to display data from the data acquisition device and analysis results of the data.

The Android Runtime comprises a core library and a virtual machine. The Android runtime is responsible for scheduling and managing an Android system.

The core library comprises two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. The virtual machine executes java files of the application layer and the application framework layer as binary files. The virtual machine is used for performing the functions of object life cycle management, stack management, thread management, safety and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface managers (surface managers), media Libraries (Media Libraries), three-dimensional graphics processing Libraries (e.g., openGL ES), 2D graphics engines (e.g., SGL), and the like.

The surface manager is used to manage the display subsystem and provide a fusion of the 2D and 3D layers for multiple applications.

The media library supports a variety of commonly used audio, video format playback and recording, and still image files, among others. The media library may support a variety of audio-video encoding formats, such as MPEG4, h.264, MP3, AAC, AMR, JPG, PNG, and the like.

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

The 2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

The following describes exemplary workflow of the software and hardware of the electronic device 100 in connection with capturing a photo scene.

When the touch sensor 180K receives a touch operation, a corresponding hardware interrupt is issued to the kernel layer. The kernel layer processes the touch operation into an original input event (including touch coordinates, a time stamp of the touch operation, and other information). The raw input events are stored at the kernel layer. And the application program framework layer acquires the original input event from the kernel layer and identifies the control corresponding to the input event. Taking the touch operation as a touch click operation, and taking a control corresponding to the click operation as a control of a camera application icon as an example, the camera application calls an interface of an application framework layer, starts the camera application, further starts a camera drive by calling a kernel layer, and captures a still image or a video through the camera 193.

A data processing method is described below by taking the communication system 30 composed of the electronic device 100, the smart watch 201, and the cloud server 300 in the communication system 10 as an example.

Referring to fig. 3, fig. 3 illustrates a schematic structural diagram of the communication system 30.

As shown in fig. 3, the smart watch 201 may include a data (1) collection module 310, a data (2) collection module 311, a data (1) encapsulation module 312, and a data (2) encapsulation module 313. Wherein the data (1) acquisition module 310 may be configured to acquire the data (1). The data (2) acquisition module 311 may be used to acquire data (2). As can be appreciated, the smart watch 201 has hardware means to collect data (1) and data (2). For example, where data (1) is heart rate, data (1) acquisition module 310 may include a heart rate monitoring device.

Not limited to the data (1) acquisition module 310 and the data (2) acquisition module 311, the smart watch 201 may further include more or less data acquisition modules.

The data (1) encapsulation module 312 may be configured to encapsulate the collected data (1) according to a data encapsulation protocol agreed between the smart watch 201 and the electronic device 100.

The data (2) encapsulation module 313 may be configured to encapsulate the collected data (2) according to a data encapsulation protocol agreed between the smart watch 201 and the electronic device 100.

The data encapsulation protocol for encapsulating data (1) and data (2) described above may determine the meaning represented by each field in the encapsulated data. The data encapsulation protocols used to encapsulate data (1) and data (2) may be the same or different.

Illustratively, the data (1) is heart rate, and the data (2) is pressure. Data (1) acquisition module 310 acquires a heart rate of 81 for the user. The data (2) acquisition module 311 acquires a user pressure of 52. The data (1) encapsulation module 312 may encapsulate the heart rate data. The packaged heart rate data may include "0181". The data (2) encapsulation module 313 may encapsulate the pressure data. The packaged pressure data may include "0152".

The smart watch 201 may send the encapsulated data (1) and data (2) to the electronic device 100.

It is understood that the smart watch 201 also includes a communication module (e.g., a bluetooth communication module). The data (1) encapsulation module 312 and the data (2) encapsulation module 313 may transmit the encapsulated data to the communication module in the smart watch 201. For example, a bluetooth communication connection is established between the smart watch 201 and the electronic device 100. The bluetooth communication module in the smart watch 201 may send the encapsulated data (1) and data (2) to the electronic device 100 according to a bluetooth communication protocol. The electronic device 100 may also include a communication module. The communication module in the electronic device 100 may receive the data sent from the smart watch 201 and transmit the data sent from the smart watch 201 to a corresponding application (e.g., an exercise health APP). In order to more clearly reflect the processing procedure of the data, the embodiment of the present application simplifies the transmission procedure of the data in the communication system 30.

The electronic device 100 may include an exercise health APP. Not limited to the exercise health APP, the electronic device 100 may also include other device management APPs for managing the data collection device. In the following embodiments of the present application, exercise health APP is specifically taken as an example for description.

The exercise health APP may include a device management module 314, one or more data storage and cloud synchronization modules, one or more data computation modules, and one or more business implementation modules.

The device management module 314 may include one or more data decapsulation modules. For example, the data (1) decapsulation module 314A and the data (2) decapsulation module 314B. The data (1) decapsulation module 314A may be configured to decapsulate the encapsulated data (1) according to a data encapsulation protocol agreed between the smart watch 201 and the electronic device 100. The data (2) decapsulation module 314B may be configured to decapsulate the encapsulated data (2) according to a data encapsulation protocol agreed between the smart watch 201 and the electronic device 100.

For example, the data (1) decapsulation module 314A may decapsulate the encapsulated heart rate data "0181" to obtain the following heart rate data "data type: heart rate, data value 81". Wherein, the "data type: the heart rate "may be determined by the data (1) decapsulation module 314A from the first 2 bits" 01 "of" 0181". The "data value 81" may be determined by the data (1) decapsulation module 314A according to the last 2 bits "81" of "0181".

The data (2) decapsulation module 314B may perform decapsulation processing on the encapsulated pressure data "0152" to obtain the following pressure data "data type: pressure, data value 52". Wherein, the "data type: pressure "may be determined by the data (2) decapsulation module 314B from the first 2 bits" 01 "of" 0152". The "data value 52" may be determined by the data (2) decapsulation module 314B based on the last 2 bits "52" of "0152".

It can be seen that the exercise health APP cannot decapsulate the encapsulated heart rate data and the encapsulated pressure data through the same data decapsulation module, otherwise, the meaning of the data content "01" cannot be determined.

It can be understood that, under the condition that data encapsulation protocols used by data acquisition devices such as the smart watch 201 to encapsulate different data are different, the same data content in different data may represent different meanings, and the exercise health APP in the electronic device 100 needs to decapsulate data according to different data encapsulation protocols, so as to determine the meaning represented by the received data.

The device management module 314 may also include other modules for managing exercise health data collection devices such as the smart watch 201, without being limited to the data encapsulation module.

The data storage and cloud synchronization module in the exercise health APP may include a data (1) storage and cloud synchronization module 316, a data (2) storage and cloud synchronization module 317. The data (1) storage and cloud synchronization module 316 may be configured to store the data (1) obtained after the data (1) is decapsulated by the data (1) decapsulation module 314A, and upload the data (1) to the cloud server 300. The data (2) storage and cloud synchronization module 317 may be configured to store the data (2) obtained after the data (2) decapsulation module 314B decapsulates the data (2), and upload the data (2) to the cloud server 300.

The data calculation module in the exercise health APP may include a data (1) calculation module 318, a data (2) calculation module 319. The data (1) calculation module 318 may obtain the data (1) from the data (1) storage and cloud synchronization module 316, and perform one or more of the following calculation processes on the data (1): determining a mean value, determining a range of variation, determining a maximum value, determining a minimum value, determining a sum, determining a number of counts of the data (1) over a period of time. The data (2) calculation module 319 may obtain the data (2) from the data (2) storage and cloud synchronization module 317 and perform calculation processing on the data (2).

A service implementation module may be used to implement a service. The business can represent the service which the sports health APP can provide for the user. The business implementation module in the exercise health APP may include a business a implementation module 320 and a business B implementation module 321. For example, the business a implementation module may be used to present heart rate related data and stress related data. The business B implementation module may be operable to present a recommendation to maintain physical fitness determined from the heart rate related data and the stress related data. Then, both business a implementation module 320 and business B implementation module 321 may obtain heart rate related data from data (1) calculation module 318 and pressure related data from data (2) calculation module 319.

In some embodiments, one or more data opening modules (not shown in fig. 3) may also be included in the exercise health APP. For example, a data (1) open module and a data (2) open module. The data opening module can be used for providing an opening interface for obtaining corresponding data for the three-party APP.

The cloud server 300 may include a data (1) storage module 322 and a data (2) storage module 323. The data (1) storage module 322 may be used to store data (1). The data (2) storage module 323 may be used to store data (2). The exercise health APP can upload the data (1) and the data (2) to the cloud server 300 according to a data encapsulation protocol agreed with the cloud server 300. Further, the cloud server 300 may determine the meaning represented by the received data according to a data encapsulation protocol agreed by the exercise health APP and the cloud server 300, and store the meaning.

As can be seen from the communication system 30 shown in fig. 3, since different types of data in the smart watch 201 may be encapsulated according to different data encapsulation protocols, and multiple data acquisition devices such as the smart watch 201 may encapsulate respective acquired data according to different data encapsulation protocols, the exercise health APP in the electronic device 100 needs to use different data encapsulation protocols to identify the meaning represented by different data. That is, the motion health APP needs to include a module for managing data encapsulated by different data encapsulation protocols. Then, in a case where a new type of data is delivered to the electronic device 100 for display, and the cloud server 300 stores and opens the three-party APP, a developer of the exercise health APP needs to develop a code for processing data, such as identification data, analysis data, presentation data, and open data, for the new type of data. The cloud server 300 and the third party APP also need to add a code for processing the newly added type of data according to a data encapsulation protocol adopted by the newly added type of data.

It can be seen that, when a new type of data access data display device, a cloud server, and a three-party APP are added to the processing method, a plurality of developers are required to modify and adapt the code for processing the data. This makes developers work heavy and data access inefficient.

The embodiment of the application provides a data processing method. In the method, the data acquisition equipment can report the data A to the data display equipment according to the data type definition rule in the data dictionary. The data display device may determine the specific content of the received data a according to the data type definition rules in the data dictionary, and analyze the data a according to the data processing rules in the data dictionary. The data display device can display the data A and an analysis result thereof, and can also upload the data A to a cloud server and open the data A to a three-party APP. The cloud server may determine the specific content of the received data a according to the data type definition rule in the data dictionary, and store the specific content. The three-party APP can determine the specific content of the received data A according to the data type definition rule in the data dictionary, and the data A is utilized to realize the required service of the three-party APP.

The data a may be exercise health data, family status data, or the like. The embodiment of the present application does not limit the specific type of the data a.

The rules of the data dictionary described above (e.g., data type definition rules, data processing rules, etc.) may be applicable to a variety of different types of data. It can be seen that, by using the rule of the data dictionary, when one type of data is newly added, the newly added type of data is accessed into the data display device, the cloud server, the three-party APP, and the data display device analyzes and displays the newly added type of data, and the codes for processing the data can be reused for processing the existing type of data. This can reduce the workload of developers and improve the efficiency of data access.

In order to facilitate understanding of the data processing method provided in the present application, a concept of the data dictionary related to the present application is described below.

A data dictionary refers to the definition and description of data items, data structures, data stores, processing logic of data. The contents contained in the data dictionary may refer to the contents shown in table 1 below.

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TABLE 1

The data dictionary may include data type definition rules and data processing rules.

The data type definition rule may contain the following data items in the data type definition in table 1 above: type ID, subType, name, description, type, sendivityLevel, validaePolicies, displayPolicies.

Where the format of data item typeID may be 00100001, for example, the first 3 bits may identify the packet of the data type, and the last 5 bits may be used to ensure that typeID has global uniqueness. Therefore, the data display equipment, the cloud server and the three-party APP can determine the type of the data according to the type identification of the data. The format of the data item typeID is not limited in the embodiments of the present application.

The data item sublType is an optional data item. In some embodiments, multiple subtypes may also be partitioned under one type of data. The data corresponding to the plurality of subtypes may have a data subtype identification. For example, the data of the sports record may include a plurality of subtypes of data: running records, swimming records, mountain climbing records, riding records, and the like.

The data item name may be an english string. For example, the name of the SLEEP data may be "SLEEP _ RECORD". The data item name may be used for a unique access identification in the code.

The data item type may include a single sample data category, a sequential sample data category, and so on. The single-sample data class may indicate that data is sampled once to determine a data value for one class. For example, the data acquisition device may obtain a heart rate value for each acquisition of heart rate data. The above-mentioned acquiring a heart rate may mean performing a heart rate acquisition at one moment. The single sample data class may also be referred to as single point data. The sequential sample data categories may indicate that data is sampled once to determine data values for multiple categories. For example, the data acquisition device may acquire data recorded each time a run is performed, and may obtain data values of multiple categories, such as a running speed average, a running mileage, and a consumed calorie. The collecting of the one-time running record may indicate collecting data related to running during a period from the start of running to the end of running.

The data item sensivitylevel may be used to determine the sensitivity level of the data. The sensitivity level may be defined in terms of how much data is revealed or abused that may be of concern to individuals, organizations or the public. For example, if one type of data is compromised or abused, which may have an irrecoverable or catastrophic adverse effect on the individual, organization, or public, the sendivitylevel for this type of data may be 4. A sendivitylevel for one type of data may be 3 if the one type of data is compromised or misused, which may have a significant adverse impact on the individual, organization, or public. A sendivitylevel for one type of data may be 2 if the data is compromised or abused, which may have a more serious adverse effect on the individual, organization, or public. A sendivitylevel for one type of data may be 1 if the disclosure or abuse of that type of data may adversely affect a limited degree to an individual, organization, or the public. The sendivitylevel for one type of data may be 0 if the adverse effects that the one type of data is compromised or abused may have on the individual, organization, or public are negligible. The specific value of sendivitylevel is not limited in the embodiment of the application.

The data item validatepolocies is an optional data item. The data item validateplaicies can be used to check the plausibility of the data acquisition device. For example, the validatepolocines of the body temperature data may be body temperature ≧ 34 and body temperature ≦ 42. If the device management APP for managing the data acquisition device receives body temperature data with a value of 45, the APP may determine that the body temperature data is abnormal data. The device management APP for managing the data acquisition device may process (e.g., delete) the abnormal data to reduce the instances in which the abnormal data is presented to the user.

The data item displayPolicies may be used to determine the display policy of the data. The value list of displayPolicies may include a display form and a display position displayPosition.

For example, if displayForm of one type of data is 1, the data display device may display the sampling value of this type of data in the form of a line graph. If the displayForm of one type of data is 2, the data display device may display the sampling values of the one type of data in the form of a histogram. If the displayForm of one type of data is 3, the data display apparatus may display the sampling value of this type of data in the form of a pie chart. If the displayForm of one type of data is 4, the data display device may display the sampling value of the one type of data using a radar chart. If the displayForm of one type of data is 5, the data display device may display the sampling value of the one type of data in the form of a scatter diagram.

If the displayPosition of one type of data is Left, the data display device may display the sampled value of this type of data with a display form a (e.g., a line graph) on the Left side of the user interface. If the displayPosition of one type of data is Right, the data display apparatus may display the sample value of this type of data having the display form a on the Right side of the user interface. If the displayPosition of one type of data is Top, the data display apparatus may display the sample value of this type of data with display form a on Top of the user interface. If the displayPosition of one type of data is Bottom, the data display apparatus may display the sample value of this type of data in display form a at the Bottom of the user interface.

Not limited to the above-mentioned displayforms and displaypositions, the data dictionary may further include more displayforms and displaypositions. The embodiment of the application does not limit the values of displayForm and displayPosition. The data dictionary may also represent different displayforms and different displaypositions by other data, letters, etc.

The values of the displayForm and the displayPosition are merely exemplary in the present application and should not be limited to the present application.

In some embodiments, displayPolicies may include one of displayForm, displayPosition. Optionally, the display policies are not limited to displayForm and displayPosition, and the displayPolicies may further include more rules for indicating the data display device to display data, such as an alignment manner.

In some embodiments, in addition to the display form and the display position for displaying the sampling values of one type of data in a period of time, the display policy displayPolicies may further include a display form and a display position for displaying statistical data (such as a maximum value, a minimum value, an average value, and the like) of the one type of data.

The data type definition rules may also contain a list of data item fields, fields. One or more fields may be included in a field list for one type of data. For example, a single point data heart rate field list may contain one field, namely the heart rate. The list of fields for the multipoint data blood pressure may contain two fields, systolic and diastolic pressures. The multi-point data can indicate that a data acquisition device can acquire data of multiple types at one time.

The data processing rules may contain other data items than those contained in table 1 in the data type definition rules. For example, data items in field definitions and data items in statistical policy definitions.

Wherein a field in the field list fields may have the data items contained in the field definitions in table 1: fieldType, fieldName, fieldDescription, format, unit (cn), unit (en), fieldOptional, mergePolicy, dataSourcePriority, mergePolicySameSource, statPolicies. That is, the data items contained in the field definitions in table 1 may describe a field in the field list fields from different dimensions.

The data item fieldType may be used to identify different types of fields under one type of data. The format of the fieldType of one field may be 00100001001, the first 8 bits may be the type id of the data of the type to which the field belongs, and the last 3 bits may be used to ensure that the fieldType has uniqueness in the fields contained in the data corresponding to the type id.

The data item fieldame may be an english string. For example, the fieldName for body temperature may be "body temperature".

The data entry fieldoperational may be used to indicate whether a field is optional. For example, a value of "M" for the data item fieldoOptional may indicate that a field is mandatory. A value of "O" for the data item fieldop may indicate that a field is optional. When one type of data is defined according to the rules of the data dictionary, the necessary fields contained in the one type of data must be defined.

The data item mergePolicy may be used to determine a policy for processing the same type of data collected at the same time from multiple data collection devices. I.e. a multi-source fusion strategy. The multi-SOURCE fusion policy may include Maximum (MAX), minimum (MIN), NEW (NEW), OLD (OLD), and per-data-SOURCE PRIORITY (SOURCE _ PRIORITY). The data source may represent a source of data, and a data collection device.

The data item dataSourcePriority is an optional data item that may be used to determine the priority of the data source. The data entry dataSourcePriority only needs to be defined when the value of the aforementioned data entry mergePolicy is SOURCE _ PRIORITY.

The data item mergepolicysameSource may be used to determine a policy for processing the same type of data collected from one data collection device. I.e., a homologous fusion strategy. For example, in a scenario where the smart watch 201 determines whether the user is asleep at time a, the smart watch 201 needs to utilize a plurality of sleep-related data monitored prior to time a in order to determine whether the user is asleep at time a. That is, in a case where the data acquisition device determines that one type of data cannot be acquired immediately to obtain an immediate result, but needs to process a plurality of data acquired in a previous period of time to obtain a result, the data display device may determine a method for processing the plurality of data acquired in the previous period of time by using the same-source fusion policy. The homologous fusion strategy may include taking a Maximum (MAX), taking a Minimum (MIN), taking a NEW value (NEW), taking an OLD value (OLD).

The data item statPolicies may represent a list of statistical policies for the field. One or more statistical policies may be included in the statistical policy list of a field. For example, a statistical strategy to calculate a maximum, a statistical strategy to calculate a minimum, a statistical strategy to calculate an average, a statistical strategy to calculate a sum, and so on.

Each statistical policy may have data items contained in the statistical policy definition in table 1: statType, statFieldname, statFormat, statPolixy. Wherein:

the data item statType can be used to identify the statistics type of a field. The format of the data item statType can refer to the data format of the aforementioned data item fieldType.

The data item statPolicy may be used to determine the statistical strategy of a field. The statistical strategies may include calculating a Maximum (MAX), calculating a Minimum (MIN), calculating a mean (AVG), summing (SUM), counting (COUNT), calculating a variance (SD), taking a new value (LAST).

The embodiment of the present application does not limit the names of the data items in the data dictionary. Not limited to the data items listed in table 1 above, more or fewer data items may be included in the data dictionary.

The rules for providing a uniform definition for different types of data may be other names, not limited to the above-mentioned digital dictionary. The embodiments of the present application do not limit this.

Different types of data can be defined by metadata according to the data dictionary shown in table 1. Metadata corresponding to one type of data can be used to determine values of various data items of the one type of data. Then, metadata corresponding to different types of data defined by metadata in the data dictionary may have the same or similar data structures. Having the same data structure for metadata corresponding to different types of data may indicate that the kinds of data items included in the metadata are the same. The metadata corresponding to different types of data are similar, and can represent the metadata, wherein some metadata comprise optional data items in the data dictionary, and some metadata do not comprise optional data items in the data dictionary.

Since the metadata corresponding to different types of data may have the same or similar data structure, the code for calculating and presenting the newly added type of data in the device management APP (e.g., exercise health APP) for managing the data collection device may reuse the code of the existing type of data. Such as codes for performing data fusion and data statistics, etc. This can reduce the workload of developers and improve the efficiency of data access.

Based on the data dictionary, a data processing method provided in the embodiment of the present application is described here by taking the communication system 40 composed of the electronic device 100, the smart watch 201, and the cloud server 300 in the communication system 10 as an example.

Referring to fig. 4, fig. 4 illustrates a schematic structural diagram of the communication system 40.

(1) The data collected by the smart watch 201 is accessed to the electronic device 100.

As shown in fig. 4, the smart watch 201 may include a data (1) acquisition module 410, a data (2) acquisition module 411, and a data reporting module 412. The data (1) acquisition module 410 and the data (2) acquisition module 411 may refer to the description of the communication system 30. The data reporting module 412 may be configured to report the data (1) to the exercise health APP in the electronic device 100 according to a data type definition rule included in the metadata corresponding to the data (1), and report the data (2) to the exercise health APP in the electronic device 100 according to a data type definition rule included in the metadata corresponding to the data (2).

In a possible implementation manner, the smart watch 201 may write the data type definition rule included in the metadata corresponding to the data (1) and the data type definition rule included in the metadata corresponding to the data (2) before shipping. Optionally, the data type definition rule adapted to the data (1) and the data (2) may also be written into the smart watch 201 through software update in the smart watch 201 after the smart watch 201 leaves a factory.

When the data (1) is collected, the smart watch 201 may determine the data type definition rule adapted to the data (1). The smart watch 201 may report the data (1) to the exercise health APP in the electronic device 100 through the data reporting module 412 according to the data type definition rule adapted to the data (1).

(2) The electronic device 100 processes data of the data acquisition device.

The electronic device 100 may include an exercise health APP. The exercise health APP may include a data management module 413, a data dictionary 414, a service a implementation module 415, and a service B implementation module 416. The data management module 413 may obtain the data (1) and the data (2) reported by the data reporting module 412 in the smart watch 201. It can be understood that, in the process of transmitting the data (1) and the data (2) from the data reporting module 412 to the data management module 413, the data (1) and the data (2) are further processed by the smart watch 201 and other modules (such as a bluetooth communication module, etc.) in the electronic device 100. In order to more clearly reflect the processing procedure of the data, the embodiment of the present application simplifies the transmission procedure of the data in the communication system 40. The embodiment of the present application does not limit the specific method for transmitting the data (1) and the data (2) from the data reporting module 412 to the data management module 413 and from the data management module 413 to the data storage module 417 in the cloud server 300.

Data dictionary 414 may contain a configuration file for data (1) and a configuration file for data (2). The configuration file for one type of data may follow the definition in the metadata corresponding to this type of data. I.e. the profile of the data (1) may be determined from the corresponding metadata of the data (1). The configuration file of the data (2) may be determined according to metadata corresponding to the data (2). The configuration file of one type of data can be used for the device management APP to identify, process, synchronize cloud and open the received data of the type to the three-party APP.

When receiving the data (1) and the data (2) from the data reporting module 412, the data management module 413 may obtain the configuration file of the data (1) and the configuration file of the data (2) from the data dictionary 414. The data (1) reported by the data reporting module 412 includes a data item typeID of the data (1), and the data (2) includes a data item typeID of the data (2). The data management module 413 may acquire the profile of the data (1) from the data dictionary 414 according to the data item typeID of the data (1), and acquire the profile of the data (2) from the data dictionary 414 according to the data item typeID of the data (2).

The data management module 413 may identify the specific contents of the data (1) and the data (2) according to the data type definition rule in the profile of (1) and the profile of the data (2). According to the data processing rule in the configuration file of (1) and the configuration file of data (2), the data management module 413 may perform calculation processing such as data fusion and data statistics on the data (1) and the data (2).

As can be seen from table 1, the data processing rules in the data dictionary may include data fusion rules and data statistics rules. The rules for data fusion described above may include data items mergePolicy, dataSourcePriority, mergepolicysameSource. The rules of the above data statistics may comprise the data item statPolicy.

(a) Data fusion

In a possible implementation manner, the data management module 413 may first determine whether a data acquisition device other than the smart watch 201 reports the data (1), and the data acquisition devices and the smart watch 201 have the same data (1) acquisition time. If the data management module 413 only receives the data (1) collected by the smart watch 201, the data management module 413 may store the data (1) collected by the smart watch 201.

If the data management module 413 receives a plurality of data (1) acquired by a plurality of data acquisition devices such as the smart watch 201 at the time a, the data management module 413 may determine which data (1) is used as the accurate data at the time a in the plurality of data (1) according to the data item mergePolicy of the multi-source fusion policy in the configuration file of the data (1).

For example, in the case where the data item mergePolicy is NEW in the configuration file of the data (1), the data management module 413 may use the data (1) with the latest writing time among the plurality of data (1) as the merged data, that is, the accurate data of the time a. The writing time may be a time for writing data into a memory module of the electronic device 100.

For another example, in a case where the data item mergePolicy is an OLD in the configuration file of the data (1), the data management module 413 may use the data (1) with the oldest writing time among the plurality of data (1) as the merged data.

For another example, when the data item mergePolicy in the configuration file of the data (1) is MAX, the data management module 413 may use the data (1) with the largest value among the plurality of data (1) as the merged data.

For another example, in a case where the data item mergePolicy in the configuration file of the data (1) is MIN, the data management module 413 may use the data (1) having the smallest value among the plurality of data (1) as the merged data.

For another example, in a case that the data item mergePolicy in the configuration file of the data (1) is SOURCE _ PRIORITY, the data management module 413 may use the data (1) acquired by the device with the highest device PRIORITY in the plurality of data acquisition devices such as the smart watch 201 as the merged data.

Wherein, in the case that the data item mergePolicy is SOURCE _ PRIORITY, the data item dataSourcePriority is included in the configuration file of the data (1). DataSourcePriority may be used to determine device priority.

In one possible implementation, the device priority determined by the dataSourcePriority is a priority determined according to a category of the data acquisition device. For example, when blood pressure data is collected, the priority of the sphygmomanometer is higher than the priority of the smart watch. The data management module 413 may determine the types of the data acquisition devices acquiring the data (1) at the time a, and select the data (1) acquired by the data acquisition device with the highest type priority according to the device priority determined by the dataSourcePriority. If there are multiple data acquisition devices that acquire data (1) at time a, and all of the multiple data acquisition devices are the data acquisition devices with the highest category priority, the data management module 413 may select one of the data (1) acquired by the multiple data acquisition devices with the highest category priority as the fused data in combination with other fusion policies (such as MAX, MIN, NEW, OLD, and the like).

In one possible implementation, the device priority determined by the dataSourcePriority may include two levels of priority: the priority determined according to the category of the data acquisition equipment and the priority determined according to the model of the data acquisition equipment. The priority determined according to the category of the data collecting apparatus described above can refer to the description of the foregoing embodiment. The priority determined according to the model of the data acquisition device may be used to determine the priority of each model of data acquisition device. For example, when collecting blood pressure data, data collection devices classified as sphygmomanometers have a plurality of models: a type A sphygmomanometer, a type B sphygmomanometer and the like. The priority of the model A sphygmomanometer is higher than that of the model B sphygmomanometer. Then, the data management module 413 may first select the data (1) acquired by the data acquisition device with the highest class priority from the plurality of data acquisition devices acquiring the data (1) at the time a, using the priority determined according to the class of the data acquisition device. Further, if there are a plurality of data acquisition devices with the highest category priority, the data management module 413 may determine the types of the plurality of data acquisition devices with the highest category priority, and select the data (1) acquired by the data acquisition device with the highest type priority according to the priority determined by the types of the data acquisition devices.

In one possible implementation, the device priority determined by the dataSourcePriority may only include a priority determined according to a model of the data acquisition device. The data management module 413 may determine the models of the multiple data acquisition devices acquiring the data (1) at the time a, and select the data (1) acquired by the data acquisition device with the highest model priority according to the device priority determined by the dataSourcePriority.

The data management module 413 may perform data fusion on the data (2) by referring to the above description of performing data fusion on the data (1). And will not be described in detail herein.

The multi-source fusion strategy can reduce the situation that data conflict is caused when a plurality of data acquisition devices acquire data of the same type at the same time. Not limited to the above-listed multi-source fusion strategies, the data dictionary may also contain more multi-source fusion strategies.

In some embodiments, in a case where the data management module 413 receives a plurality of data of the same type collected from one data collection device, the data management module 413 may perform data fusion on the plurality of data of the same type according to the data item mergePolicySameSource of the same source fusion policy in the configuration file of the data of the type. The method for performing homologous fusion on data by the data management module 413 may refer to the above description of performing multisource fusion on data.

(b) Data statistics

In one possible implementation, the data management module 413 may perform data statistics on a plurality of data (1) over a period of time according to a data item statPolicy of a data statistics policy in a configuration file of the data (1). The period of time may be, for example, one hour, one day, etc. The length of the period of time is not limited in the embodiments of the present application.

In the case that the data management module 413 only receives the data (1) collected by the smart watch 201, the data (1) in the period of time may be the data (1) collected by the smart watch 201 in the period of time. When the data management module 413 receives the data (1) acquired by the plurality of data acquisition devices such as the smart watch 201, the plurality of data (1) within the period of time may be the plurality of data (1) acquired within the period of time and subjected to the multi-source fusion processing.

For example, in a case where the data item statPolicy is AVG in the profile of the data (1), the data management module 413 may calculate an average value of a plurality of data (1) over the above period of time.

For another example, in the case where the data item statPolicy is SUM in the configuration file of the data (1), the data management module 413 may calculate the SUM of the plurality of data (1) within the period of time.

For another example, in a case where the data item statPolicy in the configuration file of the data (1) is MAX, the data management module 413 may determine the maximum value of the plurality of data (1) in the period of time.

For another example, in the case where the data item statPolicy is MIN in the profile of the data (1), the data management module 413 may determine the minimum value of the plurality of data (1) within the period of time.

For another example, in the case where the data item statPolicy is SD in the configuration file of the data (1), the data management module 413 may calculate the variance of the plurality of data (1) over the above-described period of time.

For another example, in the case where the data item statPolicy is COUNT in the configuration file of the data (1), the data management module 413 may calculate the number of data of the plurality of data (1) within the above-described period of time.

For another example, in the case where the data item statPolicy is LAST in the configuration file of the data (1), the data management module 413 may determine the latest values of the plurality of data (1) within the period of time. The latest value may be the data acquired the latest time within a period of time.

Not limited to the above listed data statistics policies, the data dictionary may also contain more data statistics policies.

The data management module 413 performs data statistics on the data according to the rule of the data statistics, which can facilitate the service implementation module to realize the requirement of displaying various types of statistical data. For example, the average, sum, and the like of the data are presented, and the data are presented in the form of a line graph, a bar graph, and the like.

The services that the service a implementation module 415 and the service B implementation module 416 need to implement may refer to the description in the communication system 30 shown in fig. 3. Both the service a implementation module 415 and the service B implementation module 416 can obtain data such as data (1), data (2), statistical results of the data (1) under various data statistical policies, statistical results of the data (2) under various data statistical policies, and the like from the data management module 413.

Illustratively, the service a implementation module 415 may be configured to present data related to data (1) and data related to data (2). The service a implementation module may determine the display policy of data (1) from the profile of data (1) (e.g., displayed in a line graph on top of the user interface) and determine the display policy of data (2) from the profile of data (2) (e.g., displayed in a bar graph on top of the user interface). The service a implementation module 415 may display the data (1) acquired from the data management module 413 according to the display policy of the data (1), and display the data (2) acquired from the data management module 413 according to the display policy of the data (2).

In addition, if a display policy of the statistical data of the data (1) is defined in the configuration file of the data (1) (for example, an average value is displayed on the lower side of the line graph of the user interface data (1)), the service a implementation module may further obtain each item of statistical data of the data (1) from the data management module 413 and display the item of statistical data according to the display policy of the statistical data of the data (1). The method for displaying the statistical data of the data (2) by the service a implementation module can refer to the method for displaying the statistical data of the data (1). And will not be described in detail herein.

It will be appreciated that the user interface for displaying data related to data (1) described above is a different user interface than the user interface for displaying data related to data (2).

(3) The electronic device 100 uploads the data collected by the data collection device to the cloud server 300 and opens the data to the three-party APP.

In some embodiments, the data management module 413 may send the data (1) to the cloud server 300 according to the data type definition rule in the configuration file of the data (1). The cloud server 300 may include a data storage module 417. When receiving the data (1), the cloud server 300 may determine the specific content of the data (1) according to the data type definition rule included in the metadata corresponding to the data (1), and store the data (1) in the data storage module 417.

The process of the cloud server 300 receiving the data (2) and storing the data (2) to the data storage module 417 may refer to the introduction of the cloud server 300 storing the data (1) to the data storage module 417.

In some embodiments, data management module 413 may open data (1) to a three-party APP according to data type definition rules in a configuration file for data (1). The three-party APP can determine the specific content of the data (1) according to the data type definition rule contained in the metadata corresponding to the data (1), and the data (1) is utilized to realize the own requirement service.

As can be seen from the foregoing embodiments, in the case that different types of data are all metadata-defined according to the rules of the data dictionary, the metadata corresponding to the different types of data may have the same or similar data structure, and the data items typeID of the different types of data are globally unique. Then, interfaces for data interaction between the data acquisition device and the electronic device 100 in the process of accessing different types of data to the device management APP in the electronic device 100 may be shared, interfaces for data interaction between the electronic device 100 and the cloud server 300 in the process of cloud synchronization for different types of data may be shared, and an open interface provided by the device management APP in the process of opening the different types of data to the three-party APP may also be shared. When a type of data is newly added, the newly added type of data may be accessed to the electronic device 100 and the cloud server 300, and the related interfaces opened to the third party APP may be the same as the existing type of data accessed to the electronic device 100 and the cloud server 300, and the related interfaces opened to the third party APP. The existing type data is defined according to the rules of the data dictionary. That is, when the newly added type of data is accessed to the electronic device 100 and the cloud server 300 and is opened to the three-party APP, the developer may not separately develop an access interface suitable for the newly added type of data. This can reduce the workload of developers when new types of data are accessed, and improve the efficiency of data access.

In some embodiments, a profile of one or more types of data may be stored in cloud server 300. The profile for one type of data may be determined based on the metadata corresponding to that type of data. When data of the new type is generated, the cloud server 300 may transmit a configuration file of the data of the new type to the electronic device 100. A device management APP (e.g., an athletic health APP) in electronic device 100 may update the data dictionary with a profile for the new type of data. In this way, when receiving the newly added type of data acquired by the data acquisition device, the device management APP may determine the content of the newly added type of data by using the updated data dictionary, and perform processing such as calculation and display on the newly added type of data according to the configuration file of the newly added type of data.

In some embodiments, when there is a newly added type of data generated, the electronic device 100 may update the version of the device management APP in response to a user operation for updating the version of the device management APP. The data dictionary in the device management APP after the version update can contain the configuration file of the newly added type of data.

Taking the newly added body temperature data as an example, a data processing process of accessing the data acquired by the data acquisition device to the data display device and the cloud server and opening the data to the three-party APP is described below.

(1) And defining metadata corresponding to the body temperature data according to rules of the data dictionary.

The metadata corresponding to the body temperature data can be used for determining the values of various data items of the body temperature data. The metadata corresponding to the body temperature data can refer to the contents shown in table 2 below.

TABLE 2

The values of the data items in table 2 can refer to the description of the data dictionary in the foregoing embodiment. And will not be described in detail herein.

(2) And determining a configuration file of the body temperature data according to the metadata corresponding to the body temperature data.

The profile of body temperature data may include:

/>

it can be seen that the values of the data items of the body temperature data are defined in the configuration file of the body temperature data. Because the body temperature data is single-point data, only one field is contained in the field list fields in the data item field list in the configuration file of the body temperature data, namely the field with the field name "fieldame" being "body temperature" and the field data type identifier "fieldType" being "400011975". The configuration file of the body temperature data can also comprise a data fusion strategy and a statistical strategy for a field in the body temperature data. For example, the statistical policy list "statPolicies" in the configuration file includes four statistical policies: calculating the Average (AVG), calculating the Maximum (MAX), calculating the Minimum (MIN), counting (COUNT).

The configuration file of the body temperature data can be used for identifying the received body temperature data by the equipment management APP, and carrying out data fusion, data statistics and other processing on the body temperature data.

(3) And solidifying the data type definition rule in the configuration file of the body temperature data to the body temperature data acquisition equipment.

In a possible implementation manner, before the body temperature data acquisition device leaves the factory, a manufacturer of the body temperature data acquisition device may write the data type definition rule in the configuration file of the body temperature data into the body temperature data acquisition device. Optionally, the data type definition rule in the body temperature data configuration file may also be written into the body temperature data acquisition device when software is updated after the body temperature data acquisition device leaves a factory.

The data type definition rule may include data items: type ID, name, type, sendivityLevel, validaePolicies, displayPoliciy. Wherein, one or more of the data items name, type, sendivitylevel, validatepolicis and displaypolicy may not be written into the body temperature data acquisition device.

The data type definition rule may further include a data item field list fields. The manufacturer of the body temperature data acquisition device may also write one or more data items defined by fields in the configuration file of the body temperature data into the body temperature data acquisition device. Since the body temperature data is a single point of data, the body temperature data has only one field, namely the body temperature. The manufacturer of the body temperature data acquisition device may associate the data items in the field definitions as: fieldType, unit (en), write to body temperature data acquisition device. Then, the body temperature data acquisition device may report the body temperature data according to the data type definition rule, and report fields included in the body temperature data according to the data items in the field definitions.

(4) The body temperature data acquisition equipment reports the acquired body temperature data to the data display equipment according to the data type definition rule of the body temperature data.

When the body temperature data is acquired, the body temperature data acquisition equipment can describe the body temperature data according to the data type definition rule of the body temperature data and send the described data to the data display equipment. The data display device may be a device that establishes a binding relationship with the body temperature data acquisition device.

In a possible implementation manner, the described body temperature data may include both a type identifier type id and a field data type identifier fieldType and a sampling value of the field.

For example, the described body temperature data may be:

"typeID":400011

"fieldType":400011975

"start_time":1626836477471

"end_time":1626836477471

"value":36.0

it is to be understood that the above-mentioned "start _ time" and "end _ time" may respectively represent the start time and the end time of the one body temperature data acquisition. The body temperature data described by the body temperature data acquisition equipment can also comprise more data items. Such as name, type, sendivitylevel, validateplaticies, and the like.

In another possible implementation manner, since the body temperature data is single-point data, the body temperature data acquisition device may uniquely identify the body temperature data by only field data type identification fieldType of a field included in the body temperature data. That is, the described body temperature data may contain a field data type identifier fieldType and a sampling value of the field, but does not contain a type identifier type id.

For example, the described body temperature data may be:

"fieldType":400011975

"start_time":1626836477471

"end_time":1626836477471

"value":36.0

in the case where the data described by the data acquisition device is multipoint data, the data acquisition device may uniquely identify the data by the type identification type of the data and identify the different fields contained in the data by the field data type identification fieldType. For example, the blood pressure data is multipoint data. The blood pressure data described according to the rule of the data dictionary may contain a type identification type of the blood pressure data, a start time and an end time of the collection, a field data type identification fieldType of a field diastolic pressure of the blood pressure data, a sampling value of the field diastolic pressure, a field data type identification fieldType of a field systolic pressure of the blood pressure data, and a sampling value of the field systolic pressure.

(5) The data display equipment identifies the body temperature data reported by the body temperature data acquisition equipment by using the configuration file of the body temperature data, and carries out processing such as calculation, display and the like on the body temperature data.

Here, the data display device is taken as the electronic device 100, and the device management APP for managing the body temperature data acquisition device in the data display device is taken as an exercise health APP for example.

The electronic device 100 stores a configuration file of the body temperature data. When the electronic device 100 receives body temperature data reported by the body temperature data acquisition device, the exercise health APP in the electronic device 100 may identify specific content in the body temperature data by using a configuration file of the body temperature data.

For example, the exercise health APP may recognize that the data is body temperature data based on the data item "fieldType":400011975 in the received data. The exercise health APP can determine that the data with the fieldType of 400011975 is the body temperature data with the field name of body temperature according to the configuration file of the body temperature data.

In some embodiments, when the data acquisition device reports the acquired data to the data display device, the data acquisition device may also report the device identifier of the data acquisition device to the data display device. Each model of data acquisition device has a device identification that is globally unique. For example, the body temperature data collecting device of model a has a device identification 71. The body temperature data acquisition device of model B has a device identification 72. The blood pressure data collecting device of model C has a device identification 73. The embodiment of the present application does not limit the format of the device identifier of the data acquisition device.

After the exercise health APP identifies the specific content in the body temperature data, the body temperature data may be stored in a data storage module in the electronic device 100. For example, the storage format of the body temperature data in the data storage module of the electronic device 100 may refer to the contents shown in table 3 below:

Id	start_time	end_time	fieldType	value	device_id	sync_status
							1	1626836477471	1626836477471	400011975	36.0	71	0
2	1626836477481	1626836477481	400011975	36.2	71	0

TABLE 3

Wherein each row in table 3 may represent a record of body temperature data. A record of body temperature data may represent body temperature data acquired by a body temperature data acquisition device at a time. Id in table 3 may indicate the serial number of the record corresponding to the row in which it is located. Device _ id in table 3 may represent the device identification of the data collection device. The sync _ status in table 3 may represent the cloud synchronization status of the body temperature data. For example, a sync _ status of 0 may indicate that the body temperature data has not been uploaded to the cloud server. A sync _ status of 1 may indicate that the body temperature data has been uploaded to the server. The storage format of the body temperature data may also contain more or less contents, not limited to those listed in table 3. Such as data name, data unit, data sensitivity level, etc.

As can be seen from the foregoing embodiments, all data defined by metadata according to the rules of the data dictionary have globally unique type identifier typeID and have the same or similar data structure. Then, the exercise health APP can identify all data reported according to the rule of the data dictionary through the same data identification module. The code for implementing the data recognition module is a program for recognizing the data reported according to the rule of the data dictionary. The data identification module can be equivalent to an interface for data interaction between the data display device and the data acquisition device. When one type of data is newly added and the newly added type of data is reported according to the rule of the data dictionary, the newly added type of data can reuse the data interaction interface of the existing type of data in the reporting process. The developer only needs to define the configuration file of the newly added type of data according to the rules of the data dictionary, and does not need to additionally develop a data interaction interface suitable for the newly added type of data. Therefore, the workload of developers when the newly added type data is accessed into the data display equipment can be reduced, and the data access efficiency is improved.

In some embodiments, the configuration file of the body temperature data includes a data item checking rule set validatepediicies. The exercise health APP can check the body temperature data stored in the data storage module according to validaepolicies to judge whether the body temperature data is abnormal or not.

In some embodiments, the exercise health APP may determine data fusion and data statistics for the body temperature data according to a profile of the body temperature data.

For example, when it is determined that the multiple body temperature data stored in the data storage module have a multi-source conflict, the exercise health APP may perform data fusion on the multiple body temperature data having the multi-source conflict by using a data item multi-source fusion policy mergePolicy included in the configuration file of the body temperature data. The multiple body temperature data with the multi-source conflict can comprise body temperature data acquired at the same time by the body temperature data acquisition equipment of multiple models.

As known from the configuration file of the body temperature data, the mergePolicy is "SOURCE _ PRIORITY", that is, the fused data is determined according to the PRIORITY of the data acquisition equipment. The configuration file of the body temperature data contains the data item device priority. The exercise health APP can select body temperature data acquired by body temperature data acquisition equipment with the highest equipment priority from a plurality of body temperature data with multi-source conflict as fused data according to the dataSourcePriority. For example, the dataSourcePriority is [1,129,384,57,72,71]. The priority of the data source priority is determined according to the model of the data acquisition device. The device identification in array [1,129,384,57,72,71] may identify a particular model of data collection device. Wherein, the priority of the body temperature data acquisition equipment with the equipment identification 1 is the highest. The body temperature data acquisition device with device identification 71 has the lowest priority. If a plurality of body temperature data with multi-source conflict exist, the body temperature data are acquired by the body temperature data acquisition device with the device identification number 129 and the body temperature data acquisition device with the device identification number 71. Then, the exercise health APP may select the body temperature data acquired by the body temperature data acquisition device with the device identification 129 as the fused body temperature data.

In some embodiments, the priority of the data source priority is determined according to the category of the body temperature data acquisition device. The value of the dataSourcePriority may include a device class identifier. A device class identifier may identify a class of body temperature data collection devices. The exercise health APP can select the body temperature data acquired by the body temperature data acquisition equipment with the highest category priority as the fused body temperature data. The method for representing the device class identifier in the embodiment of the present application is not limited. For example, the device class identification may be represented by one or more of numeric, alphabetic, etc. characters.

The fused body temperature data can be used for data statistics, data display and other processing.

The configuration file of the body temperature data comprises four statistical strategies of MAX, MIN, AVG and COUNT. The exercise health APP can perform statistical processing corresponding to the four statistical strategies on the body temperature data within a period of time, and store the statistically processed body temperature data in the data storage module of the electronic device 100. For example, the storage format of the statistical body temperature data in the data storage module of the electronic device 100 may refer to the contents shown in table 4 below:

TABLE 4

Wherein each row in table 4 may represent a record of the statistical body temperature data. A record of the statistical body temperature data may represent a statistical value obtained by the exercise health APP performing a statistical analysis of the received body temperature data according to a statistical strategy over a period of time, such as a day. Id in table 4 may indicate the need for the record corresponding to the row in which it is located. The date in table 4 may indicate the time period during which the body temperature data for data statistics is acquired. For example, a date of 20210722 may represent data statistics for body temperature data acquired at a time of 2021 within 7 months and 22 days. Further contents of table 4 can be referred to the description of the previous embodiment.

In some embodiments, the exercise health APP may determine the display strategy for body temperature data with a profile of body temperature data. For example, in the configuration file of the body temperature data, the data item display policy is [1, top ], which may indicate that the body temperature data needs to be displayed in the form of a line graph and displayed at the top of the user interface. The exercise health APP may invoke the code that draws a line graph to draw a line graph of the body temperature data over time and display the line graph at the top of the user interface. Optionally, the exercise health APP may also display statistical body temperature data (e.g., maximum, minimum, etc.).

Fig. 5A to 5C are schematic diagrams illustrating a scene of the electronic device 100 displaying body temperature data and statistical body temperature data.

As shown in fig. 5A, electronic device 100 may display user interface 510. User interface 510 displays a page on which application icons are placed. The page may include a plurality of application icons. For example, a smart life application icon, an exercise health application icon 511, a YY exercise application icon 512, and a ZZ health icon 513. In response to a user operation, such as a touch operation, applied to the application icon, the electronic device 100 may open an application program corresponding to the application icon. It is understood that the exercise health APP corresponding to the exercise health APP icon 511 may be a device management APP for managing the body temperature data collecting device. The YY exercise APP corresponding to the YY exercise application icon and the ZZ health APP corresponding to the ZZ health application icon 513 can both be three-party APPs. In response to the user operation applied to the exercise health application icon 511, the electronic device 100 may display the user interface 520 shown in fig. 5B.

As shown in FIG. 5B, a plurality of cards may be included in user interface 520. One card may be used to present one type of data. For example, a heart rate card 521 may be used to present heart rate data. The body temperature card 522 may be used to present body temperature data. The pressure card 523 may be used to present pressure data. The athletic recording card 524 may be used to present athletic recording data. In response to a user operation, such as a touch operation, acting on one card, the electronic apparatus 100 may display more detailed contents of data corresponding to the one card. Such as the sampled value of the data over a period of time, statistical data of the data under different statistical strategies, etc. In response to user manipulation of the body temperature card 522, the electronic device 100 may display the user interface 530 shown in FIG. 5C.

As shown in fig. 5C, the user interface 530 may include a time options area 531, a body temperature data display area 532, a body temperature mean card 533, and a body temperature range card 534. The time option area 531 may include a plurality of time options. When a time option is in the selected state, the body temperature data in the time period corresponding to the time option can be displayed in the body temperature data display area 532 in the form of a line graph. For example, when the time option indicating 1 month and 15 days is in the selected state, a line graph of all body temperature data acquired by the body temperature data acquiring device on 1 month and 15 days may be displayed in the body temperature data display area 532. When the time option indicating 1 month is in the selected state, a line graph of all the body temperature data acquired by the body temperature data acquiring device in 1 month may be displayed in the body temperature data display area 532. In this way, the user can view the body temperature data over different time periods through different time options in the time option area 531.

Body temperature mean card 533 may be used to display a mean of body temperature data over a period of time (e.g., a day).

The body temperature range card 534 may be used to display a range of fluctuations in body temperature data over a period of time (e.g., over a day). The range over which the internal body temperature data fluctuates over a period of time can be determined from the minimum and maximum values of the internal body temperature data over the period of time.

The user interfaces shown in fig. 5A to 5C are only exemplary illustrations of displaying body temperature data on the data display device according to the embodiment of the present application, and should not be construed as limiting the present application.

If the heart rate data, the body temperature data, the pressure data and the exercise record data are all defined by metadata according to rules of a data dictionary, the body temperature data is used as newly-added type data, and the heart rate data, the pressure data and the exercise record data are used as existing type data, then codes for performing data fusion, data statistics (such as body temperature mean and body temperature range shown in fig. 5C) and data display (such as broken line graph in a body temperature data display area 532 shown in fig. 5C) on the body temperature data in the exercise health APP can all multiplex codes for processing the existing type data by the exercise health APP.

As can be seen from the foregoing embodiments, in the case that different types of data are metadata-defined according to rules of a data dictionary, codes used for performing data fusion (e.g., a multi-source fusion policy) on the different types of data in the exercise health APP may be multiplexed, codes used for performing data statistics (e.g., a statistical policy) on the different types of data may be multiplexed, and codes used for performing data presentation (e.g., line graph presentation data) on the different types of data may also be multiplexed. When one type of data is newly added and the newly added type of data is defined by metadata according to the rule of the data dictionary, codes for performing data fusion, data statistics and data display on the newly added type of data can all multiplex codes for processing the existing type of data in the exercise health APP. The developer can only modify the part (such as type identification typeID and the like) for identifying data in the code for processing the existing type of data in the exercise health APP into the content for identifying the newly added type of data, and the developer can develop the code suitable for processing the newly added type of data without modifying the code logic for processing the data. Therefore, the workload of developers when the newly added type data is accessed into the data display equipment can be reduced, and the data access efficiency is improved.

(6) And the data display equipment sends the body temperature data to the cloud server according to the data type definition rule of the body temperature data.

In some embodiments, the data display device may send the body temperature data that is not cloud-synchronized in the data storage module to the cloud server. The cloud server may be an application server of a device management APP for managing the body temperature data acquisition device. The cloud server can identify that the received data belongs to the body temperature data and specific content in the body temperature data according to a data type definition rule of the body temperature data.

After receiving the body temperature data reported by the body temperature data acquisition device, the data display device can associate the sampling value of the body temperature data with the name of the body temperature data identified according to the configuration file of the body temperature data, and then send the body temperature data to the cloud server. Therefore, the cloud server can directly store the received body temperature data, and does not need to identify whether the received data belongs to the body temperature data according to the data type definition rule of the body temperature data and then store the data.

In some embodiments, the data display device may also download the body temperature data from a cloud server. In the case where the data display device unloads the device management APP and downloads the device management APP again, only part of the body temperature data may be stored in the data display device. Then, the data display device may download the body temperature data from the cloud server that is present in the cloud server but not present in the data display device.

Referring to the introduction that different types of data defined by metadata according to the rules of the data dictionary are accessed into the data display device by the data acquisition device, when different types of data defined by metadata according to the rules of the data dictionary are accessed into the cloud server by the data display device, an interactive interface for uploading data can be shared, and when the data are downloaded from the cloud server to the data display device, an interactive interface for downloading data can be shared. Therefore, under the condition that the newly added type data is generated, developers do not need to separately develop an interactive interface suitable for transmitting the newly added type data between the data display equipment and the cloud server each time. The workload of developers can be reduced when the newly added type data is accessed into the cloud server, and the data access efficiency is improved.

(7) The data display equipment opens the body temperature data to the three-party APP according to the data type definition rule of the body temperature data.

In some embodiments, the three-party APP may request an open right to acquire body temperature data from a device management APP in the data display device, the device management APP being used to manage the body temperature data acquisition device. Under the condition that the open permission for acquiring the body temperature data is requested, the device management APP can provide an open interface of the body temperature data for the three-party APP. The device management APP can open the body temperature data to the three-party APP through the open interface of the body temperature data. The body temperature data opened to the three parties APP can be described according to data type definition rules of the body temperature data. The three-party APP can identify that the obtained data belongs to the body temperature data and the specific content of the body temperature data according to the data type definition rule of the body temperature data. Optionally, the data display device may also open the three-party APP after associating the name of the body temperature data in the configuration file of the body temperature data with the body temperature data sampling value. Therefore, the three-party APP can identify whether the acquired data belongs to the body temperature data or not without the need of identifying the body temperature data according to the configuration file.

In some embodiments, the data type definition rules in the three-party APP may contain different types of data. The different types of data may be defined by metadata according to rules of a data dictionary. Then the codes for identifying the different types of data in the three-party APP can be multiplexed, as can the codes for processing the different types of data. In this way, in the case of being generated from data of a new type, the code for identifying the data of the new type, the code for processing the data of the new type, may reuse the code in the three-party APP corresponding to the data of the existing type. The workload of developers of the three-party APP can be reduced when the newly-added data are accessed into the three-party APP, and the data access efficiency is improved.

Another communication system 60 provided in the embodiment of the present application will be described based on the above-mentioned processing procedure of the body temperature data.

As shown in fig. 6, the communication system 60 may include a body temperature data collecting device 610, the electronic device 100, and the cloud server 300.

Wherein:

the body temperature data acquisition device 610 may include a body temperature data acquisition module 611 and a data reporting module 612. The body temperature data collection module 611 is configured to collect body temperature data and send the body temperature data to the data reporting module 612. The data reporting module 612 writes the data type definition rule in the configuration file of the body temperature data. The data reporting module 612 may report the exercise health APP in the electronic device 100 according to the rule of the data dictionary.

The process of reporting the body temperature data by the data reporting module 612 according to the rule of the data dictionary may be a process of describing the body temperature data according to a data type definition rule in a configuration file of the body temperature data and sending the described body temperature data.

The electronic device 100 may include an exercise health APP and a three-party APP. The exercise health APP may be a device management APP for managing the body temperature data collection device 610. The exercise health APP may include a data calculation module 621, a data storage module 622, a data presentation module 623, a data opening module 624, and a data dictionary 625.

The data dictionary 625 may contain a configuration file of body temperature data. The exercise health APP may identify the body temperature data reported by the body temperature data acquisition device 610 according to the rules of the data dictionary by using the configuration file of the body temperature data in the data dictionary 625.

The data calculation module 621 may perform calculation processing such as data fusion and data statistics on the body temperature data according to the configuration file of the body temperature data.

The data storage module 622 may store body temperature data. The storage format of the body temperature data in the data storage module 622 can refer to the description of the foregoing embodiments.

The data display module 623 may be configured to display a plurality of sampling values of the body temperature data and a statistical value obtained by data statistics of the body temperature data. In some embodiments, the displayed body temperature data may be data obtained by data fusion performed by the data calculation module 621.

The data opening module 624 can be used for providing an open interface of body temperature data for three-party APP.

As can be seen from the foregoing embodiments, all data defined by metadata according to the rules of the data dictionary have globally unique type identification typeID and have the same or similar data structure. Then, not limited to the body temperature data, the exercise health APP may also correspondingly manage other data defined by metadata according to rules of the data dictionary through the data calculation module 621, the data storage module 622, the data presentation module 623, and the data opening module 624. That is, the data calculation module 621, the data storage module 622, the data presentation module 623 and the data opening module 624 may be multiplexed. When a new type of data is added and the new type of data is reported according to the rules of the data dictionary, developers do not need to additionally develop each module suitable for managing the new type of data.

The exercise health APP can open the body temperature data to the three-party APP with the permission of obtaining the body temperature data through the body temperature data open interface provided by the data open module 624. The body temperature data opened to the three-party APP can be obtained after being described according to a data type definition rule of the body temperature data. The described body temperature data may include a type identifier of the body temperature data and a sampling value of the body temperature data. The three-party APP can identify the obtained body temperature data according to the data type definition rule of the body temperature data, and the body temperature data is used for realizing the required service of the three-party APP. Optionally, the exercise health APP may also open a name of the body temperature data in the configuration file of the body temperature data to a three-party APP after associating the name with the body temperature data sampling value. Therefore, the three-party APP can identify whether the acquired data belongs to the body temperature data or not without the need of identifying the body temperature data according to the configuration file.

The exercise health APP can also perform cloud synchronization processing on the body temperature data. The exercise health APP can be described according to the data type definition rule of the body temperature data, and the described body temperature data is sent to the cloud server 300. The described body temperature data may include a type identifier of the body temperature data and a sampling value of the body temperature data. The cloud server 300 may identify and store the received body temperature data according to a data type definition rule of the body temperature data. Optionally, the exercise health APP may also associate the sampling value of the body temperature data with the name of the body temperature data identified according to the configuration file of the body temperature data, and then send the association result to the cloud server. Therefore, the cloud server can directly store the received body temperature data, and does not need to identify whether the received data belongs to the body temperature data according to the data type definition rule of the body temperature data and then store the data.

It can be seen that, with the rule of the data dictionary designed in the embodiment of the present application, in the case of adding one type of data, the data of the added type is accessed to the data display device, the cloud server, the three-party APP, and the data display device analyzes and displays the data of the added type, and the code for processing the data can be reused for processing the existing type of data. This can reduce the workload of developers and improve the efficiency of data access.

The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of data processing, the method comprising:

the method comprises the steps that first data are received by first equipment from first data acquisition equipment, the first data comprise first data identification and first sampling values of first type data, and the first sampling values conform to rules of a first configuration file, the first configuration file is defined according to first rules, the first configuration file comprises the first data identification, the first data identification is used for identifying the first type data, and the first data identification has uniqueness in the data identification defined according to the first rules;

and the first device identifies that the first data belongs to the first type of data according to the first data identifier and the first configuration file.

2. The method of claim 1, wherein the first rule is a rule of a data dictionary.

3. The method of claim 1 or 2, further comprising:

the first device receives second data from a second data acquisition device, wherein the second data comprises a second data identifier and a second sampling value of a second type of data and conforms to the rule of a second configuration file, the second configuration file is defined according to the first rule, the second configuration file comprises the second data identifier, the second data identifier is used for identifying the second type of data, and the second data identifier has uniqueness in the data identifier defined according to the first rule;

the first device identifies that the second data belongs to the second type of data according to the second data identifier and the second configuration file; wherein the procedure for identifying the first data in the first device is the same as the procedure for identifying the second data.

4. The method of any of claims 1-3, wherein the first sample value was acquired by the first data acquisition device at a first time, the method further comprising:

the first device receives M sampling values of the first type of data, wherein the M sampling values are respectively acquired by M data acquisition devices at the first time; m is a positive integer;

the first device determines that a data fusion policy of the first type of data is a first fusion policy from the first configuration file, and determines one sampling value from the first sampling value and the M sampling values according to the first fusion policy as a sampling value of the first type of data at the first time; the first fusion strategy is any one of the following: the method comprises the steps of taking a maximum value, taking a minimum value, taking a value with the earliest time for accessing the first equipment, taking a value with the latest time for accessing the first equipment, and taking a sampling value collected by the first data collection equipment and the equipment with the highest equipment priority in the M data collection equipment.

5. The method according to any one of claims 1-4, further comprising:

the first device determines, from the first configuration file, that the data statistical policy of the first type of data is a first statistical policy, where the first statistical policy includes one or more of: calculating a maximum value, a minimum value, a mean value, summation, variance and the number of sampling values, and determining the sampling value with the latest acquisition time;

and the first equipment performs data statistics on N sampling values of the first type of data within a first time period at the acquisition time according to the first statistical strategy, wherein N is a positive integer.

6. The method of any of claims 1-5, wherein the first device comprises a display device, wherein the first configuration file comprises a first display policy for a first type of data, and wherein the first display policy comprises one or more of: a first display form and a first display position; the method further comprises the following steps:

and the first equipment displays the received sampling value of the first type of data on a first user interface according to the first display strategy through the display device.

7. The method of claim 6, wherein the second configuration file comprises a second display policy for a second type of data, the second display policy being the same as the first display policy; the method further comprises the following steps:

the first equipment displays the received sampling value of the second type of data on a second user interface according to the first display strategy through the display device; wherein a procedure for causing the sample values of the first type of data to be displayed in accordance with the first display policy is the same as a procedure for causing the sample values of the second type of data to be displayed in accordance with the first display policy.

8. The method of any of claims 1-7, wherein the first profile contains first description information for the first type of data, the method further comprising:

the first device sends third data to a cloud server, wherein the third data comprises the first description information and the sampling value of the first type of data.

9. The method according to any one of claims 1-8, wherein a first application is installed in the first device, the first application having a right to obtain the first type of data, and the first configuration file contains first description information of the first type of data, the method further comprising:

the first device providing the fourth data to the first application in response to a request by the first application to obtain the first type of data; the fourth data includes the first description information and a sample value of the first type of data.

10. The method of any of claims 1-5, wherein the first device is a cloud server, the method further comprising:

and the cloud server sends fifth data to data display equipment, wherein the fifth data comprises the first data identification and the sampling value of the first type of data.

11. The method according to any one of claims 1-10, wherein the first data acquisition device is any one of: intelligence wrist-watch, intelligent bracelet, body fat balance, intelligent glasses, clinical thermometer, sphygmomanometer, heart rate monitoring facilities.

12. The method according to any one of claims 1 to 11, wherein the first type of data is any one of: walking data, running data, swimming data, riding data, sleeping data, weight data, pressure data, heart rate data, blood pressure data, body temperature data, blood oxygen data, blood glucose data.

13. A method of data processing, the method comprising:

the method comprises the steps that first data are acquired by first data acquisition equipment, the first data comprise a first data identifier and a first sampling value of first type data and accord with the rule of a first configuration file, the first configuration file is defined according to a first rule, the first configuration file comprises the first data identifier, the first data identifier is used for identifying the first type data, and the first data identifier has uniqueness in the data identifier defined according to the first rule;

and the first data acquisition equipment sends the first data to first equipment.

14. The method of claim 13, wherein the first rule is a rule of a data dictionary.

15. The method according to claim 13 or 14, wherein the first data acquisition device is any one of: intelligence wrist-watch, intelligent bracelet, body fat balance, intelligent glasses, clinical thermometer, sphygmomanometer, rhythm of the heart monitoring facilities.

16. The method according to any one of claims 13-15, wherein the first type of data is any one of: walking data, running data, swimming data, riding data, sleeping data, weight data, pressure data, heart rate data, blood pressure data, body temperature data, blood oxygen data, blood glucose data.

17. A communication system, characterized in that the communication system comprises a first data acquisition device and a data display device, wherein,

the first data acquisition equipment is used for acquiring first data and sending the first data to the data display equipment; the first data comprises a first data identifier and a first sampling value of first type data, and conforms to the rule of a first configuration file, the first configuration file is defined according to a first rule, the first configuration file comprises the first data identifier, the first data identifier is used for identifying the first type data, and the first data identifier has uniqueness in the data identifier defined according to the first rule;

and the data display device is used for identifying that the first data belongs to the first type data according to the first data identifier and the first configuration file.

18. The communication system according to claim 17, wherein the communication system further comprises a cloud server, and the first profile contains first description information of the first type of data;

the data display device is further configured to send third data to the cloud server, where the third data includes the first description information and a sampling value of the first type of data;

the cloud server is used for storing the third data.

19. An apparatus, characterized in that the apparatus comprises a memory for storing a computer program and a processor for invoking the computer program such that the apparatus performs the method of any of claims 1-12 or claims 13-16.

20. A computer-readable storage medium comprising instructions that, when executed on a device, cause the device to perform the method of any of claims 1-12 or claims 13-16.

21. A computer program product comprising computer instructions which, when run on an apparatus, cause the apparatus to perform the method of any one of claims 1-12 or claims 13-16.