CN112765140A

CN112765140A - Data processing method, data acquisition system and computer storage medium

Info

Publication number: CN112765140A
Application number: CN202110034713.XA
Authority: CN
Inventors: 何伟
Original assignee: Zhejiang Xinghan Yuntu Artificial Intelligence Technology Co ltd
Current assignee: Zhejiang Xinghan Yuntu Artificial Intelligence Technology Co ltd
Priority date: 2021-01-11
Filing date: 2021-01-11
Publication date: 2021-05-07

Abstract

The invention discloses a data processing method, a data acquisition system and a computer storage medium. The method comprises the following steps: the data acquisition platform acquires acquired original data; correcting the original data according to a correction coefficient corresponding to the type of the original data to obtain corrected data; and correcting the correction data according to a user instruction to obtain processing data. Therefore, the data acquisition system in the embodiment of the invention can correct and revise the original data, so that the processed data is standardized. Therefore, the subsequent use process of the processed data is more convenient, and the phenomenon of inaccurate data caused by various factors is avoided.

Description

Data processing method, data acquisition system and computer storage medium

Technical Field

Embodiments of the present invention relate to the field of data processing, and in particular, to a data processing method, a data acquisition system, and a computer storage medium.

Background

The data collection platform may collect data through a variety of hardware. Where different hardware may have their corresponding SDKs so that respective raw data may be collected. However, the original data may have various data formats due to differences of a plurality of factors such as manufacturers, models, default settings and the like of hardware, and the complex form cannot be unified. In addition, the collected data may not be accurate enough due to factors such as the field environment of data collection, installation errors, and the like. It can be seen that the raw data collected cannot be used directly, and a solution for processing the raw data is needed.

Disclosure of Invention

The embodiment of the invention provides a data processing method, a data acquisition system and a computer storage medium.

In a first aspect, there is provided a method of data processing, comprising: the data acquisition platform acquires acquired original data; correcting the original data according to a correction coefficient corresponding to the type of the original data to obtain corrected data; and correcting the correction data according to a user instruction to obtain processing data.

In one embodiment, the type of the raw data is determined according to a hardware type of an acquisition device of the raw data.

In one embodiment, the type of hardware of the acquisition device is any one of: the system comprises an attitude sensor, a handle sensor, a vital sign measuring suite, an emotion collecting suite, serial port communication custom hardware, network communication custom hardware and Bluetooth communication custom hardware.

In one embodiment, the raw data is collected by an attitude sensor, and accordingly, the raw data is rectified, including: and obtaining relative attitude deviation data corresponding to the original data by taking preset initial attitude data as a calibration point to serve as the correction data.

In one embodiment, correcting the correction data comprises: correcting the correction data using a default mapping rule.

In one embodiment, correcting the correction data comprises: acquiring a modification instruction of a user, and constructing a data mapping table based on a default mapping rule; and correcting the correction data by using the data mapping table.

In one embodiment, the raw data is collected by a handle-like sensor, and the data mapping table represents a mapping relationship between (a) default mapping rules and (b) key positions used by a user.

In one embodiment, further comprising: and packaging the processing data.

In a second aspect, a data acquisition system is provided, comprising: the data acquisition module is used for acquiring original data from various different hardware; the data processing module is used for correcting the original data according to the correction coefficient corresponding to the type of the original data to obtain corrected data; and correcting the correction data according to a user instruction to obtain processing data.

In a third aspect, a computer storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a computer or a processor, implements the steps of the method according to the first aspect or any embodiment.

Therefore, the data acquisition system in the embodiment of the invention can correct and revise the original data, so that the processed data is standardized. Therefore, the subsequent use process of the processed data is more convenient, and the phenomenon of inaccurate data caused by various factors is avoided.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.

FIG. 1 is a schematic block diagram of a data acquisition system provided by an embodiment of the present invention;

FIG. 2 is another schematic block diagram of a data acquisition system provided by an embodiment of the present invention;

FIG. 3 is a schematic flow chart diagram of a method of data processing provided by an embodiment of the present invention;

fig. 4 is a schematic block diagram of a data processing apparatus according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

An embodiment of the present invention provides a data acquisition system, as shown in fig. 1, the system includes a data acquisition module and a data processing module. In addition, optionally, as shown in fig. 2, the system may further include a data usage module.

The data acquisition module may obtain hardware data from various different hardware, and then use different Software Development Kits (SDKs) according to the different hardware, thereby obtaining raw data. It can be understood that different SDKs corresponding to different hardware are stored in the data acquisition module, and the SDKs can be continuously expanded as the number of connected hardware (such as manufacturers, models, and the like) increases.

The data collected by the data collection module may be data collected by hardware such as a microphone, a camera, a radar, a dancing blanket, an attitude sensor, a remote control board, or may also be network data, which is not limited in the present application.

The data processing module may include a local data processing module and optionally may include a cloud data processing module. For example, the data processing module may obtain raw data from the data acquisition module and process the data to obtain processed data. In this embodiment of the present invention, a process of processing data by a data processing module (particularly, a local data processing module) may be as shown in fig. 3, where the process includes:

s10, acquiring the acquired original data;

s20, correcting the original data according to the correction coefficient corresponding to the type of the original data to obtain corrected data;

and S30, correcting the correction data according to the user command to obtain processed data.

It is understood that the raw data in S10 may be data obtained by the data acquisition module using the corresponding SDK.

In the embodiment of the present invention, the type of the raw data may refer to a hardware type of the acquisition device. Hardware types include, but are not limited to: the system comprises an attitude sensor, a handle sensor, a vital sign measuring suite, an emotion collecting suite, serial port communication custom hardware, network communication custom hardware, Bluetooth communication custom hardware and the like.

Corresponding correction coefficients may be preset according to attributes of the raw data acquired by the acquisition devices of different hardware types, and then in S20, the correction coefficients corresponding to the hardware types may be extracted according to the correspondence relationship, thereby obtaining corrected data. The following will be described separately for various different hardware types.

1. Attitude sensor

The attitude sensor is a huge set, and can be a three-axis sensor, a six-axis sensor, a nine-axis sensor and the like, and comprises an attitude sensor of a mobile phone, an attitude sensor of a handle or a self-made attitude sensor. Such as, for example, accelerometers, gyroscopes, magnetometers, and the like.

The data acquisition mode of the attitude sensor is different due to different hardware, but the data format of the finally obtained raw data is the same, so that all the attitude sensors are unified into one hardware type to perform the same data processing mode in the application.

Specifically, if the raw data in S10 is the raw data collected by the attitude sensor (also referred to as attitude data), the correction process in S20 may include: and taking the initial attitude data as a calibration point to obtain relative attitude deviation data corresponding to the original data as correction data. That is, the correction parameter may be initial posture data set in advance.

For the attitude data, it is generally impossible for the facing azimuth to exactly coincide with the north-south pole of the earth magnetism, so an initial attitude data is first required as a calibration point for the attitude data (calibration is performed), and on this basis, all the relative attitude offset data (relative displacement) can be directly used as the raw data.

2. Handle type sensor

The handle-like sensor may refer to a device using a keyboard handle protocol common to platforms including windows or android. These keyboard handle protocols can be directly recognized by the operating system or the usage module, and have a certain universality. Such as, for example, a handle, a keyboard, a remote control pad, a dance mat, etc.; such as arm rings, brain waves, etc. Such devices have unified features, that is, have a certain standard, but if the user performs the adaptation, the complicated work of performing different key position definitions on different hardware and the like needs to be completed.

In S10, the handle-like sensor may collect raw data using the SDK or unified protocol corresponding to the hardware.

In consideration of the variation in hardware, since the collected raw data cannot be uniformly normalized, it is necessary to correct the variation in S20 based on a deviation correction coefficient stored in advance for each hardware. Specifically, the correction may be performed within a specific data range.

3. Vital sign measuring kit

The vital signs, namely heart rate, pulse, blood pressure, respiration (frequency, vital capacity, etc.), pain, blood oxygen, pupil and cornea reflex changes, and the like, can be measured through various sensors or other types of devices, and corresponding special data exchange can be completed through movements such as movement, deep breathing and air blowing. Such as, for example, a sphygmomanometer, a heart rate meter, a respiratory mask, etc. For another example, the face information of the human face and/or the motion state of the person may be obtained by a camera.

Specifically, after the raw data is collected, simple health information can be inferred through the extraction processes of age analysis, gender analysis and the like, the basic health condition of the human body can be basically judged, and corresponding opinions can be proposed. Meanwhile, physical sign information such as respiration and pulse can be extracted, the current human motion state and the like are combined, and the following parameters are extracted: physical sign comprehensive information, exercise comprehensive information, limit data and the like.

The sign comprehensive information may include health conditions, such as stationary sign information in a stationary state: heart rate, pulse, etc. The exercise comprehensive information may include a current exercise state, such as real-time exercise signs in the exercise state, an exercise state (running speed, squat jump speed/number), and the like. The limit data may include, but is not limited to: maximum lung capacity, maximum exercise blood pressure, maximum pulse, limiting respiratory rate, etc.

4. Emotion collection kit

For example, the device may be a camera, a microphone, or other hardware devices. The camera can gather the image, and the microphone can gather the sound to can judge personage's mood through collecting personage's expression, limbs action and sound.

Accordingly, the correction parameter may include exposure, white balance, saturation, and the like, and may further include a sound enhancement coefficient, a noise suppression ratio, and the like. Specifically, the human expression uses a color camera to collect a color picture containing data of the human clear face by dynamically adjusting parameters such as exposure, white balance and saturation. In addition, the sound is corrected by means of sound analysis, dynamic modification of the enhancement coefficient of the sound, noise suppression and the like, and the definition of the sound is ensured.

5. Serial port type communication self-defining hardware

The serial port type communication is usually special hardware, and generally, the device uses a matched SDK or a self-defined serial port protocol, and different data acquisition methods are required according to different hardware to obtain original data.

For example, in radar, the custom hardware usually has no uniform format protocol, so it needs to be corrected and uniform in S20. It is understood that the specific manner of correction and the correction parameters may be preset according to the attributes of the customized hardware (and the customized manner, etc.).

6. Network communication type self-defining hardware

The network hardware is usually established on the basis of a general TCP/IP protocol for data transmission, the transmission types and contents of the network hardware are various, usually, network cameras, mobile phones, self-made simple sensors and the like, the respective SDK is used in the extraction process, and the communication modes used later are usually all TCP/UDP modes, so that the legality of the hardware can be verified by using specific exchange messages besides a fixed port mode which is usually set, and the data content format to be transmitted is defined by a mode of firstly exchanging the data format, so that the normal transmission and identification of the data are ensured.

7. Bluetooth communication self-defined hardware

Bluetooth communication has its standard protocol, through complete broadcasting, searching, binding, etc. process, can form stable short distance data transmission channel. The data content is self-defined by Bluetooth hardware, so that the data collection and data standardization definition are required to be carried out by self. Different devices need to use the self-defined data acquisition method, and original data are obtained through the data acquisition module.

Further, in S20, data needs to be corrected, and the respective correction methods are usually defined by using interactive commands, and the correction can be completed by using the instructions of the hardware and the corresponding correction commands.

Therefore, the data correction method has extensibility, and for other new hardware types, only corresponding correction parameters need to be set according to specific requirements to correct, and the expansion of hardware for collecting data can be realized through small change.

For example, in S30, the corrected data may be further corrected, so as to obtain processed data.

In one embodiment, corrective data may be modified using default mapping rules.

In another embodiment, a user's modification instruction may be obtained to build a data mapping table based on default mapping rules. So that the corrective data can be corrected using the data map at S30. This ensures the mapping correctness of the specific device.

For example, assuming that the raw data is collected by the handle-type sensor, the data mapping table may represent a mapping relationship between (a) default mapping rules and (b) key positions used by the user. Therefore, when a user plays games, the user can use the key position used by the user to drag by himself, so that the key can be remapped before the games are started, and the support range of the data use module to the universal handle sensor is expanded.

Therefore, the local data processing module in the application can correct the acquired original data, and errors caused by factors such as equipment installation deviation and field environment are reduced as much as possible in the process. The standardization can be carried out by modification, and different standardized formats which are in accordance with actual situations are defined according to the types of hardware.

Optionally, in an optional implementation manner, in S30, after the correction is performed, feature extraction may be further performed to obtain the processed data.

Referring to fig. 1, the feature extraction process may be performed in a local data processing module or in a cloud data processing module. Specifically, different algorithms can be started according to different requirements, and data can be standardized according to convenience and convenience in actual use.

Understandably, the feature extraction can be performed according to the attribute of the data, the concerned field, and the like.

For example, if the raw data is collected by a gesture sensor, only the gesture data can be provided because of the raw data. And corresponding movement tracks, specific track identification and the like need to further extract data. Meanwhile, different devices can use different length units, which are different from millimeters to meters, and hardware needs to be unified in metering units, so that correct use of the data use module is guaranteed.

The displacement calculation may use an integral accumulation mode, i.e., a form of inertial navigation. However, due to the limitation of precision of civil hardware, the purpose of accurate positioning is difficult to achieve at present, so that displacement calculation can only be applied to functions with low precision requirements, such as track recognition and the like.

For example, if the raw data is collected by a vital sign measurement suite, simple health information can be inferred through extraction processes such as age analysis and gender analysis, and further, vital sign information such as comprehensive vital sign information, comprehensive exercise information and limit data can be obtained.

For example, the cloud data processing module may perform feature extraction required for operations such as cloud computing, cloud comparison, image processing, and portrait recognition.

In connection with fig. 1 or fig. 2, the method of fig. 3 may be performed by a data acquisition system, in particular by a data processing module, more particularly by a local data processing module.

Thus, the embodiment of the present invention can obtain the processed data based on the original data by the method shown in fig. 3, so that after S30, the data usage module can use the processed data to perform the subsequent usage process. Optionally, the data processing module may further encapsulate the processing data, and provide the encapsulated data to the data using module.

The embodiment of the present invention does not limit the specific scene of the data usage module, and may be, for example, a game engine, a general compiling environment, and the like.

In addition, as shown in fig. 4, an embodiment of the present invention further provides an apparatus for data processing, which includes a processor and a memory, where the memory stores computer instructions, and when the computer instructions are executed by the processor, the steps of the method shown in fig. 3 can be implemented.

The memory may be a Read Only Memory (ROM), a static memory device, a dynamic memory device, or a Random Access Memory (RAM).

The processor may be a general-purpose Central Processing Unit (CPU), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits, and is configured to execute the relevant programs to implement the methods of the embodiments of the present application.

The processor may also be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the method of the present application may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory, and performs functions required to be performed by units included in the apparatus according to the embodiments of the present application or performs the method according to the embodiments of the present application in combination with hardware thereof.

Optionally, the apparatus may further comprise a communication interface and a bus. Wherein the communication interface enables communication with other devices or networks using transceiver means such as, but not limited to, a transceiver. For example, raw data may be acquired through a communication interface, processed data may be transmitted through a communication interface, and so on. A bus may include a pathway that transfers information between various components of the device (e.g., memory, processor, communication interface).

It is understood that the apparatus in fig. 4 may be the data processing module described above, or may be the data acquisition system described above.

In addition, the embodiment of the invention also provides a computer storage medium, and the computer storage medium is stored with the computer program. When executed by a computer or processor, may implement the steps of the method described above in connection with fig. 3. For example, the computer storage medium is a computer-readable storage medium.

In one embodiment, the computer program instructions, when executed by a computer or processor, cause the computer or processor to perform the steps of: acquiring collected original data; correcting the original data according to a correction coefficient corresponding to the type of the original data to obtain corrected data; and correcting the correction data according to a user instruction to obtain processing data.

The computer storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a portable compact disc read only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

In addition, an embodiment of the present invention further provides a computer program product, which contains instructions that, when executed by a computer, cause the computer to perform the steps of the method described above in conjunction with fig. 3.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the foregoing illustrative embodiments are merely exemplary and are not intended to limit the scope of the invention thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.

Claims

1. A method of data processing, comprising:

the data acquisition platform acquires acquired original data;

correcting the original data according to a correction coefficient corresponding to the type of the original data to obtain corrected data;

and correcting the correction data according to a user instruction to obtain processing data.

2. The method of claim 1, wherein the type of the raw data is determined according to a hardware type of an acquisition device of the raw data.

3. The method of claim 2, wherein the type of hardware of the acquisition device is any one of:

the system comprises an attitude sensor, a handle sensor, a vital sign measuring suite, an emotion collecting suite, serial port communication custom hardware, network communication custom hardware and Bluetooth communication custom hardware.

4. The method of claim 1, wherein the raw data is collected by an attitude sensor, and wherein rectifying the raw data accordingly comprises:

and obtaining relative attitude deviation data corresponding to the original data by taking preset initial attitude data as a calibration point to serve as the correction data.

5. The method of claim 1, wherein correcting the correction data comprises:

correcting the correction data using a default mapping rule.

6. The method of claim 1, wherein correcting the correction data comprises:

acquiring a modification instruction of a user, and constructing a data mapping table based on a default mapping rule;

and correcting the correction data by using the data mapping table.

7. The method of claim 6, wherein the raw data is collected by a handle-like sensor, and the data mapping table represents a mapping relationship between (a) default mapping rules and (b) key locations used by a user.

8. The method of claim 1, further comprising:

and packaging the processing data.

9. A data acquisition system, comprising:

the data acquisition module is used for acquiring original data from various different hardware;

the data processing module is used for correcting the original data according to the correction coefficient corresponding to the type of the original data to obtain corrected data; and correcting the correction data according to a user instruction to obtain processing data.

10. A computer storage medium on which a computer program is stored, characterized in that the computer program, when being executed by a computer or a processor, carries out the steps of the method according to any one of claims 1 to 8.