CN110659330A - Data processing method, device and storage medium - Google Patents
Data processing method, device and storage medium Download PDFInfo
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- CN110659330A CN110659330A CN201910900339.XA CN201910900339A CN110659330A CN 110659330 A CN110659330 A CN 110659330A CN 201910900339 A CN201910900339 A CN 201910900339A CN 110659330 A CN110659330 A CN 110659330A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
- G06F16/275—Synchronous replication
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Abstract
The application discloses a data processing method, a data processing device and a storage medium, and relates to the field of Internet of things and cloud computing. The specific implementation scheme is as follows: the method comprises the steps that the electronic equipment obtains data of a first theme of the Internet of things equipment; the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data; and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server. The scheme realizes data synchronization between the electronic equipment and the server, and has high efficiency.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data processing method and apparatus in the internet of things, and a storage medium.
Background
With the continuous development of the internet of things technology, more and more devices are connected to the internet of things, and the internet of things technology is widely applied, so that more and more data are generated on the devices of the internet of things. Because the computing power of the internet of things equipment is limited and the network bandwidth is limited, edge computing becomes one of new trends in the development of the internet of things in order to meet the requirement of real-time response.
Services such as Artificial Intelligence (AI) inference and function calculation are often run on the edge computing device, and on one hand, these services generate a large amount of data results including video, picture files, AI inference results, and the like, and on the other hand, the edge computing device also generates a large amount of system logs. How to synchronize mass data generated on edge computing equipment to a cloud server in the scene of the internet of things is very important.
The main ways to solve this problem currently are: the data are synchronized to the cloud server by manually operating the edge computing device and manually copying the required files. The processing efficiency is lower in the mode, and huge labor cost is wasted.
Disclosure of Invention
The application provides a data processing method, a data processing device and a storage medium, so that data synchronization of edge computing equipment and a server is realized, and the efficiency is high.
A first aspect of the present application provides a data processing method, including:
the method comprises the steps that the electronic equipment obtains data of a first theme of the Internet of things equipment;
the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data;
and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server.
In the scheme, the electronic equipment acquires data of a first theme of the Internet of things equipment; the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data; and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server. The scheme realizes data synchronization between the electronic equipment and the server, and has high efficiency.
In a possible implementation manner, the electronic device stores the processed data;
the electronic equipment generates a message of a third theme according to the storage address of the processed data; the message of the third theme comprises a storage address of the processed data;
the electronic equipment generates the processed data into data of a second theme to be published, and the method comprises the following steps:
and the electronic equipment generates the processed data into data of a second theme to be issued according to the message of the third theme.
In one possible implementation, the method further includes:
and the electronic equipment converts the data of the fourth theme into the data of the fifth theme according to a preset forwarding rule and sends the data of the fifth theme to the server.
In a possible implementation manner, the converting, by the electronic device, the data of the fourth topic into the data of the fifth topic according to a preset forwarding rule includes:
the electronic equipment generates a message of a sixth theme according to the data of the fourth theme, wherein the message of the sixth theme comprises a storage address of the data of the fourth theme;
and the electronic equipment converts the data of the fourth theme into the data of the fifth theme according to the message of the sixth theme and a preset forwarding rule.
According to the scheme, the data acquired from the Internet of things equipment or the local data of the electronic equipment are directly uploaded to the server, and data synchronization of the electronic equipment and the server is achieved.
In a possible implementation manner, before sending the data of the second topic to the server, the method further includes:
the electronic equipment determines whether the sum of the data volume sent to the server and the data volume of the processed data exceeds a preset data volume threshold value;
and if not, the electronic equipment sends the data of the second theme to the server.
In a possible implementation manner, after the electronic device sends the data of the second topic to the server, the method further includes:
and the electronic equipment records the sum of the data volume sent to the server and the data volume of the processed data and updates the data volume sent to the server.
In the scheme, the function of flow limitation is realized.
In one possible implementation manner, the method further includes:
the electronic equipment receives the optimized AI model sent by the server; the optimized AI model is obtained by optimizing the established AI model by the server according to the received processed data;
and the electronic equipment processes the data sent by the Internet of things equipment according to the optimized AI model.
In the above embodiment, the processed data of the AI model is uploaded to the cloud server and the AI model is continuously optimized to form positive feedback.
In a possible implementation manner, before sending the data of the second topic to the server, the method further includes:
the electronic equipment establishes connection with the server according to the configuration information; the configuration information includes: address information of the server and topic information supported by the server.
A second aspect of the present application provides a data processing apparatus comprising:
the acquisition module is used for acquiring data of a first theme of the Internet of things equipment;
the processing module is used for carrying out data processing on the data of the first theme by utilizing an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data;
the processing module is further configured to generate the processed data into data of a second topic to be published;
and the sending module is used for sending the data of the second theme to a server.
A third aspect of the present application provides an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of the first aspects of the present application.
A fourth aspect of the present application provides a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any of the first aspects of the present application.
One embodiment in the above application has the following advantages or benefits: the method comprises the steps that the electronic equipment obtains data of a first theme of the Internet of things equipment; the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data; and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server. The scheme realizes data synchronization between the electronic equipment and the server, and has high efficiency.
Other effects of the above-described alternative will be described below with reference to specific embodiments.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is an application scenario architecture diagram provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of a data processing method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of the present application according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;
fig. 5 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Before describing the method provided by the present application, an application scenario of the embodiment of the present application is first described with reference to fig. 1. Fig. 1 is an application scenario architecture diagram provided in the embodiment of the present application. Optionally, as shown in fig. 1, the application scenario includes an internet of things device 11, an electronic device 12, and a server 13; the internet of things device 11 may include, for example, a video capture device (e.g., a monitoring camera), an in-vehicle device, an intelligent home device, and the like. An edge computing device such as a computer.
The internet of things device 11, the electronic device 12, and the electronic device 12 and the server 13 may be connected through a network.
The method provided by the invention can be realized by an electronic device such as a processor executing corresponding software codes, and can also be realized by an electronic device executing corresponding software codes and simultaneously performing data interaction with a server.
The technical solution of the present application will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. For convenience of understanding, the specific examples in the following embodiments are described by taking the big data field as an example, but are not limited to the application scenario.
Fig. 2 is a schematic flow chart of a data processing method according to an embodiment of the present application. As shown in fig. 2, the method provided by this embodiment includes the following steps:
s101, the electronic equipment acquires data of a first theme of the Internet of things equipment;
specifically, the electronic device obtains data of the internet of things device, where the data is, for example, data of a first theme, and the first theme is a theme supported by the electronic device.
Before sending data, the internet of things device establishes connection with the electronic device according to the acquired configuration information, for example, permission information of the electronic device and a theme which can be supported by the electronic device. The authority information includes information such as an account number and a password of the electronic device.
S102, the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data;
in one implementation, the AI model is used to perform data processing on the data of the first topic, for example, a corresponding data processing instance may be called to process the data, and the data processing instance includes, but is not limited to, a plurality of functions such as an AI inference function, an SQL statement, P5thon, node.
The data processing strategy is to transmit the data of the subject A after being processed by the AI model a and the data of the subject B.
S103, the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server.
Specifically, the processed data is generated into data of a second theme, the second theme is a theme supported by the server, and the data of the second theme is sent to the server. And verifying whether the data synchronization is successful by checking the file stored in the server.
In one implementation, before sending data to a server, an electronic device establishes a connection with the server according to configuration information; the configuration information includes: address information of the server and topic information supported by the server.
The configuration information may further include authentication information, for example, key information of the electronic device, and the electronic device is verified when the connection is established, and if the verification is passed, the connection is established.
In the method of the embodiment, the electronic device acquires data of a first theme of the internet of things device; the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data; and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server. The scheme realizes data synchronization between the electronic equipment and the server, and has high efficiency.
On the basis of the above embodiment, further, the following operations may be performed after step S102:
the electronic equipment stores the processed data;
the electronic equipment generates a message of a third theme according to the storage address of the processed data; the message of the third topic comprises a storage address of the processed data;
accordingly, step S103 can be implemented by the following steps:
and the electronic equipment generates the processed data into data of a second theme to be issued according to the message of the third theme and sends the data of the second theme to the server.
Specifically, the data processed by the AI model may be stored in a local disk of the electronic device, and a message of a third topic is generated, where the message of the third topic includes a storage address of the processed data, that is, a file path of the processed data in the local disk, and the third topic is a topic subscribed by the upload module.
In the above manner, the processed data is persistently stored in the local disk, so that the persistence of the abnormal state can be realized.
In an optional embodiment, as shown in fig. 3, the message processing module may send the obtained data of the internet of things device to the data processing module, the data processing module processes the data by using the AI model, stores the processed data in the local disk, and the message processing module generates a message of a third topic and sends the message to the uploading module; and the uploading module acquires the processed data according to the storage address included in the message of the third theme, generates the data of the second theme to be issued from the processed data, and sends the data to the server. The internet of things equipment is video acquisition equipment for example, and acquires video data. The data processing, for example, identifies a face in each frame of image in the video data, and marks the position of the face in the image to obtain a processed multi-frame image.
On the basis of the foregoing embodiment, the method of this embodiment may further include:
and the electronic equipment converts the data of the fourth theme into the data of the fifth theme according to a preset forwarding rule and sends the data of the fifth theme to the server.
The data of the fourth theme may be data sent by the internet of things device, such as a video, an image file, and the like, or data stored locally by the electronic device, such as a system log, device status information, and the like. The forwarding rule refers to that the data of the theme A is directly changed into the data of the theme B and then is sent.
In an implementation manner, the "electronic device converts the data of the fourth topic into the data of the fifth topic according to a preset forwarding rule", which may specifically be implemented by the following steps:
the electronic equipment generates a message of a sixth theme according to the data of the fourth theme, wherein the message of the sixth theme comprises a storage address of the data of the fourth theme;
and the electronic equipment converts the data of the fourth theme into the data of the fifth theme according to the message of the sixth theme and a preset forwarding rule.
Specifically, as shown in fig. 3, the message processing module may generate a message of a sixth topic according to the acquired data of the fourth topic, and send the message to the uploading module, and the uploading module acquires the data of the fourth topic according to a storage address included in the message of the sixth topic, and generates the data of the fourth topic into data of a fifth topic to be published, and sends the data of the fifth topic to the server. The sixth theme is a theme subscribed by the uploading module, and the fifth theme is a theme supported by the server.
On the basis of the above embodiment, before sending the data to the server, the following operations may also be performed:
the electronic equipment determines whether the sum of the data volume sent to the server and the data volume of the processed data exceeds a preset data volume threshold value or not;
and if not, the electronic equipment sends the data of the second theme to the server.
Specifically, the electronic device may implement flow control of uploading a file to the server. For example, before sending the current data to be sent, it is determined whether a data stream sent to the server exceeds a preset data amount threshold, if so, the sending is stopped, if not, the sum of the data amount sent to the server and the data amount of the current data to be sent is further determined, and whether the sum exceeds the preset data amount threshold, and if not, the current data to be sent is sent to the server, where the current data to be sent is, for example, data of a second theme (including data after AI model processing), or data of a fifth theme.
In one implementation, if it is determined that the sum of the data amount sent to the server and the data amount of the data to be sent currently exceeds the data amount threshold, the electronic device records the sum of the data amount sent to the server and the data amount of the processed data, and updates the data amount sent to the server.
That is, the electronic device records the sum of the data size sent to the server and the data size of the current data to be sent, and updates the data size sent to the server. I.e. the amount of data sent to the server is updated to the sum of the two.
In an alternative embodiment, breakpoint resuming may also be implemented, for example, data to be sent is divided into at least two parts and sent through different threads.
In an optional embodiment, before sending the data to the server, the data may also be compressed, and the compression method in this application is not limited.
In the implementation method, the function of flow limitation is realized.
On the basis of the foregoing embodiment, further, the method of this embodiment may further include:
the electronic equipment receives the optimized AI model sent by the server; the optimized AI model is obtained by optimizing the established AI model by the server according to the received processed data;
and the electronic equipment processes the data sent by the Internet of things equipment according to the optimized AI model.
Specifically, after the electronic device sends the data to the cloud server, the cloud server optimizes the AI model according to the received data, and sends the optimized AI model to the electronic device.
And the electronic equipment processes the data sent by the equipment of the Internet of things according to the optimized AI model.
In the above embodiment, the processed data of the AI model is uploaded to the cloud server and the AI model is continuously optimized to form positive feedback.
In one implementation, as shown in fig. 3, the message processing module may be configured to configure a connection right between the internet of things device and the electronic device, and a topic sending and subscribing right of the internet of things device; the data processing module is used for making a data processing strategy, configuring function instance starting information and the like, and processing data by utilizing an AI model or other data processing modes.
The cloud agent module is used for configuring connection and authentication information of the electronic equipment and the cloud server, theme information sent by data and the like, acquiring an AI model issued by the server, and receiving messages forwarded by the cloud server by subscribing corresponding themes. The connection mode adopted when the cloud agent module establishes connection with the cloud server includes, but is not limited to, TCP, SSL one-way authentication, SSL two-way authentication, and the like.
The data format of the configuration information in the embodiment of the present application includes, but is not limited to JSON, 5AML, XML, and the like.
The uploading module is used for uploading local file data of the electronic equipment, limiting flow of the uploaded data and the like. The uploading module can configure the address of the server and the authority of the electronic device for accessing the server, the breakpoint continuous transmission capability, the flow limiting function information and the supported theme information of the received message.
The cloud server includes, for example: the device access service module, the object storage service module and the AI training platform.
According to the method, the electronic device (such as the edge computing device) is deployed at the end of the local near-internet-of-things device, meanwhile, the inference function computing instance of the AI model can be configured, the data is processed by applying the configured inference function computing instance of the AI model while the time delay of near-receiving and forwarding messages is reduced, and the processing result can be uploaded to the cloud server according to the flow control.
In summary, on one hand, by using the data acquisition of the localized internet of things device and the data processing of the electronic device, the performance of processing the message is improved to a certain extent while the message is ensured to be sufficiently safe; on the other hand, the electronic device can also customize a synchronization policy, for example, data is stored in a file set, the storage location of the file set, flow restriction, a file compression mode and the like, and the data file set is uploaded to the cloud server.
Fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application. As shown in fig. 4, the data processing apparatus 400 provided in this embodiment includes:
an obtaining module 401, configured to obtain data of a first theme of the internet of things device;
a processing module 402, configured to perform data processing on the data of the first topic by using an artificial intelligence AI model according to a preset data processing policy, so as to obtain processed data;
the processing module 402 is further configured to generate data of a second topic to be published from the processed data;
a sending module 403, configured to send the data of the second topic to a server.
In one possible implementation manner, the method further includes:
the storage module is used for storing the processed data;
the processing module 402 is further configured to generate a message of a third topic according to the storage address of the processed data; the message of the third theme comprises a storage address of the processed data;
and generating the data of the second theme to be issued from the processed data according to the message of the third theme.
In a possible implementation manner, the processing module 402 is further configured to:
and converting the data of the fourth theme into the data of the fifth theme according to a preset forwarding rule, and sending the data of the fifth theme to the server.
In a possible implementation manner, the processing module 402 is specifically configured to:
generating a message of a sixth theme according to the data of the fourth theme, wherein the message of the sixth theme comprises a storage address of the data of the fourth theme;
and converting the data of the fourth theme into the data of the fifth theme according to the message of the sixth theme and a preset forwarding rule.
According to the scheme, the data acquired from the Internet of things equipment or the local data of the electronic equipment are directly uploaded to the server, and data synchronization of the electronic equipment and the server is achieved.
In a possible implementation manner, the processing module 402 is further configured to:
determining whether the sum of the data volume sent to the server and the data volume of the processed data exceeds a preset data volume threshold;
if not, the sending module 403 is configured to send the data of the second topic to the server.
In a possible implementation manner, the processing module 402 is further configured to:
and recording the sum of the data volume sent to the server and the data volume of the processed data, and updating the data volume sent to the server.
In the scheme, the function of flow limitation is realized.
In one possible implementation manner, the method further includes:
the receiving module is used for receiving the optimized AI model sent by the server; the optimized AI model is obtained by optimizing the established AI model by the server according to the received processed data;
the processing module 402 is further configured to: and processing the data sent by the Internet of things equipment according to the optimized AI model.
In the above embodiment, the processed data of the AI model is uploaded to the cloud server and the AI model is continuously optimized to form positive feedback.
In a possible implementation manner, the processing module 402 is further configured to:
establishing connection with the server according to the configuration information; the configuration information includes: address information of the server and topic information supported by the server.
The data processing apparatus provided in the embodiment of the present application may execute the technical solution in any of the method embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 5, it is a block diagram of an electronic device according to the method of data processing in the embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 5, the electronic apparatus includes: one or more processors 501, memory 502, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 5, one processor 501 is taken as an example.
The memory 502, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method of data processing in the embodiments of the present application (for example, the obtaining module 401, the processing module 402, and the sending module 403 shown in fig. 4). The processor 501 executes various functional applications of the server and data processing, i.e., a method of implementing data processing in the above-described method embodiments, by executing non-transitory software programs, instructions, and modules stored in the memory 502.
The memory 502 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 502 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 502 optionally includes memory located remotely from processor 501, which may be connected to data processing electronics over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the data processing method may further include: an input device 503 and an output device 504. The processor 501, the memory 502, the input device 503 and the output device 504 may be connected by a bus or other means, and fig. 5 illustrates the connection by a bus as an example.
The input device 503 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the data processing electronic apparatus, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, or other input devices. The output devices 504 may include a display device, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
According to the technical scheme of the embodiment of the application, the electronic equipment acquires data of a first theme of the Internet of things equipment; the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data; and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server. The scheme realizes data synchronization between the electronic equipment and the server, and has high efficiency.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (18)
1. A data processing method, comprising:
the method comprises the steps that the electronic equipment obtains data of a first theme of the Internet of things equipment;
the electronic equipment performs data processing on the data of the first theme by using an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data;
and the electronic equipment generates the processed data into data of a second theme to be issued and sends the data of the second theme to a server.
2. The method of claim 1, wherein after obtaining the processed data, further comprising:
the electronic equipment stores the processed data;
the electronic equipment generates a message of a third theme according to the storage address of the processed data; the message of the third theme comprises a storage address of the processed data;
the electronic equipment generates the processed data into data of a second theme to be published, and the method comprises the following steps:
and the electronic equipment generates the processed data into data of a second theme to be issued according to the message of the third theme.
3. The method of claim 1, further comprising:
and the electronic equipment converts the data of the fourth theme into the data of the fifth theme according to a preset forwarding rule and sends the data of the fifth theme to the server.
4. The method of claim 3, wherein the electronic device converts the data of the fourth topic into the data of the fifth topic according to a preset forwarding rule, and the method comprises:
the electronic equipment generates a message of a sixth theme according to the data of the fourth theme, wherein the message of the sixth theme comprises a storage address of the data of the fourth theme;
and the electronic equipment converts the data of the fourth theme into the data of the fifth theme according to the message of the sixth theme and a preset forwarding rule.
5. The method according to any one of claims 1-4, wherein before sending the data of the second topic to the server, further comprising:
the electronic equipment determines whether the sum of the data volume sent to the server and the data volume of the processed data exceeds a preset data volume threshold value;
and if not, the electronic equipment sends the data of the second theme to the server.
6. The method of claim 5, wherein after the electronic device sends the data of the second topic to the server, further comprising:
and the electronic equipment records the sum of the data volume sent to the server and the data volume of the processed data and updates the data volume sent to the server.
7. The method according to any one of claims 1-4, further comprising:
the electronic equipment receives the optimized AI model sent by the server; the optimized AI model is obtained by optimizing the established AI model by the server according to the received processed data;
and the electronic equipment processes the data sent by the Internet of things equipment according to the optimized AI model.
8. The method according to any one of claims 1-4, wherein before sending the data of the second topic to the server, further comprising:
the electronic equipment establishes connection with the server according to the configuration information; the configuration information includes: address information of the server and topic information supported by the server.
9. A data processing apparatus, comprising:
the acquisition module is used for acquiring data of a first theme of the Internet of things equipment;
the processing module is used for carrying out data processing on the data of the first theme by utilizing an Artificial Intelligence (AI) model according to a preset data processing strategy to obtain processed data;
the processing module is further configured to generate the processed data into data of a second topic to be published;
and the sending module is used for sending the data of the second theme to a server.
10. The apparatus of claim 9, further comprising:
the storage module is used for storing the processed data;
the processing module is further configured to generate a message of a third theme according to the storage address of the processed data; the message of the third theme comprises a storage address of the processed data;
and generating the data of the second theme to be issued from the processed data according to the message of the third theme.
11. The apparatus of claim 9, wherein the processing module is further configured to:
and converting the data of the fourth theme into the data of the fifth theme according to a preset forwarding rule, and sending the data of the fifth theme to the server.
12. The apparatus of claim 11, wherein the processing module is specifically configured to:
generating a message of a sixth theme according to the data of the fourth theme, wherein the message of the sixth theme comprises a storage address of the data of the fourth theme;
and converting the data of the fourth theme into the data of the fifth theme according to the message of the sixth theme and a preset forwarding rule.
13. The apparatus of any of claims 9-12, wherein the processing module is further configured to:
determining whether the sum of the data volume sent to the server and the data volume of the processed data exceeds a preset data volume threshold;
and if not, the sending module is used for sending the data of the second theme to the server.
14. The apparatus of claim 13, wherein the processing module is further configured to:
and recording the sum of the data volume sent to the server and the data volume of the processed data, and updating the data volume sent to the server.
15. The apparatus of any one of claims 9-12, further comprising:
the receiving module is used for receiving the optimized AI model sent by the server; the optimized AI model is obtained by optimizing the established AI model by the server according to the received processed data;
the processing module is further configured to: and processing the data sent by the Internet of things equipment according to the optimized AI model.
16. The apparatus of any of claims 9-12, wherein the processing module is further configured to:
establishing connection with the server according to the configuration information; the configuration information includes: address information of the server and topic information supported by the server.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910900339.XA CN110659330A (en) | 2019-09-23 | 2019-09-23 | Data processing method, device and storage medium |
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| CN201910900339.XA CN110659330A (en) | 2019-09-23 | 2019-09-23 | Data processing method, device and storage medium |
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| CN110659330A true CN110659330A (en) | 2020-01-07 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111338808A (en) * | 2020-05-22 | 2020-06-26 | 支付宝(杭州)信息技术有限公司 | Collaborative computing method and system |
| CN111797314A (en) * | 2020-06-28 | 2020-10-20 | 百度在线网络技术（北京）有限公司 | Data processing method, device, equipment and storage medium |
| CN116938672A (en) * | 2023-09-18 | 2023-10-24 | 中国电信股份有限公司 | Task model distribution method, device, computer equipment, medium and product |
-
2019
- 2019-09-23 CN CN201910900339.XA patent/CN110659330A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111338808A (en) * | 2020-05-22 | 2020-06-26 | 支付宝(杭州)信息技术有限公司 | Collaborative computing method and system |
| CN111338808B (en) * | 2020-05-22 | 2020-08-14 | 支付宝(杭州)信息技术有限公司 | Collaborative computing method and system |
| CN111797314A (en) * | 2020-06-28 | 2020-10-20 | 百度在线网络技术（北京）有限公司 | Data processing method, device, equipment and storage medium |
| CN116938672A (en) * | 2023-09-18 | 2023-10-24 | 中国电信股份有限公司 | Task model distribution method, device, computer equipment, medium and product |
| CN116938672B (en) * | 2023-09-18 | 2024-02-23 | 中国电信股份有限公司 | Task model distribution method, device, computer equipment, medium and product |
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