CN116009844A - Obstetric and research integrated platform supporting visual dragging for carrying out vehicle networking data fusion analysis - Google Patents
Obstetric and research integrated platform supporting visual dragging for carrying out vehicle networking data fusion analysis Download PDFInfo
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Abstract
The application belongs to the technical field of Internet of vehicles data analysis systems, and particularly relates to a production and research integrated platform supporting visual dragging for Internet of vehicles data fusion analysis, which comprises a node management module, a data stream construction module, a program operation connection module and a developer community module. The integrated platform can integrate academic research, teaching platform and industrial application together to realize the integration of obstetric and research, and solves the problems that business personnel are difficult to customize algorithm behaviors and reuse of existing components when using a data analysis system; for scientific researchers, the problem that the researcher hardly lands the researched and developed algorithm in a business system is solved; for teachers and students, the problem that the running environments are not matched and the algorithm logic is difficult to intuitively display is solved.
Description
Technical Field
The application belongs to the technical field of internet of vehicles data analysis systems, and particularly relates to an integrated obstetrical and research platform supporting visual dragging for internet of vehicles data fusion analysis.
Background
The analysis and research on the data of the Internet of vehicles is a problem that enterprises related to the Internet of vehicles must consider seriously, and the advanced and effective data analysis method can fully play important roles of the data in the aspects of promoting management, participating in decision making, researching landing and the like. In scientific research, researchers need to verify the validity of a method or model by preprocessing the data set and using it for further data analysis processes; in a business department, a business system needs to analyze and process related data generated by the Internet of vehicles in real time, so that the functions of monitoring abnormal data, alarming and the like are realized; in enterprise operations, enterprise personnel need to perform multidimensional analysis on market data to obtain market research reports and use the market research reports for enterprise product decisions.
In the existing internet of vehicles data analysis system, the problem is that the use flow of the system is heavy in computing thinking rather than business thinking, and the complexity of business personnel is not reduced when the business personnel conduct business analysis in the use process. Meanwhile, the traditional data analysis flow is biased to analyze the structured data, so that service personnel cannot effectively utilize the algorithm technology of artificial intelligence to energize products, and the existing internet of vehicles data fusion analysis platform in the market has the problems of difficult operator calling, difficult multiplexing of components, no support of a custom training model and the like.
Disclosure of Invention
In order to achieve the above purpose, the technical scheme adopted in the application is as follows: the integrated platform for carrying out the integrated analysis of the data of the Internet of vehicles by supporting the visual dragging comprises a node management module, a data stream construction module, a program operation connection module and a developer community module;
the node management module is used for creating new algorithm nodes or editing existing algorithm nodes and managing all the nodes;
the data stream construction module is used for supporting the instantiation of nodes of different types into a project in a visual dragging mode, and establishing a one-way connection relationship between the instance nodes to form a data analysis stream project;
the program running connection module is used for connecting the code program packaged in the node with a code interpreter of the background service, so that the running of the node program and the sharing of memory of the background service are realized, and the integration of debugging, development and deployment of the platform is realized;
the developer community module is used for supporting individual developers to issue the packaged nodes into communities, and other people download and multiplex the nodes.
Optionally, the node management module may create a new algorithm node in the node library, the platform user may package a code into a node according to a specified form requirement, define a data type and format of input data and output data for the node, and additionally define a configuration item of the node, so that the platform user may modify a parameter value in the configuration item according to an actual project scene, and then instantiate the node to convert the input data into output data through operation of the code and output the output data.
Optionally, the node management module can edit any existing algorithm node, modify and edit the algorithm node encapsulated by others according to specific requirements of the others, and convert the algorithm node into a node library of the current project for use.
Optionally, the data stream construction module supports instantiating different node types in the node library into the current project, and modifies a configuration item of a node to form an instantiated node, then a unidirectional connection relationship can be established between two instantiated nodes, the relationship defines a mapping between partial output data of a previous node and partial input data of a next node, data circulation between instantiated nodes is achieved, a connection relationship is established between a plurality of nodes, and finally a data analysis stream project capable of completing the whole data analysis task is formed.
Optionally, when the program running connection module runs the project, the code encapsulated in the instantiation node is connected with the code interpreter of the back-end service through the message queue, so that the running of the node program and the back-end service share the memory, when the node runs, the back-end service can monitor the specific value of each variable, the running state of each node in the project can be checked and debugged in the back-end service, and the integration of debugging, developing and deploying of the platform is realized.
Optionally, the step of developing the data analysis project by the integrated obstetric and research platform includes:
step (1): encapsulating the data analysis logic algorithm into nodes;
step (2): developing a node for reading in internet of vehicles data;
step (3): connecting algorithm nodes to complete development of data analysis flow;
step (4): debugging and running the data analysis stream.
Optionally, in step (1), in the integrated platform for research and development of the present application, the operation logic of one analysis stage in data analysis is implemented as a code segment, and the code segment is packaged into a node, and the data field types and formats of the input data and the output data of the node are customized, and in the operation process, the node instance performs calculation on the received input data through the program logic defined by the code block in advance, and the obtained calculation result is transmitted outwards through the customized output; meanwhile, configuring a variable part inside the program logic of the code block;
the self-written program logic is packaged into a reusable node, and the reusable node is multiplexed into the development of other data analysis streams by modifying configuration items and defining input and output and even secondary development modes; the operation steps of a specific packaging node are as follows:
the first step: determining a name for the node for identifying the node;
and a second step of: writing a section of descriptive text for the node, so that other people can understand things and applicable scenes which the node does;
and a third step of: defining the type and form of input data and output data of the algorithm node according to the requirements;
fourth step: determining configuration items required by the algorithm nodes;
fifth step: programming the program running logic of the node in the form of codes, and converting the input data of the node into output data according to certain algorithm logic.
Optionally, in step (2), the integrated platform for obstetrics and research connects the code in the node with the code interpreter of the background service through a message queue, so as to realize the sharing of the running program of the node in the platform and the memory of the background service, thereby enabling the algorithm of the platform to use the running environment and the data computing capability of the background service; and developing a node, establishing data connection with the Internet of vehicles by using an operation environment of a background service in the form of code fragments through reading files or reading databases, and importing data required to be processed by analyzing the Internet of vehicles data into a platform.
Optionally, in step (3), the algorithm node connection mode is as follows:
the first step: searching algorithm nodes needed by a project to be developed by newly establishing the node type or multiplexing the existing node type;
and a second step of: the needed node types are dragged into the currently developed project in a visual dragging mode, and node configuration items are filled in, so that the instantiation of the nodes is completed, and the nodes become instance nodes of the current project;
and a third step of: establishing a one-way connection relation between nodes with a logic relation, defining a mapping between output and input in the connection relation, and mapping output data of a previous node to input data of a next node, thereby realizing connection of the two nodes;
fourth step: repeating the third step until all the nodes with logic relation are connected.
Optionally, in step (4), the node code is connected with the code interpreter of the background service through the message queue, and the data analysis platform can realize memory sharing with the background service, so that the node code and the code interpreter of the background service are in the same running environment, and the development and debugging environment of the data analysis flow is the same as the deployment environment; by means of memory sharing, the values of various variables of the code in the algorithm node at run-time can be monitored by a background service, and the code is debugged in the background.
The invention provides an integrated obstetric and academic platform supporting visual dragging for data fusion analysis of the Internet of vehicles, which can integrate academic research, teaching platforms and industrial application together to realize integrated obstetric and academic. The platform can open the data analysis full link, ensures that the data application is high-efficient and falls to the ground, can abstract and encapsulate data operation logic in the platform, facilitates multiplexing of other people, finally obtains a plurality of instantiated algorithm nodes through multiplexing existing algorithms and fine adjustment logic, then establishes data flow connection relation with the instantiated nodes, realizes the data analysis flow meeting the self business requirement, and simultaneously visualizes the data analysis flow by the platform, realizes the visual and easy-to-use effects of data analysis staff and business staff, thereby improving the efficiency of data analysis of related staff and having very wide application prospect. For business personnel, the problems that the business personnel are difficult to customize algorithm behaviors and reuse the existing components when using a data analysis system are solved; for scientific researchers, the problem that the researcher hardly lands the researched and developed algorithm in a business system is solved; for teachers and students, the problem that the running environments are not matched and the algorithm logic is difficult to intuitively display is solved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram of an example of a data analysis flow developed using the integrated obstetric and research platform of the present application.
FIG. 2 is an overall architecture diagram of the platform of the present application;
fig. 3 is an external behavior framework diagram of a node of the present application.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved by the present application more clear, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The integrated platform for carrying out the data fusion analysis of the Internet of vehicles by supporting visual dragging is described. As shown in FIG. 1, an integrated platform for carrying out data fusion analysis of the Internet of vehicles supporting visual drag is disclosed, the algorithm logic of data analysis is packaged into reusable algorithm nodes, an Internet of vehicles data source is accessed into an access system in a mode of multiplexing the nodes, a plurality of algorithm nodes which are packaged in an abstract mode are allowed to be customized by a user according to requirements, then a unidirectional connection relation of data flow is created among the nodes after the nodes are instantiated, a data analysis flow formed by multiple nodes is formed, finally, an analysis flow capable of intuitively displaying the data flow is obtained, and quick deployment and operation are realized in a cloud platform.
The integrated platform for obstetric and research is composed of the following four core modules, the architecture relationship of which is shown in figure 2, and the relationship among different modules is shown.
And the node management module: new algorithm nodes can be created or existing algorithm nodes can be edited and all nodes can be managed. Each node needs to define its input data form and output data form, after which the node can calculate the input data by a program according to code logic in the node to obtain output data. The running logic of a specific node can be realized by custom writing codes meeting the form requirements, so that the problem that artificial intelligence is difficult to energize a data analysis flow is solved.
And a data stream construction module: the method supports the instantiation of different types of nodes into one project in the form of visual drag, so that the algorithm logic encapsulated by the nodes can be conveniently called, and the problem that the algorithm logic in the traditional data analysis platform is difficult to call is solved. Meanwhile, unidirectional connection relations are supported and established among the instance nodes to form a data analysis flow item, and connection dependency relations among the nodes can be intuitively seen.
Program operation connection module: the code program packaged in the node is connected with the code interpreter of the background service, so that the running of the node program and the background service share the memory, and the integration of debugging, developing and deploying of the platform is realized.
Developer community module: the individual developer is supported to release the encapsulated nodes into the community, and other people download and reuse the nodes, so that the problem that components of the traditional data analysis platform are difficult to reuse is solved.
Through the four core modules, the steps of using the integrated obstetric and research platform for data analysis project development comprise the following four steps:
step (1): encapsulating the data analysis logic algorithm into nodes;
step (2): developing a node for reading in internet of vehicles data;
step (3): connecting algorithm nodes to complete development of data analysis flow;
step (4): debugging and running the data analysis stream.
In step (1), in the integrated platform for research and development of the present application, the operation logic of one analysis stage of data analysis is implemented as a code segment (such as a segment of Python code), and the code segment is packaged into a node, and the data field types and formats of the input data and the output data of the node are customized, so that the node instance can execute the calculation on the received input data through the program logic defined by the code block in advance in the operation process, and the obtained calculation result is transmitted outwards through the customized output. Meanwhile, in order to implement configuration of a variable part (such as a connection address of a certain database) in program logic of a code block, a packaged node can explicitly declare a plurality of configuration items, when multiplexing the node, a user needs to fill a configuration value for each configuration item according to a specific environment of the user in a separate operation interface after instantiating the node, so as to specifically customize values of some parameter variables of the code block in actual operation according to an actual environment or actual needs. Thus, the outward behavior of one node is shown in fig. 3 below.
Researchers can flexibly package their own written program logic into reusable nodes and multiplex them into the development of other data analysis streams by modifying configuration items and defining input and output and even secondary development. The operation steps of a specific packaging node are as follows:
the first step: determining a name for the node for identifying the node;
and a second step of: writing a section of descriptive text for the node, so that other people can understand things and applicable scenes which the node does;
and a third step of: defining the type and form of input data and output data of the algorithm node according to the requirements;
fourth step: determining configuration items (namely field values which are required to be specifically determined according to the actual environment of a user) required by the algorithm node;
fifth step: programming the program running logic of the node in the form of codes, and converting the input data of the node into output data according to certain algorithm logic.
Through the steps, a node capable of running certain algorithm logic can be obtained, and a data stream for analyzing the data of the Internet of vehicles can be regarded as algorithm logic calculation of the original data through a plurality of nodes, and the logic calculation realizes the final required calculation result obtained from the original data. In most cases, development of the data analysis process is often multiplexed to work already done by others, while the completed data analysis logic is also multiplexed to other systems (e.g., sample classification using SVM algorithms may be required in multiple systems). But there is currently a lack of a platform that can intuitively and visually multiplex these developed program code fragments to complete a data analysis process. Therefore, the reusable code segments in the data analysis flow are packaged to obtain a node, the node is directly instantiated to the current analysis flow in a visual dragging mode in the data analysis flow needing to multiplex the code segments, and the development of the whole data analysis flow is completed by combining with other nodes, so that the nodes can be multiplexed for the second time, and the problem that the code segments are difficult to multiplex in the past is solved.
In the step (2), the integrated production and research platform connects the codes in the nodes with the code interpreter of the background service through a message queue, so that the running program of the nodes in the platform and the memory of the background service are shared, and the algorithm of the platform can use the running environment and the data computing capacity of the background service. And developing a node, establishing data connection with the Internet of vehicles by using an operation environment of a background service in the form of code fragments through reading files or reading databases, and importing data required to be processed by analyzing the Internet of vehicles data into a platform. The process can encapsulate an algorithm node specially used for reading certain types of data according to the encapsulation mode in the step (1), then in a specific data analysis project, a platform user only needs to select a required data source node, the node is instantiated into the current data analysis flow in a dragging mode in a visual interface of the platform, and then the data of the Internet of vehicles can be imported by modifying configuration items of the nodes.
In step (3), a complete data analysis flow is composed of a plurality of data analysis stages, and a plurality of algorithm nodes are needed to be combined together in the platform to complete the analysis of the original data. After the internet of vehicles data is accessed according to the step (2), a further data analysis process is still required for the source data, so that a data analysis personnel can create a new algorithm node specific to the current system or multiplex the existing algorithm node to develop a data analysis flow according to the mode described in the step (1). And a developer obtains a plurality of nodes which encapsulate the code fragments in a newly built or multiplexing mode according to the service requirement, the nodes form a node library, and the next step is to instantiate the nodes in the node library into the current project and establish connection relations between the instance nodes. Because each node has its own input and output, establishing a connection to the nodes connects the individual instance nodes by creating a unidirectional connection. If the node A and the node B are required to be connected, only a connection relation pointed by the node A to the node B needs to be created, and the connection relation is designated to map which part of the output of the node A to which part of the input of the node B, so that when the code of the node A is deployed and operated, output data flows into the input of the node B according to the mapping designated by the connection relation and is handed over to the node B for continuous processing. The data analysis flow obtained by the node connection mode has the characteristics of intuitiveness and flexibility, business personnel can see the trend of data flow and the macroscopic process of data analysis from the connection relation of algorithm nodes, and can multiplex the existing nodes in a dragging mode and integrate the existing nodes into the current data analysis project. After the project development is finished and the maintenance stage is entered, data analysts or scientific researchers can flexibly change the code implementation mode inside the node without influencing the stable operation of the whole project under the condition of not damaging externally exposed input and output.
The node connection mode is as follows:
the first step: the algorithm nodes (such as SVM algorithm nodes, mySQL connection nodes and the like) needed by the project to be developed are found by newly creating the node type or multiplexing the existing node type;
and a second step of: the needed node types are dragged into the currently developed project in a visual dragging mode, and node configuration items are filled in, so that the instantiation of the nodes is completed, and the nodes become instance nodes of the current project;
and a third step of: establishing a one-way connection relation between nodes with a logic relation, defining a mapping between output and input in the connection relation, and mapping output data of a previous node to input data of a next node, thereby realizing connection of the two nodes;
fourth step: repeating the third step until all the nodes with logic relation are connected.
In the step (4), the node codes are connected with the code interpreter of the background service through the message queue, and the data analysis platform can realize memory sharing with the background service, so that the node codes and the background service are in the same running environment (specifically, the same file system), the development and debugging environment of the data analysis flow is the same as the deployment environment, and the product delivery efficiency is improved. By means of memory sharing, the values of various variables of codes in algorithm nodes during running can be monitored by background services, so that developers can debug the codes in the background. This process reduces the cost of code debugging by maintaining consistency of memory space and operating environment.
After the development of the whole data analysis flow is completed in a debugging mode, users can run the project. After the project is operated, the node at the beginning (usually the node of the butt joint data source developed in the step (2)) starts to operate, and the output data of the node operation is mapped to the input of the next node through the node connection relation, so that the continuous operation of the next node is started. The connection of all the nodes forms a pipeline with a possible branch structure, and the operation process is repeated until the operation of all the nodes is completed, and the analysis result of the whole data analysis flow is obtained in the tail node.
The method comprises the steps of abstracting and packaging codes of algorithm logic into reusable nodes, defining input, output and configuration items of each algorithm node, and enabling a developer to modify the configuration items according to actual environments when multiplexing one node and multiplexing the node into construction of other data analysis flows in a visual dragging mode;
the method has the advantages that the unidirectional connection relation is built for the nodes packaged with the algorithm logic, the mapping between output data and input data is defined, the data circulation among the nodes is realized, the operation flow of the whole data analysis can be intuitively displayed, so that different people can be convenient to familiarize with business logic, the logic of part of the nodes can be quickly changed by hands when the demands change, the agile development is realized, and the problems that the developed code fragments are difficult to multiplex and the whole data analysis flow is difficult to embody in the development process of the data fusion analysis in the past are solved;
the data analysis platform is connected with the node codes and the code interpreter of the background service through the message queue to realize memory sharing of program operation, debugging development and product deployment are integrated, and product delivery efficiency is improved.
The integrated platform for obstetrics and research supports full-process operation from Internet of vehicles data acquisition, data access, data development, data analysis, model establishment, model operation and data application, and abstracts and encapsulates operation logic of different processes into algorithm nodes, a circulation process of data analysis flows is established and displayed on the platform in a visual mode, and meanwhile, the platform supports one-key operation of the data flows, so that not only is the convenience for researchers to debug and modify the operation logic, but also convenience is brought to operators to customize and multiplex the operator nodes according to actual services. In addition, the existing data sets or the existing algorithms in the developer community matched with the platform can be conveniently introduced into the development platform of the user in the form of encapsulating the data sets or the existing algorithms into nodes, so that service developers can multiplex the nodes into a plurality of data analysis flows. In addition, the platform can also serve the research and landing of the leading edge algorithm by scientific researchers and the visual and visual display of the algorithm by teaching staff. Therefore, the use of the Internet of vehicles data analysis platform can greatly improve the efficiency of data fusion analysis of developers, business personnel, scientific researchers, teaching personnel and the like.
The foregoing description of the preferred embodiments of the present application is not intended to be limiting, but is intended to cover any and all modifications, equivalents, and alternatives falling within the spirit and principles of the present application.
Claims (10)
1. An integrated platform for supporting visual dragging to perform data fusion analysis of internet of vehicles, which is characterized in that: the system comprises a node management module, a data stream construction module, a program operation connection module and a developer community module;
the node management module is used for creating new algorithm nodes or editing existing algorithm nodes and managing all the nodes;
the data stream construction module is used for supporting the instantiation of nodes of different types into a project in a visual dragging mode, and establishing a one-way connection relationship between the instance nodes to form a data analysis stream project;
the program running connection module is used for connecting the code program packaged in the node with a code interpreter of the background service, so that the running of the node program and the sharing of memory of the background service are realized, and the integration of debugging, development and deployment of the platform is realized;
the developer community module is used for supporting individual developers to issue the packaged nodes into communities, and other people download and multiplex the nodes.
2. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis of claim 1, wherein the integrated platform comprises: the node management module can create a new algorithm node in the node library, a platform user can package a section of code into a node according to the requirement of a specified form, define the data type and format of input data and output data for the node, and additionally define the configuration item of the node, so that the platform user can modify the parameter value in the configuration item according to the actual project scene, and then instantiate the node to convert the input data into output data through the operation of the code and output the output data.
3. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis of claim 1, wherein the integrated platform comprises: the node management module can edit any existing algorithm node, and modify and edit the algorithm node packaged by others according to specific requirements of others, so that the algorithm node is converted into a node library of the current project and used.
4. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis of claim 1, wherein the integrated platform comprises: the data flow construction module supports the instantiation of different node types in a node library into a current project, modifies a configuration item of a node to form an instantiation node, and then establishes a one-way connection relation between two instantiation nodes, wherein the relation defines the mapping from partial output data of a previous node to partial input data of a next node, realizes the data flow between the instantiation nodes, and establishes a connection relation among a plurality of nodes to finally form a data analysis flow project capable of completing the whole data analysis task.
5. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis of claim 1, wherein the integrated platform comprises: when the program operation connection module operates the project, the code encapsulated in the instantiation node is connected with a code interpreter of the back-end service through a message queue, so that the operation of the node program and the back-end service share a memory, when the node operates, the back-end service can monitor the specific value of each variable, and the operation state of each node in the project can be checked and debugged in the back-end service, thereby realizing the integration of debugging, development and deployment of the platform.
6. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis of claim 1, wherein the integrated platform comprises: the step of developing the data analysis project by the integrated obstetric and academic platform comprises the following steps:
step (1): encapsulating the data analysis logic algorithm into nodes;
step (2): developing a node for reading in internet of vehicles data;
step (3): connecting algorithm nodes to complete development of data analysis flow;
step (4): debugging and running the data analysis stream.
7. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis as defined in claim 6, wherein: in the integrated platform for obstetric and research, the operation logic of one analysis stage of data analysis is realized as a code segment, the code segment is packaged into a node, the data field types and formats of the input data and the output data of the node are customized, the received input data are calculated through program logic which is defined by a code block in advance in the operation process of the node instance, and the obtained calculation result is transmitted outwards through the customized output; meanwhile, configuring a variable part inside the program logic of the code block;
the self-written program logic is packaged into a reusable node, and the reusable node is multiplexed into the development of other data analysis streams by modifying configuration items and defining input and output and even secondary development modes; the operation steps of a specific packaging node are as follows:
the first step: determining a name for the node for identifying the node;
and a second step of: writing a section of descriptive text for the node, so that other people can understand things and applicable scenes which the node does;
and a third step of: defining the type and form of input data and output data of the algorithm node according to the requirements;
fourth step: determining configuration items required by the algorithm nodes;
fifth step: programming the program running logic of the node in the form of codes, and converting the input data of the node into output data according to certain algorithm logic.
8. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis as defined in claim 6, wherein: in the step (2), the integrated production and research platform connects the codes in the nodes with the code interpreter of the background service through a message queue, so that the running program of the nodes in the platform and the memory of the background service are shared, and the algorithm of the platform can use the running environment and the data computing capacity of the background service; and developing a node, establishing data connection with the Internet of vehicles by using an operation environment of a background service in the form of code fragments through reading files or reading databases, and importing data required to be processed by analyzing the Internet of vehicles data into a platform.
9. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis as defined in claim 6, wherein: in the step (3), the algorithm node connection mode is as follows:
the first step: searching algorithm nodes needed by a project to be developed by newly establishing the node type or multiplexing the existing node type;
and a second step of: the needed node types are dragged into the currently developed project in a visual dragging mode, and node configuration items are filled in, so that the instantiation of the nodes is completed, and the nodes become instance nodes of the current project;
and a third step of: establishing a one-way connection relation between nodes with a logic relation, defining a mapping between output and input in the connection relation, and mapping output data of a previous node to input data of a next node, thereby realizing connection of the two nodes;
fourth step: repeating the third step until all the nodes with logic relation are connected.
10. The integrated obstetric and research platform supporting visual drag for internet of vehicles data fusion analysis as defined in claim 6, wherein: in the step (4), the node codes are connected with a code interpreter of a background service through a message queue, and the data analysis platform can realize memory sharing with the background service so that the node codes and the background service are in the same running environment, thereby enabling the development and debugging environment of the data analysis flow to be the same as the deployment environment; by means of memory sharing, the values of various variables of the code in the algorithm node at run-time can be monitored by a background service, and the code is debugged in the background.
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| CN118093556A (en) * | 2024-04-28 | 2024-05-28 | 中国科学院西北生态环境资源研究院 | Method and device for constructing scientific research communities in frozen circle field based on data engineering |
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| CN118093556A (en) * | 2024-04-28 | 2024-05-28 | 中国科学院西北生态环境资源研究院 | Method and device for constructing scientific research communities in frozen circle field based on data engineering |
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