CN117951339A - Physical data point service modeling method and device for Internet of things - Google Patents
Physical data point service modeling method and device for Internet of things Download PDFInfo
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Abstract
A physical data point service modeling method of the Internet of things comprises the following steps: creating a hierarchical model tree comprising a plurality of nodes, each node having a corresponding business model; setting a modeling rule for each node of the plurality of nodes; setting attribute information of a service model of each node in the plurality of nodes respectively; setting a service model of physical data points; a service level management unit for constructing the level structure model tree step by step; and accessing the physical data point, and selecting a data point service model to which the physical data point belongs. The utility model also discloses a physical data point service modeling device of the Internet of things.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of the Internet of things, in particular to a physical data point service modeling method and device of the Internet of things.
Background
Along with the development of science and technology and society, the technology of digitalization and the internet of things are widely applied, so that the transformation of enterprises is promoted, and good economic and social benefits are brought.
In the technical field of the Internet of things, a production site is comprehensively perceived through intelligent monitoring instruments, sensors and the like, and data acquired by the intelligent monitoring instruments and the sensors are uploaded to an automatic control system through accessing physical data points, so that parameter monitoring and state monitoring are carried out in a production process, and production management and production decision making are assisted and supported.
However, since the automation control system is connected with a large number of intelligent monitoring meters and sensors, such as data acquisition equipment, SCADA (Supervisory Control And Data Acquisition, data acquisition and monitoring control system) systems, the structures of the data uploaded by the physical data points of the intelligent monitoring meters and sensors are different from each other, so that the automation control system has multi-source heterogeneous data (i.e. diversified data sources and differentiated data structures). In this case, the access of physical data points is complicated and the subsequent processing of the uploaded data is very heavy.
The uploaded data will be stored in a database and the different data will form different data structures in the database in the form of including data fields and meter numbers, i.e. different data tables. This data structure needs to be programmed separately and requires a lot of work in the subsequent processing of the data.
In addition, the number of physical data points acquired from the field instrument and the sensor is large, the service meaning is not available, and the problems that the technology is complicated to realize, the complexity is high, the maximum value of the data cannot be exerted and the like exist when the information system applies the acquired physical data points. Meanwhile, when the field device is newly added, the physical data point and the service data point of the newly added field device cannot be connected, and service meaning cannot be given to the physical data point, so that the field instrument and the sensor are difficult to expand after the Internet of things is built, the customization degree is low, the expandability is poor, and the maximum value of the data cannot be exerted.
Disclosure of Invention
At least one embodiment of the present disclosure provides a method for modeling physical data point business of the internet of things, including:
creating a hierarchical model tree comprising a plurality of nodes, each node having a corresponding business model;
Setting a modeling rule for each node of the plurality of nodes;
Setting attribute information of a service model of each node in the plurality of nodes respectively;
Setting a service model of physical data points;
a service level management unit for constructing the level structure model tree step by step; and
And accessing the physical data points, and selecting a data point service model to which the physical data points belong.
In one embodiment of the present disclosure, the hierarchical model tree includes at least a site management hierarchy.
In one embodiment of the present disclosure, the hierarchical model tree further comprises an administrative organization above the site management level.
In one embodiment of the disclosure, the physical data point service modeling method of the internet of things further includes: before creating the hierarchical model tree, a hierarchy is created.
In one embodiment of the present disclosure, the hierarchy includes: hierarchical structure name, hierarchical structure type, node type, child node type, whether data points are associated, whether device.
In one embodiment of the present disclosure, the modeling rules include:
The type of the node;
whether a child node is created for the node; and
In case of creating a child node for the node, the type of child node.
In one embodiment of the present disclosure, the attribute information of the traffic model of each node includes: attribute name, attribute operation type, length, data unit, and enumeration data value.
In one embodiment of the present disclosure, setting the business model of the physical data point includes: the fields of the physical data points carried by each hierarchical node are set.
In one embodiment of the present disclosure, the fields of the physical data points include: one or more of an identifier of a physical data point, a field name, an english name, a parameter type, a transmission type, a data unit, a field type, and an acquisition frequency.
In one embodiment of the present disclosure, the business level management unit for building the hierarchical model tree step by step includes:
And determining attribute information of each node based on the type of the service model of each node and the modeling rule of each node, constructing a hierarchical model of membership relations among all nodes of the hierarchical structure model tree, and constructing a service hierarchy management unit of the hierarchical structure model tree step by step.
In one embodiment of the present disclosure, accessing the physical data point, selecting a data point traffic model to which the physical data point belongs comprises: and when the physical data points are accessed, selecting a data point service model applied by the physical data points, and matching the physical data points with the service data points.
At least one embodiment of the present disclosure further provides an internet of things physical data point service modeling apparatus, including:
a hierarchical model tree creation module configured to create a hierarchical model tree comprising a plurality of nodes, each node having a corresponding business model;
A modeling rule setting module configured to set a modeling rule for each node in response to a user first input;
an attribute information setting module configured to set attribute information of a service model of each of the plurality of nodes in response to a user second input;
a physical data point business model setting module configured to set a business model of a physical data point in response to a third input from a user;
a service level construction module configured to construct a service level management unit of the hierarchical model tree step by step; and
And the selection module is configured to select a data point service model to which the physical data point belongs when the physical data point is accessed.
In one embodiment of the present disclosure, the hierarchical model tree includes at least a site management hierarchy.
In one embodiment of the present disclosure, the hierarchical model tree further comprises an administrative organization above the site management level.
In one embodiment of the disclosure, the internet of things physical data point business modeling apparatus further comprises a hierarchy creation module configured to create a hierarchy in response to a fourth input by a user.
In one embodiment of the present disclosure, the user first input includes: the type of node; whether to create a child node; and in the case of creating a child node, the type of the child node.
In one embodiment of the present disclosure, the user second input includes: one or more of an attribute name, an attribute operation type, a length, a data unit, and an enumeration data value.
In one embodiment of the present disclosure, the user third input includes: one or more of an identifier of a physical data point, a field name, an english name, a parameter type, a transmission type, a data unit, a field type, and an acquisition frequency.
In one embodiment of the disclosure, the service level construction module is configured to determine attribute information of each node according to attribute of the service model of each node based on a type of the service model of each node and a modeling rule of each node, construct a level model of membership between all nodes of the hierarchy model tree, and construct a service level management unit of the hierarchy model tree step by step.
In one embodiment of the present disclosure, the selection module is configured to select a data point traffic model to which the physical data point applies when accessing the physical data point, matching the physical data point with the traffic data point.
In one embodiment of the present disclosure, the physical data point business model setting module sets a business model of a physical data point comprising:
the physical data point business model setting module sets the fields of the physical data points carried by each hierarchical node.
At least one embodiment of the present disclosure also provides a non-volatile storage medium having stored thereon a computer program executable by a processor, the processor being configured to implement the operations of any of the above-described internet of things physical data point business modeling methods in response to the processor executing the computer program.
At least one embodiment of the present disclosure also provides a computer program product comprising a processor-executable program computer program, which when executed by a processor is configured to implement the operations of any of the above-described internet of things physical data point business modeling methods.
In the modeling method and the device for the physical data point service of the Internet of things according to the embodiment of the disclosure, the physical data point is corresponding to an enterprise administrative organization, an industrial management level, a production unit level, equipment, a data service point and the like, the service meaning of the physical data point is given, a data source and a decision basis are provided for other upper-layer service applications, and the purposes of improving quality, reducing cost and improving efficiency and maximizing data value are achieved. Compared with the traditional physical data point access management application, the method has the advantages of high efficiency, small workload and convenience in statistics application, retrieval and positioning. In addition, compared with the prior art that physical data points are added to an information system in a manual processing matching logic or massive data selection mode, a service model is added between the physical data points and the service data points, an applicable service model is selected, the belonging relation of the physical data points is constructed, the efficient, low-cost and low-code research and development access of the physical data points can be realized, and comprehensive digital and intelligent management and control are realized for enterprises.
Drawings
FIG. 1 illustrates a flow chart of a method of modeling an Internet of things physical data point business according to one embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a method of modeling an Internet of things physical data point business according to yet another embodiment of the present disclosure;
FIG. 3 schematically illustrates a block diagram of a physical data point business modeling apparatus of the Internet of things according to one embodiment of the disclosure; and
Fig. 4 schematically illustrates a block diagram of an internet of things physical data point business modeling apparatus according to yet another embodiment of the present disclosure.
Detailed Description
The application is further described in detail below by means of the figures and examples. The features and advantages of the present application will become more apparent from the description.
The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. Although various aspects of the embodiments are illustrated in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
In addition, the technical features described below in the different embodiments of the present application may be combined with each other as long as they do not collide with each other.
The internet of things monitors meters and sensors installed on a production site, realizes comprehensive perception of the production site, and provides monitoring functions of production parameters and state parameters for production by accessing physical data points (i.e. physical data of the meters or the sensors), so that assistance and support are carried out for production management and decision making.
However, since the meters and the sensors are disposed at different locations on the production site, the data formats of the physical data points of the meters and the sensors are different, and the data collected by the physical data points of the meters and the sensors are uploaded to a database for storage, but it is difficult to clearly know from which location the data is the meter or the sensor when viewing the data, and the actual meaning of the data is not clear, and the relationship between the data and the production parameters is not clear. In addition, since these data are stored together, manual viewing or separate programming is required when viewing the data of a certain meter or sensor is required, which is labor intensive.
Therefore, there is a need to design business models for the physical data points of these meters and sensors, and to be able to establish a link between the physical data points and their corresponding business models, giving business implications to the physical data points.
In this disclosure, physical data points refer to points disposed in meters or sensors that are used to make measurements on a production site, which may generate data reflecting conditions of the production site. In the present disclosure, the business model refers to a data format set for physical data points according to circumstances, and data of the physical data points stored in a database according to the data format can clearly reflect business circumstances.
To solve the above problems, at least one embodiment of the present disclosure provides a method for modeling an internet of things physical data point service, as shown in fig. 1, including:
s01, creating a hierarchical structure model tree, wherein the hierarchical structure model tree comprises a plurality of nodes, and each node is provided with a corresponding service model;
S02, modeling rules are respectively set for the plurality of nodes;
s03, respectively setting attribute information of a service model of each node in the plurality of nodes;
S04, setting a service model of physical data points;
S05, constructing a service level management unit of the level structure model tree step by step; and
S06, accessing the physical data points, and selecting a data point service model to which the physical data points belong.
In practice, a hierarchical model tree is first created at S01, in which a number of business models are included, which form nodes in the hierarchical model tree.
The hierarchical model tree may customize the tiers and node types for each tier, including at least a site management tier, for example. In the production field, the field management level may be a factory management level or a production unit management level, and the production management unit may be a production line or a workshop. In general, the plant management hierarchy will include equipment, process units, production lines, workshops, and plants, which can minimally enable monitoring of production sites and business modeling of physical data points. In a practical scenario, the largest unit in many small organizations is a plant, so that the hierarchical model tree built for these plants may include only equipment, process units, production lines, workshops, and plants. In the scientific research field, the field management level may be the management level of a certain number of test tables, or may be the management level of a certain number of laboratories. In the field of environmental monitoring, the field management level may be a management level of a certain water area, or may be a management level of all water areas of a certain large administrative area. The field management level of the hierarchical model tree is described above by taking the production field, the scientific research field, and the environmental monitoring as examples, and the embodiments of the present disclosure are not limited thereto.
In some embodiments, the hierarchical model tree may further include an administrative organization on the site management hierarchy paper. For example, an area to which the plant belongs, a business block to which the plant belongs, a group to which the plant belongs, and the like. In this way, monitoring of the production site can be achieved over a larger range, and business modeling of physical data points can be performed over a larger range.
According to the actual situation of the site and the administrative management framework of the site, a hierarchical structure model tree can be constructed.
For example, for a sensor set up for a first process unit of a first line of assembly plants of a first plant of a northeast large area of SUV business slabs of a group, a hierarchical model tree may be constructed comprising, from a root node to a leaf node: a cluster, SUV business tile, northeast large area, first factory, assembly shop, first production line, first process unit, sensor, physical data points disposed on the sensor.
According to the same concept, a plant-level model tree may be constructed for each sensor installed throughout a cluster, such that each sensor and its physical data points are represented in the plant-level model tree, clearly looking at where each sensor and its physical data points are located.
For another example, for a small organization, such as an a plant, a sensor installed in a first process unit of a first production line of a first plant thereof, when constructing a hierarchical model tree including, from a root node to a leaf node: a factory, a first plant, a first production line, a first process unit, a sensor, and physical data points disposed on the sensor. Thus, the location of each sensor and its physical data point can be clearly determined.
For each node on the hierarchical model tree, a business model is provided that is applicable to that node. The business model refers to a data format set for physical data points according to a hierarchical structure of nodes, and data of the physical data points stored in a database according to the data format can clearly reflect business data.
Fig. 2 illustrates a flow chart of an internet of things physical data point business modeling method according to yet another embodiment of the present disclosure. As shown in fig. 2, before constructing the hierarchical structure model tree, the physical data point service modeling method of the internet of things further includes: s00, creating a hierarchical structure.
Generally, the structure of the hierarchy includes: hierarchy name, hierarchy type, whether data points are associated, whether device. In one embodiment of the present disclosure, the hierarchy name is unique, not null. The hierarchical name can support 50 characters at maximum. For the hierarchy name, it also supports special character checking, supporting combinations of chinese, english, numbers, "-", "_", "@," blank ", must start with chinese, english or numbers. The hierarchy type is an enumerated value, which may be, for example, a plant model hierarchy, predetermined. At the same time, it can be selected whether the hierarchy is associated with a data point, whether it is a device.
In one example of a hierarchy, the hierarchy name is a plant model hierarchy, the hierarchy type is a plant model hierarchy, and data points are associated, although unassociated data points may be provided.
After the hierarchically structured model tree is created, modeling rules need to be set for each node in the plant hierarchically structured model tree.
In an embodiment of the present disclosure, the modeling rules for each node include: the type of the node; whether a child node can be created for the node; and, in the case where the child node can be created, the type of the child node.
In one embodiment of the present disclosure, the modeling rules include a type of node; a child node can be created for the node; and in the case where the child node can be created, the type of the child node. In one embodiment of the present disclosure, the modeling rules may also include a hierarchy type and hierarchy.
In one embodiment of the present disclosure, taking the example of a factory hierarchy model tree of factory a, the hierarchy structure name of which is the hierarchy structure of factory a hierarchy, has eight levels in total, node type names are respectively a group, a plate, an area, a factory, a workshop, a production line, a process unit and equipment, and before a factory node, a child node type name of each level node is a node type name of the next level, for a factory hierarchy, the child node type name thereof may be a workshop, a production line or a process unit, which is to reserve a sufficient margin in designing a business model considering the case that the workshop, the production line and the process unit may need to be directly checked at the factory level. And after the plant node, the child node type name of each level node is the node type name of the next level. For the leaf node device, it has no child node, one item of its child node type name is null, and if it is set as the device node, one item is yes, it means that the node is the lowest level node, it has no child node, and at the same time, the node is the device node. The node type names represent names of node types, are input character types, are unique under a certain level and are necessary to fill in items. In some embodiments, a length check may be set for the node type name, for example, it may be checked whether the length of the input character type exceeds a certain preset length, for example, 50 characters, or a special character check may be set to prevent certain special characters from being input.
For a child node type name, which indicates the type of child node, a node may have multiple child nodes. In some embodiments, a length check may be set for the child node type name, for example, it may be checked whether the length of the entered character type exceeds a certain preset length, for example, 50 characters, or a special character check may be set to prevent certain special characters from being entered.
Whether the associated data point is a filling item or not, if not, the data point is defaulted to be 'no', if yes, the data point is allowed to be associated by the class node, and if no, the data point is not allowed to be associated by the class node.
Whether the device node is set as the option is defaulted as 'no' under the condition of not filling, and 'yes' or 'no' can be filled under the condition of filling, the node is indicated to be the device node under the condition of filling 'yes', and the node is indicated to be not the device node under the condition of filling 'no'.
In one embodiment of the present disclosure, the attribute information of the service model of each of the plurality of nodes includes: attribute name, attribute operation type, length, data unit, and enumerated data value, where the attribute name represents the name of the business model.
In one embodiment of the present disclosure, the attribute operation type may include one of an input type, a single type, a multiple type, a date type, a picture type, and a file type. In one embodiment of the present disclosure, the data units include m 2, kw·h, and the like. In the case where the attribute operation type is single-choice or multi-choice, the selectable attribute enumeration values need to be defined accordingly in the enumeration data values.
In one embodiment of the present disclosure, in S04, setting a business model of the physical data point includes: the fields of the physical data points carried by each hierarchical node are set.
In one embodiment of the present disclosure, the field of the physical data point includes one or more of an Identifier (ID) of the physical data point, a field name, an english name, a parameter type, a transmission type, a data unit, a field type, and an acquisition frequency.
The ID of a physical data point is a symbol used to identify the physical data point. The field names are chinese names used as meaning of display services in the generated user interface. English names are used as header names in the generated data tables. The parameter type is used to identify the type of data generated by the physical data point, such as real-time data or alarm data. The transmission type includes a shift data type and a time sequence data type, wherein the shift data type refers to data which is generated when the state is changed, for example, data generated when the state of a switch is changed, and the time sequence data type refers to data uploaded by physical data points of the device every time period. The data units may include A, V, kW, kW.h, DEG C, m 3, and the like. The field type is a data type of data generated by the physical data points, and may be LONG, FLOAT, BOOL, UINT, UINT32, INT16, INT32, STRING, DOUBLE, and the like, for example. The sampling frequency refers to the frequency at which physical data points sample and upload data, and may be, for example, 5s, 1min, 5min, 15min, etc. The embodiments of the present disclosure are explained above by way of various examples with respect to field names, english names, parameter types, transmission types, data units, field types, acquisition frequencies, but the embodiments of the present disclosure are not limited thereto and may be adjusted according to specific situations.
In one embodiment of the present disclosure, in S05, based on the type of the service model of each node and the modeling rule of each node, attribute information of each node is determined according to the service model attribute of each node, a hierarchical model of membership between all nodes of the hierarchical model tree is constructed, and a service level management unit of the hierarchical model tree is constructed step by step.
In one embodiment of the present disclosure, in S06, accessing the physical data point, selecting a data point traffic model to which the physical data point belongs includes: and when the physical data points are accessed, selecting a data point service model applied by the physical data points, and matching the physical data points with the service data points. And constructing a attribution relation between the service data points and the plant model hierarchical nodes, and setting service meanings for the physical data points.
In the modeling method for the physical data point service of the Internet of things according to the embodiment of the disclosure, the physical data point is corresponding to an enterprise administrative organization, an industrial management level, a production unit level, equipment, a data service point and the like, the meaning of the physical data point service is given, a data source and a decision basis are provided for other upper-layer service applications, and the purposes of improving quality, reducing cost and improving efficiency and maximizing data value are achieved. Compared with the traditional physical data point access management application, the method has the advantages of high efficiency, small workload and convenience in statistics application, retrieval and positioning. The system can realize high-efficiency, low-cost and low-code research and development access, and realize comprehensive digital and intelligent management and control for enterprises.
At least one embodiment of the present disclosure also provides an internet of things physical data point business modeling apparatus 300. As shown in fig. 3, the physical data point service modeling apparatus 300 of the internet of things includes:
A hierarchical model tree creation module 301 configured to create a hierarchical model tree comprising a plurality of nodes, each node having a respective business model;
a modeling rule setting module 302 configured to set a modeling rule for each node in response to a user first input;
an attribute information setting module 303 configured to set attribute information of a service model of each of the plurality of nodes in response to a user second input;
a physical data point business model setting module 304 configured to set a business model of a physical data point in response to a third input from a user;
A service level construction module 305 configured to construct a service level management unit of the hierarchical model tree step by step; and
A selection module 306 is configured to select, when accessing the physical data point, a data point traffic model to which the physical data point belongs.
The hierarchical model tree creation module 301 creates a hierarchical model tree in which a plurality of business models are included, which form nodes in the hierarchical model tree.
The hierarchical model tree includes at least a field management hierarchy. For example, in the production field, the site management hierarchy may be a factory management hierarchy or a production unit management hierarchy. For example, the plant management hierarchy may be equipment, process units, production lines, workshops, and plants such that monitoring of production sites and business modeling of physical data points may be accomplished at a minimum. In a practical scenario, the largest unit in many small organizations is a plant, so that the hierarchical model tree built for these plants may include only equipment, process units, production lines, workshops, and plants. In the above, the field management hierarchy has been described and illustrated by taking the production field as an example, but the embodiments of the present disclosure are not limited to the production field.
In some embodiments, the hierarchical model tree may also include an administrative organization above the field management level. For example, an area to which the plant belongs, a business block to which the plant belongs, a group to which the plant belongs, and the like. In this way, the monitoring of the field can be realized on a larger scale, and the service modeling of the physical data points can be performed on a larger scale.
According to the actual situation of the site and the administrative management framework of the site, a hierarchical structure model tree can be constructed.
In one embodiment of the present disclosure, as shown in fig. 4, the internet of things physical data point business modeling apparatus 300 further includes a hierarchy creation module 307, the hierarchy creation module 307 configured to create a hierarchy in response to a fourth input by a user. For a description of the hierarchical structure, please see above.
The user fourth input identifies the name of the hierarchy, which can support up to 50 characters. When the hierarchy creation module 307 creates a hierarchy, an annotation may also be entered for each hierarchy in response to a fifth input by the user. Additionally, when the hierarchy creation module 707 creates a hierarchy, it may be further configured to select, for each hierarchy, whether to associate a data point, whether to be a device, in response to a sixth input by the user.
For modeling rule settings module 302, the first input by the user includes: the type of node; whether to create a child node; and in the case of creating a child node, the type of the child node. The first input of the user may also include a hierarchy type and hierarchy. The modeling rule setting module 302 sets modeling rules for each node in response to a first input from a user. For specific details on the type of node, whether child nodes are created, the type of child node, the hierarchy type and the hierarchy, see description above.
The attribute information setting module 303 is configured to set attribute information of a business model of each of the plurality of nodes in response to a user second input. The user second input includes an attribute name, an attribute operation type, a length, a data unit, and an enumerated data value. Wherein the attribute name represents the name of the business model. The user second input constitutes attribute information of a business model of each of the plurality of nodes.
In particular implementations, the attribute operation type may include one of an input type, a single type, a multiple type, a date type, a picture type, and a file type. In one embodiment of the present disclosure, the data units include m 2, kw·h, and the like. In the case of an attribute operation type, selectable attribute enumeration values may be defined accordingly in the enumeration data values.
The physical data point business model setting module 304 is configured to set a business model of a physical data point in response to a third input from a user. More specifically, the physical data point business model setting module 304 is configured to set the fields of the physical data points carried by each hierarchical node in response to a third input from the user.
The user third input includes one or more of an Identifier (ID) of the physical data point, a field name, an english name, a parameter type, a transmission type, a data unit, a field type, and a collection frequency.
The ID of a physical data point is a symbol used to identify the physical data point. The field names are chinese names used as meaning of display services in the generated user interface. English names are used as header names in the generated data tables. The parameter type is used to identify the type of data generated by the physical data point, such as real-time data or alarm data. The transmission type includes a shift data type and a time sequence data type, wherein the shift data type refers to data which is generated when the state is changed, for example, data generated when the state of a switch is changed, and the time sequence data type refers to data uploaded by physical data points of the device every time period. The data units include A, V, kW, kW.h, DEG C, m 3, etc. The field type is a data type of data generated by the physical data points, and may be LONG, FLOAT, BOOL, UINT, UINT32, INT16, INT32, STRING, DOUBLE, and the like, for example. The sampling frequency refers to the frequency at which physical data points sample and upload data, and may be, for example, 5s, 1min, 5min, 15min, etc. The above description is merely for the purpose of illustrating embodiments of the present disclosure, which are not limited thereto.
The service level construction module 305 is configured to build service level management units of the hierarchical model tree in stages. The service level construction module 305 determines attribute information of each node according to the attribute of the service model of each node based on the type of the service model of each node and the modeling rule of each node, constructs a level model of membership between all nodes of the level structure model tree, and constructs a service level management unit of the level structure model tree step by step.
The selection module 306 is configured to select, upon accessing the physical data point, a data point traffic model to which the physical data point belongs. Specifically, when accessing a physical data point, the selection module 306 selects a data point traffic model applied by the physical data point, matching the physical data point with the traffic data point. Thus, a home relationship between the service data point and the device can be constructed, and the service meaning can be set for the physical data point.
In the physical data point service modeling device of the internet of things according to the embodiment of the disclosure, physical data points are corresponding to an enterprise administrative organization, a site management level, equipment, a data service point and the like, the meaning of the physical data point service is given, a data source and a decision basis are provided for other upper-layer service applications, and the purposes of improving quality, reducing cost and improving efficiency and maximizing data value are achieved. Compared with the traditional physical data point access management application, the method has the advantages of high efficiency, small workload and convenience in statistics application, retrieval and positioning. The system can realize high-efficiency, low-cost and low-code research and development access, and realize comprehensive digital and intelligent management and control for enterprises.
At least one embodiment of the present disclosure also provides a non-volatile storage medium having a computer program stored thereon that, in response to being executed by a processor configured to implement the operations of any of the internet of things physical data point business modeling methods described above.
At least one embodiment of the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, is configured to implement the operations of any of the above-described internet of things physical data point business modeling methods.
In the description of the present application, it should be noted that the directions or positional relationships indicated by the terms "upper", "lower", "inner", "outer", "front", "rear", "left", "right", etc. are directions or positional relationships based on the operation state of the present application are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements to be referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application.
In the description of the present application, it should be noted that the terms "mounted," "connected," and "connected" are to be construed broadly, unless otherwise specifically defined and limited. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
The application has been described above in connection with preferred embodiments, which are, however, exemplary only and for illustrative purposes. On this basis, the application can be subjected to various substitutions and improvements, and all fall within the protection scope of the application.
Claims (23)
1. A physical data point service modeling method of the Internet of things comprises the following steps:
creating a hierarchical model tree comprising a plurality of nodes, each node having a corresponding business model;
Setting a modeling rule for each node of the plurality of nodes;
Setting attribute information of a service model of each node in the plurality of nodes respectively;
Setting a service model of physical data points;
a service level management unit for constructing the level structure model tree step by step; and
And accessing the physical data points, and selecting a data point service model to which the physical data points belong.
2. The internet of things physical data point business modeling method of claim 1, wherein the hierarchical model tree comprises at least a field management hierarchy.
3. The internet of things physical data point business modeling method of claim 2, wherein the hierarchical model tree further comprises an administrative organization above the field management level.
4. The internet of things physical data point business modeling method of claim 1, further comprising: before creating the hierarchical model tree, a hierarchy is created.
5. The internet of things physical data point business modeling method of claim 4, wherein the hierarchy comprises: hierarchical structure name, hierarchical structure type, node type, child node type, whether data points are associated, whether device.
6. The internet of things physical data point business modeling method of claim 1, wherein the modeling rules comprise:
The type of the node;
whether a child node is created for the node; and
In case of creating a child node for the node, the type of child node.
7. The internet of things physical data point business modeling method of claim 1, wherein the attribute information of the business model of each node comprises: attribute name, attribute operation type, length, data unit, and enumeration data value.
8. The method of modeling an internet of things physical data point business according to any of claims 1 to 7, wherein setting a business model of the physical data point comprises: the fields of the physical data points carried by each hierarchical node are set.
9. The internet of things physical data point business modeling method of claim 8, wherein the fields of the physical data point comprise: one or more of an identifier, a field name, an english name, a parameter type, a transmission type, a data unit, a field type, and an acquisition frequency.
10. The method for modeling physical data point traffic of the internet of things according to any one of claims 1 to 7, wherein the traffic level management unit for constructing the hierarchical model tree step by step comprises:
And determining attribute information of each node based on the type of the service model of each node and the modeling rule of each node, constructing a hierarchical model of membership relations among all nodes of the hierarchical structure model tree, and constructing a service hierarchy management unit of the hierarchical structure model tree step by step.
11. The internet of things physical data point business modeling method of claim 1, wherein accessing the physical data point, selecting a data point business model for the physical data point comprises: and when the physical data points are accessed, selecting a data point service model applied by the physical data points, and matching the physical data points with the service data points.
12. An internet of things physical data point business modeling apparatus, comprising:
a hierarchical model tree creation module configured to create a hierarchical model tree comprising a plurality of nodes, each node having a corresponding business model;
A modeling rule setting module configured to set a modeling rule for each node in response to a user first input;
an attribute information setting module configured to set attribute information of a service model of each of the plurality of nodes in response to a user second input;
a physical data point business model setting module configured to set a business model of a physical data point in response to a third input from a user;
a service level construction module configured to construct a service level management unit of the hierarchical model tree step by step; and
And the selection module is configured to select a data point service model to which the physical data point belongs when the physical data point is accessed.
13. The internet of things physical data point business modeling apparatus of claim 12, wherein the hierarchical model tree comprises at least a field management hierarchy.
14. The internet of things physical data point business modeling apparatus of claim 13, wherein the hierarchical model tree further comprises an administrative organization above the site management level.
15. The internet of things physical data point traffic modeling apparatus of claim 12, further comprising a hierarchy creation module configured to create a hierarchy in response to a fourth input by a user.
16. The internet of things physical data point traffic modeling apparatus of claim 12, wherein the user first input comprises: the type of node; whether to create a child node; and in the case of creating a child node, the type of the child node.
17. The internet of things physical data point traffic modeling apparatus of claim 12, wherein the user second input comprises: one or more of an attribute name, an attribute operation type, a length, a data unit, and an enumeration data value.
18. The internet of things physical data point traffic modeling apparatus of claim 12, wherein the user third input comprises: one or more of an identifier of a physical data point, a field name, an english name, a parameter type, a transmission type, a data unit, a field type, and an acquisition frequency.
19. The physical data point service modeling apparatus of the internet of things according to claim 12, wherein the service level construction module is configured to determine each node attribute information according to the service model attribute of each node based on the type of the service model of each node and the modeling rule of each node, construct a level model of membership between all nodes of the hierarchy model tree, and construct a service level management unit of the hierarchy model tree step by step.
20. The internet of things physical data point traffic modeling apparatus of claim 12, wherein the selection module is configured to select a data point traffic model to which the physical data point applies when accessing the physical data point, matching the physical data point with the traffic data point.
21. The internet of things physical data point business modeling apparatus of any of claims 12 to 20, wherein the physical data point business model setting module sets a business model of a physical data point comprising:
the physical data point business model setting module sets the fields of the physical data points carried by each hierarchical node.
22. A non-volatile storage medium having stored thereon a computer program executable by a processor, the processor being configured to implement the operations of the internet of things physical data point business modeling method of any of claims 1 to 11 in response to the processor executing the computer program.
23. A computer program product comprising a processor-executable program computer program which, when executed by a processor, is configured to implement the operations of the internet of things physical data point traffic modeling method of any of claims 1 to 11.
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