CN114662629B - Method and device for identifying industrial code in multi-level node structure - Google Patents
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Abstract
The application relates to the technical field of identification and discloses a method for identifying an industrial code in a multi-level node structure, wherein the multi-level node is a topological structure consisting of enterprise nodes, secondary nodes and national nodes; the method comprises the following steps: recording the identification registration information of the product in each level of nodes, and updating the identification registration information of the nodes in real time; the AR workbench analyzes the industrial code through the enterprise node and returns the analyzed identification registration information to the AR workbench; calculating the class characteristic vector of the product in the enterprise node according to the analyzed identification registration information; when the position of the product class feature vector is triggered to need to expand the class, the similar classes of the superior nodes are issued to the enterprise nodes; and optimizing the categories stored in the enterprise nodes at regular time. The technical problem of time required for analyzing and tracking the industrial Internet identification in the multi-stage nodes is solved. The application also discloses an apparatus for identifying an industrial code in a multi-level node structure.
Description
Technical Field
The present application relates to the field of identification technology, and for example, to a method and apparatus for identifying an industrial code in a multi-level node structure.
Background
The industrial internet identification is widely applied to the mobile internet and the internet of things, and identification, analysis and tracking of the identification can be realized by scanning industrial codes including two-dimensional codes and bar codes. With the ever-expanding application scenes and range of industrial internet identification and the popularization of AR (Augmented Reality) technology, the need arises for a plurality of platforms to recognize the same industrial code together and to analyze and track the industrial code through AR recognition.
In the prior art, the industrial code is usually analyzed and tracked in one platform, and when a plurality of platforms analyze and track the same industrial code together, the requirement of analyzing and tracking the industrial code without delay is difficult to meet due to information interaction among the platforms.
Disclosure of Invention
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of such embodiments but rather as a prelude to the more detailed description that is presented later.
The disclosed embodiment provides a method and a device for identifying an industrial code in a multi-level node structure, wherein a topological structure comprising enterprise nodes, secondary nodes and country-level nodes is constructed, categories in the secondary nodes are issued to the enterprise nodes, and the industrial code is analyzed in the enterprise nodes to obtain identification registration information, so that the time required for analyzing and tracking the industrial internet identification can be shortened, and the delay is reduced.
In some embodiments, the method comprises: the multi-level nodes are topological structures which are formed by enterprise nodes, second-level nodes and national-level nodes and collect the identification registration information step by step, a plurality of classes which divide products according to class characteristic vectors are arranged in the nodes, and the class characteristic vectors consist of industry fields, identification types and regions; the method comprises the following steps: recording the identification registration information of the product in each level of nodes, and updating the identification registration information of the nodes in real time; the augmented reality AR workbench analyzes the industrial code through the enterprise node and returns the analyzed identification registration information to the AR workbench; calculating the class characteristic vector of the product in the enterprise node according to the analyzed identification registration information; when the position of the product class feature vector is in the condition that the class needs to be expanded by triggering, the similar class of the superior node is issued to the enterprise node, and the method comprises the following steps: setting an area where the category characteristic vector exceeding the preset length is located as a threshold area in an enterprise node, and setting an expanded category reference point at a superior node along the direction of the category characteristic vector; under the condition that the position of the product class feature vector is in a threshold value area, the superior node searches for similar classes according to the expanded class reference point; the superior node issues the similar categories to the enterprise node; optimizing the categories stored in the enterprise nodes at regular time; wherein, in the enterprise node will exceed the grade eigenvector regional setting of preset length as the threshold value region, set up along the higher level node of grade eigenvector direction and enlarge the grade reference point, include: threshold regionCalculating an upper quartile Q3, a median Q2, a lower quartile Q1 and an upper limit value ULV of the classification feature vector for a region range formed by the classification feature vector, wherein a region formed by the classification feature vector with the length larger than the upper quartile Q3 is a threshold region, and a point with the length of the upper limit value ULV is an expanded classification reference point of an upper node, wherein the position of Qi is = i ^
I =1, 2, 3; n represents the number of terms contained in the sequence, Q1=0.25 × term +0.75 × term, where the term in 0.25 × 0 term is the term value corresponding to the position of Q1 rounded, and the term in 0.75 × 1 term is the term value corresponding to the position of Q1 rounded + 1; q2=0.5 × 2 terms +0.5 × 3 terms, where the first 0.5 × 4 term is the term value corresponding to the position of Q2 rounded, and the second 0.5 × term is the term value corresponding to the position of Q2 rounded + 1; q3=0.75 × item +0.25 × item, and of the Q3=0.75 × item +0.25 × item, the item in the 0.75 × item is the item value corresponding to the position where Q3 is located, and the item in the 0.25 × item is the item value corresponding to the position where Q3 is located, by rounding +1, where the quartile distance IQR, IQR = Q3-Q1, and ULV = Q3+1.5 × IQR.
Optionally, the recording of the identification registration information of the product in each level of node includes: the identification registration information is sent to the enterprise node in a lightweight data exchange format JSON format and is recorded in the enterprise node; the enterprise node sends the identification registration information to the superior node and records the identification registration information in the superior node until the superior node is a national node.
Optionally, the updating, in real time, the identifier registration information of the node includes: the updating information of the identification registration information is sent to the enterprise node by adopting a JSON format and is recorded in the enterprise node; the enterprise node sends the update information of the identification registration information to the superior node and records the update information of the identification registration information in the superior node until the superior node is a country node.
Optionally, the augmented reality AR workstation parses the industrial code through the enterprise node, and returns the parsed identification registration information to the AR workstation, including: the AR workbench scans the industrial codes and transmits the industrial codes to the enterprise nodes; the enterprise node analyzes the industrial code and inquires corresponding identification registration information; the enterprise node returns the inquired identification registration information to the AR workbench; the AR workbench displays the query results.
Optionally, the calculating, in the enterprise node, a class feature vector to which the product belongs according to the parsed identification registration information includes: and analyzing the identification registration information in the enterprise node, and taking the analyzed values of the industry field, the identification type and the region as the class characteristic vector of the product.
Optionally, the identifier registration information of the categories stored in the timing optimization enterprise node includes: and in the enterprise node, inquiring the use conditions of all products at regular time, and deleting the unused categories exceeding the preset time.
Optionally, in the case that the required identification registration information is not contained in the enterprise node, the identification registration information is inquired to the upper level node until the country level node.
In some embodiments, the apparatus comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform any one of the above methods for identifying industrial code in a multi-level node structure.
Because the products processed in the logistics process have the similarity in the aspects of industry field, identification type and region, when the AR workbench analyzes the industrial code through the enterprise node, if the analyzed identification registration information reaches the condition that the categories need to be expanded, the similar categories in the superior node are issued to the enterprise node, the categories in the enterprise node are expanded, the times of searching the database and the data transmission time between the enterprise node and the secondary node are reduced, the speed of analyzing the industrial code is increased, and the delay is reduced.
The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.
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One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the accompanying drawings and not in limitation thereof, in which elements having the same reference numeral designations are shown as like elements and not in limitation thereof, and wherein:
FIG. 1 is a multi-level block diagram of a method for identifying an industrial code in a multi-level node structure provided by an embodiment of the present disclosure;
FIG. 2 is a graph of threshold regions at various levels of a method for identifying an industrial code in a multi-level node structure provided by an embodiment of the present disclosure;
FIG. 3 is a flow chart of a method for identifying an industrial code in a multi-level node structure provided by an embodiment of the present disclosure;
FIG. 4a is a diagram of an expanded enterprise node class architecture for a method of identifying an industrial code in a multi-level node structure according to an embodiment of the present disclosure;
FIG. 4b is a flowchart of an expanded enterprise node class for a method of identifying an industrial code in a multi-level node structure according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of resolving an industrial code and expanding categories of the industrial code in a method for identifying the industrial code in a multi-level node structure according to an embodiment of the present disclosure.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The terms "first," "second," and the like in the description and in the claims, and the above-described drawings of embodiments of the present disclosure, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure described herein may be made. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion.
The term "plurality" means two or more unless otherwise specified.
In the embodiment of the present disclosure, the character "/" indicates that the preceding and following objects are in an or relationship. For example, A/B represents: a or B.
The term "correspond" may refer to an association or binding relationship, and a corresponds to B refers to an association or binding relationship between a and B.
Referring to fig. 1, a multi-level structure diagram of a method for identifying an industrial code in a multi-level node structure according to an embodiment of the present disclosure includes:
the enterprise nodes, the second-level nodes and the national-level nodes are of a multi-level topological structure. A plurality of enterprise nodes are connected with a secondary node, and the enterprise nodes can also be directly connected with the national level nodes. Each node comprises a plurality of categories, and the categories comprise a plurality of products of similar industry fields, identification types and regions. The identification registration information of the product is firstly registered to the enterprise node, then is mapped to the second level node from the enterprise node, and finally is mapped to the country level node from the second level node.
Therefore, when the industrial code is analyzed, the enterprise node is firstly analyzed and corresponding identification registration information is searched, and if the enterprise node does not contain the corresponding identification registration information, the enterprise node can search the identification registration information from the upper node step by step. The multi-level topology of the hierarchical storage may maintain a large amount of identity registration information.
Referring to fig. 2, a threshold area map of each level of a method for identifying an industrial code in a multi-level node structure according to an embodiment of the present disclosure includes:
the enterprise node 1 is an area surrounded by an enterprise node area boundary 12, and an enterprise node threshold area 11 is preset inside the enterprise node area boundary 12. The outer side of the enterprise node 1 is provided with a secondary node 2, the secondary node 2 is an area surrounded by a secondary node area boundary 22, and the inner side of the secondary node area boundary 22 is provided with a preset secondary node threshold area 21. The outer side of the second-level node 2 is provided with a country-level node 3, and the country-level node 3 is an area surrounded by a country-level node area boundary 31.
Thus, the enterprise node threshold region 11 is a preset region, when the class to which the analyzed product belongs is in the enterprise node threshold region 11, the similar class can be searched for in the secondary node and issued to the enterprise node 1, so that the number of the similar class in the enterprise node can be increased, and the subsequent query of the identification registration information can be limited in the enterprise node 1.
Referring to fig. 3, a flowchart of a method for identifying an industrial code in a multi-level node structure according to an embodiment of the present disclosure includes:
and S01, recording the identification registration information of the product in each level of node, and updating the identification registration information of the node in real time.
And S02, the AR workbench analyzes the industrial code through the enterprise node and returns the analyzed identification registration information to the AR workbench.
And S03, calculating the class feature vector of the product in the enterprise node according to the analyzed identification registration information.
And S04, when the position of the product class feature vector is in the condition that the class needs to be expanded by triggering, the similar classes of the superior nodes are issued to the enterprise nodes.
And S05, optimizing the categories stored in the enterprise nodes at regular time.
Therefore, logistics has similarity in the aspects of the industry field, the identification types and the regions in distributing products, so that when the AR workbench analyzes the industrial code through the enterprise node, if the analyzed identification registration information reaches the condition of triggering the expansion of the categories, the similar categories in the superior node are issued to the enterprise node, the categories of the categories in the enterprise node are expanded, the transmission time between networks and the number of data query consumed by analyzing the identification registration information to the secondary node are reduced, and the speed of analyzing the industrial code can be increased.
Optionally, in step S01, the recording the identification registration information of the product in each level of node includes: the identification registration information is sent to the enterprise node by adopting a lightweight data exchange format JSON format and is recorded in the enterprise node; the enterprise node sends the identification registration information to the superior node and records the identification registration information in the superior node until the superior node is a national node.
Therefore, the JSON format is adopted among the nodes to transmit information, and compatibility is provided for different systems adopted by the nodes. Meanwhile, the step-by-step recording of the identification registration information from the enterprise node to the superior node is beneficial to information query.
Optionally, in step S01, the updating the identifier registration information of the node in real time includes: the updating information of the identification registration information is sent to the enterprise node by adopting a JSON format and is recorded in the enterprise node; the enterprise node sends the update information of the identification registration information to the superior node and records the update information of the identification registration information in the superior node until the superior node is a country node.
Therefore, the JSON format is adopted among the nodes to transmit information, and the method has compatibility with different systems adopted by the nodes. Meanwhile, the mark registration information is updated step by step from the enterprise node to the superior node, so that the integrity of the information can be effectively ensured.
Optionally, in step S02, the parsing, by the AR workbench, the industrial code by the enterprise node, and returning the parsed identifier registration information to the AR workbench includes: the AR workbench scans the industrial codes and transmits the industrial codes to the enterprise nodes; the enterprise node analyzes the industrial code and inquires corresponding identification registration information; the enterprise node returns the inquired identification registration information to the AR workbench; the AR workbench displays the query results.
The AR workbench analyzes the industrial code and obtains the identification registration information through the enterprise node, the enterprise node is equivalent to a local server, and network transmission time consumed by accessing a remote server is avoided, so that the AR workbench can rapidly display a query result.
Optionally, in step S03, the calculating, in the enterprise node, a category feature vector to which the product belongs according to the parsed identification registration information includes: and analyzing the identifier registration information in the enterprise node, and taking the analyzed values of the industry field, the identifier type and the region as the class characteristic vector of the product.
In this way, the category feature vector to which the product belongs is calculated in the enterprise node according to the analyzed identification registration information, so that whether the number of categories needs to be expanded in the enterprise node is judged according to the position of the category feature vector.
Optionally, in step S04, when the position of the product class feature vector is in the condition that the product class needs to be expanded, issuing the higher-level node similar class to the enterprise node includes: setting an area where the category characteristic vector exceeding the preset length is located as a threshold area in an enterprise node, and setting an expanded category reference point at a superior node along the direction of the category characteristic vector; under the condition that the position of the product class feature vector is in a threshold value area, the superior node searches for similar classes according to the expanded class reference point; and the superior node issues the similar categories to the enterprise node.
Because the products are distributed in logistics and have similarity in the aspects of the industry field, the identification type and the region, if the class characteristic vector is in the threshold value area, the similar class needs to be issued from the superior node, the number of the enterprise nodes is increased, and the number of times of accessing the superior node is reduced.
Optionally, the setting, in the enterprise node, an area where the category feature vector exceeding the preset length is located as a threshold area, and setting an expanded category reference point at a higher-level node along the direction of the category feature vector includes: the threshold region is a region range formed by the class feature vector, the upper quartile Q3, the median Q2, the lower quartile Q1 and the upper limit value ULV of the class feature vector are calculated, the region formed by the class feature vector with the length larger than the upper quartile Q3 is the threshold region, the point with the length as the upper limit value ULV is the expanded class reference point of the upper node,
wherein, Qi position = i is prepared
I =1, 2, 3; n represents the number of terms contained in the list,
q1=0.25 × term +0.75 × term, where the term in 0.25 × term is the term value corresponding to the position of Q1 being rounded, and the term in 0.75 × term is the term value corresponding to the position of Q1 being rounded +1, and can be expressed as Q1=0.25 × term [ Q1 being rounded ] +0.75 × term [ Q1 being rounded +1],
q2=0.5 × term +0.5 × term, where the first 0.5 × term is the term value corresponding to the position of Q2 rounded, and the second 0.5 × term is the term value corresponding to the position of Q2 rounded +1, which can be expressed as Q2=0.5 × term [ Q2 rounded ] +0.5 × term [ Q2 rounded +1 at the position ],
q3=0.75 × term +0.25 × term, the term in 0.75 × term is the term value corresponding to the position of Q3 being rounded, the term in 0.25 × term is the term value corresponding to the position of Q3 being rounded +1, and may be further expressed as Q3=0.75 × term [ Q3 being rounded ] +0.25 × term [ Q3 being rounded +1 at the position thereof),
wherein, the quartile distance IQR, IQR = Q3-Q1,
ULV=Q3+1.5×IQR。
in this way, the threshold region and the class reference point are set according to the improved box chart algorithm, the approximate class can be found through a probability calculation method, and therefore the number of times of accessing the upper node is reduced.
Optionally, in step S05, the step of registering identifiers of the categories stored in the timing optimization enterprise node includes: and in the enterprise node, inquiring the use conditions of all products at regular time, and deleting the unused categories exceeding the preset time.
In this way, classes that are not used for a long time can be deleted from the enterprise node, thereby saving product search time.
Optionally, the method further includes: and under the condition that the enterprise node does not contain the required identification registration information, inquiring the identification registration information from the upper-level node until reaching the national-level node.
When the identification registration information is inquired, if the identification registration information is not inquired at the enterprise node, inquiring the upper-level node until the identification registration information to be inquired is found.
In conjunction with the structure diagram of the expanded enterprise node class of the method for identifying an industrial code in a multi-level node structure provided by the embodiment of the present disclosure shown in fig. 4a, and the flowchart of the expanded enterprise node class of the method for identifying an industrial code in a multi-level node structure provided by the embodiment of the present disclosure shown in fig. 4b include:
in enterprise node 1 there is a class feature vector 111 in threshold region 11 and there is an extended class reference point 211 in secondary node 2.
And S100, analyzing the industrial codes in the enterprise nodes and calculating class characteristic vectors.
S101, judging whether the category feature vector is in a threshold region, if not, executing S102, and if so, executing S103, namely, if the category feature vector 111 is in the threshold region 11.
And S102, processing the identification registration information in the enterprise node.
And S103, processing the identification registration information in the enterprise node.
And S104, downloading the similar categories from the secondary nodes, namely downloading the similar categories from the expanded category reference point 211 to the enterprise nodes.
And S105, expanding the types of the enterprise node types.
With reference to fig. 5, a schematic diagram of analyzing an industrial code and expanding categories according to a method for identifying an industrial code in a multi-level node structure provided in an embodiment of the present disclosure includes:
s200, scanning an industrial code on an AR workbench;
s201, sending an analysis request of the industrial code from the AR workbench to the enterprise node;
s202, analyzing the industrial code at the enterprise node;
s203, inquiring identification registration information at the enterprise node;
s204, returning an analysis result of the industrial code from the enterprise node to the AR workbench;
s205, displaying the analysis result by the AR workbench;
s206, judging whether the category needs to be expanded, if the characteristic vector of the category is in the threshold region, expanding the category;
s207, a request for searching similar categories is sent from the enterprise node to the second-level node/the national-level node;
s208, searching similar categories in the second-level node/national-level node;
s209, returning the similar categories to the enterprise nodes;
s210, adding categories to enterprise nodes;
and S211, optimizing the categories at the enterprise nodes, and deleting the categories which are not used for more than the preset time.
The above description and drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, procedural, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising an …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosures, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.
Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (8)
1. A method for identifying an industrial code in a multi-level node structure is characterized in that the multi-level node is a topological structure formed by enterprise nodes, second-level nodes and national-level nodes and used for collecting identification registration information step by step, a plurality of categories for dividing products according to category feature vectors are arranged in the nodes, and the category feature vectors consist of industry fields, identification types and regions;
the method comprises the following steps:
recording the identification registration information of the product in each level of nodes, and updating the identification registration information of the nodes in real time;
the augmented reality AR workbench analyzes the industrial code through the enterprise node and returns the analyzed identification registration information to the AR workbench;
calculating the class characteristic vector of the product in the enterprise node according to the analyzed identification registration information;
when the position of the product class feature vector is in the condition that the class needs to be expanded by triggering, the similar class of the superior node is issued to the enterprise node, and the method comprises the following steps: setting an area where the category characteristic vector exceeding the preset length is located as a threshold area in an enterprise node, and setting an expanded category reference point at a superior node along the direction of the category characteristic vector; under the condition that the position of the product class feature vector is in a threshold value area, the superior node searches for similar classes according to the expanded class reference point; the superior node issues the similar categories to the enterprise node;
optimizing the categories stored in the enterprise nodes at regular time;
wherein, the region that will exceed the article class eigenvector of preset length in enterprise node sets up to the threshold value region, sets up along the superior node of article class eigenvector direction and enlarges the article class reference point, includes: the threshold region is a region range formed by the class feature vectors, the upper quartile Q3, the median Q2, the lower quartile Q1 and the upper limit value ULV of the class feature vectors are calculated, the region formed by the class feature vector length being larger than the upper quartile Q3 is the threshold region, the point with the length being the upper limit value ULV is an expanded class reference point of a superior node, wherein the position of Qi = i
I =1, 2, 3; n represents the number of terms contained in the sequence, Q1=0.25 × term +0.75 × term, where the term in 0.25 × 0 term is the term value corresponding to the position of Q1 rounded, and the term in 0.75 × 1 term is the term value corresponding to the position of Q1 rounded + 1; q2=0.5 × 2 terms +0.5 × 3 terms, where the first 0.5 × 4 term is the term value corresponding to the position of Q2 rounded, and the second 0.5 × term is the term value corresponding to the position of Q2 rounded + 1; q3=0.75 × item +0.25 × item, and of the Q3=0.75 × item +0.25 × item, the item in the 0.75 × item is the item value corresponding to the position where Q3 is located, and the item in the 0.25 × item is the item value corresponding to the position where Q3 is located, by rounding +1, where the quartile distance IQR, IQR = Q3-Q1, and ULV = Q3+1.5 × IQR.
2. The method according to claim 1, wherein the recording of the identification registration information of the product in each level of nodes comprises:
the identification registration information is sent to the enterprise node by adopting a JSON format and is recorded in the enterprise node;
the enterprise node sends the identification registration information to the superior node and records the identification registration information in the superior node until the superior node is a national node.
3. The method of claim 2, wherein updating the identity registration information of the node in real time comprises:
the updating information of the identification registration information is sent to the enterprise node by adopting a JSON format and is recorded in the enterprise node;
the enterprise node sends the update information of the identification registration information to the superior node and records the update information of the identification registration information in the superior node until the superior node is a country node.
4. The method of claim 1, wherein the Augmented Reality (AR) workbench parses the industrial code through the enterprise node and returns the parsed identity registration information to the AR workbench, comprising:
the AR workbench scans the industrial codes and transmits the industrial codes to the enterprise nodes;
the enterprise node analyzes the industrial code and inquires corresponding identification registration information;
the enterprise node returns the inquired identification registration information to the AR workbench;
the AR workbench displays the query results.
5. The method of claim 1, wherein computing, within the enterprise node, a class feature vector to which the product belongs based on the parsed identity registration information comprises:
and analyzing the identification registration information in the enterprise node, and taking the analyzed values of the industry field, the identification type and the region as the class characteristic vector of the product.
6. The method of claim 1, wherein the registering information of the identities of the classes stored in the timing optimization enterprise node comprises:
and in the enterprise node, inquiring the use conditions of all products at regular time, and deleting the unused categories exceeding the preset time.
7. The method of claim 1, further comprising:
and under the condition that the enterprise node does not contain the required identification registration information, inquiring the identification registration information from the upper-level node until reaching the national-level node.
8. An apparatus for identifying an industrial code in a multi-level node structure, comprising: at least one processor; and the number of the first and second groups,
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 a method for identifying industrial code in a multi-level node structure as claimed in any one of claims 1 to 7.
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