CN111401486B - Identification method and device for Internet of things identification and terminal equipment - Google Patents
Identification method and device for Internet of things identification and terminal equipment Download PDFInfo
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Abstract
The invention provides a method, a device and terminal equipment for identifying an Internet of things identifier, wherein the method for identifying the Internet of things identifier comprises the following steps: acquiring an identifier of the Internet of things to be identified; converting the to-be-identified internet of things identifier into a polygon; identifying the polygon pattern by utilizing a pre-trained pattern classification model to obtain an identification result of the coding category representing the identification of the Internet of things to be identified; and analyzing the identification of the internet of things to be identified according to the coding category of the identification of the internet of things to be identified. According to the embodiment of the invention, the automatic identification of the Internet of things identifications of different coding systems can be realized by utilizing the pre-trained graph classification model, so that the identification process of the heterogeneous Internet of things identifications is simplified, and the identification efficiency is improved.
Description
Technical Field
The present invention relates to the field of internet of things, and in particular, to a method and apparatus for identifying an identifier of the internet of things, and a terminal device.
Background
Along with the rapid development of the Internet of things, internet of things identification systems are continuously introduced in different countries and different fields, and the coexistence situation of various heterogeneous Internet of things identifications is brought. The internet of things identifier is a name tag for identifying different internet of things objects, such as commodity codes, device serial numbers, device network addresses, page URIs ((Uniform Resource Identifier, uniform resource identifiers) and the like, which are all internet of things identifiers.
Generally, the coding format and the analysis method of each Internet of things identifier are different, so that the mutual recognition of data and the resource sharing between Internet of things systems face serious challenges, and further development of the Internet of things is hindered. According to the compatibility and expandability of the identification system, the Internet of things identification can be divided into two categories, namely a proprietary identification and a comprehensive identification. The proprietary identifier has a separate coding structure, and has a fixed identification field or identification object, such as GS1 (EAN. UCC), EPC, sensor node identification, IPv4/6, and the like. The comprehensive identifier supports the identification of any object in different fields, and is a comprehensive identification system, and a common comprehensive identification system comprises three types of Handle, OID (Object Identifier, object identifier is also called as the internet of things domain name) and Ecode (Entity Code).
At present, for automatic identification of the heterogeneous Internet of things identifier, the compatibility of the heterogeneous Internet of things identifier is realized mainly by pre-agreeing mapping rules of other codes through comprehensive identifiers (such as Handle, OID or Ecode), so that the automatic identification and analysis of the heterogeneous Internet of things identifier are completed. However, because different comprehensive identification systems are in a competing relationship and are independent of each other, the unified identification system cannot be used for completing analysis and intercommunication of different codes, so that the identification process of the heterogeneous Internet of things identification is complicated and the efficiency is low.
Disclosure of Invention
The embodiment of the invention provides a method, a device and terminal equipment for identifying an Internet of things identifier, which are used for solving the problems of complex identification process and low efficiency of the existing heterogeneous Internet of things identifier.
In a first aspect, an embodiment of the present invention provides a method for identifying an identifier of an internet of things, including:
acquiring an identifier of the Internet of things to be identified;
converting the to-be-identified internet of things identifier into a polygon;
identifying the polygon pattern by utilizing a pre-trained pattern classification model to obtain an identification result of the coding category representing the identification of the Internet of things to be identified;
and analyzing the identification of the internet of things to be identified according to the coding category of the identification of the internet of things to be identified.
In a second aspect, an embodiment of the present invention provides an identification device for an identifier of the internet of things, including:
the first acquisition module is used for acquiring the identification of the Internet of things to be identified;
the first conversion module is used for converting the to-be-identified internet of things identifier into a polygon;
the recognition module is used for recognizing the polygon pattern by utilizing a pre-trained pattern classification model to obtain a recognition result of the coding category representing the identification of the internet of things to be recognized;
and the analysis module is used for analyzing the to-be-identified internet of things identifier according to the coding category of the to-be-identified internet of things identifier.
In a third aspect, an embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the computer program when executed by the processor may implement the steps of the method for identifying an identifier of the internet of things.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor may implement the steps of the method for identifying an identifier of the internet of things.
According to the embodiment of the invention, the identification of the Internet of things to be identified is converted into the polygon, and the converted polygon is identified by utilizing the pre-trained graph classification model, so that the identification result of the coding type of the identification of the Internet of things to be identified is obtained, and the automatic identification of the Internet of things of different coding systems can be realized without additionally creating a new identification system and changing the existing identification structure, thereby simplifying the identification process of the identification of the heterogeneous Internet of things and improving the identification efficiency.
Furthermore, the identification method of the embodiment of the invention does not need to force the internet of things objects to adopt a unified coding system, can convert the internet of things identifications of different coding systems into unified polygon images, and utilizes the pre-trained image classification model to identify the polygon image types corresponding to different coding systems, thereby realizing the identification of the internet of things identifications of different coding systems.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a flowchart of an identification method of an internet of things identifier according to an embodiment of the present invention;
FIG. 2 is a flow chart of converting logos into polygon graphics according to an embodiment of the present invention;
FIGS. 3A, 3B and 3C are schematic diagrams illustrating a process of converting labels into polygon patterns according to embodiments of the present invention;
fig. 4 is a schematic structural diagram of an identification device of an internet of things identifier according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Firstly, it is pointed out that the embodiment of the invention provides an automatic identification method for heterogeneous internet of things identifications, which does not need to additionally create a new identification system or change the existing identification structure, and the method can identify the graphic categories corresponding to different coding systems by utilizing a pre-trained graphic classification model by converting the internet of things identifications of different coding systems into uniform polygon graphics, so that the coding categories of the internet of things identifications are automatically identified, thereby simplifying the identification process of the heterogeneous internet of things identifications and improving the identification efficiency.
Referring to fig. 1, fig. 1 is a flowchart of an identification method of an internet of things identifier according to an embodiment of the present invention, as shown in fig. 1, the identification method includes the following steps:
step 101: and obtaining the identification of the Internet of things to be identified.
The to-be-identified internet of things identifier can be understood as a heterogeneous internet of things identifier. The to-be-identified internet of things identifier can be located on different carriers. For example, the carrier on which the to-be-identified internet of things identifier can be located includes, but is not limited to, two-dimensional codes, bar codes, RFID (Radio Frequency Identification ) tags, and the like.
Step 102: and converting the identification of the internet of things to be identified into a polygon.
It may be appreciated that, when executing step 102, the to-be-identified internet of things identifier may be converted into a multi-deformation graph that meets the preset condition based on the preset rule. The multi-deformation graph can be embodied in the form of an image, namely, when the multi-deformation graph is specifically implemented, the to-be-identified internet of things identification can be converted into the image comprising the corresponding multi-deformation graph.
Step 103: and identifying the polygon pattern by utilizing a pre-trained pattern classification model to obtain an identification result of the coding type representing the identification of the Internet of things to be identified.
The pattern classification model can be obtained by training in advance based on a machine learning object recognition (or pattern recognition) method. When step 103 is executed, the converted polygon pattern may be input into a pre-trained pattern classification model, so as to identify the input polygon pattern, and output an identification result indicating the coding type of the internet of things identifier to be identified.
Therefore, by utilizing a pre-trained graph classification model to identify the polygon graph obtained by conversion, the automatic identification problem of the coding type of the heterogeneous Internet of things identification can be converted into the object identification problem based on the graph, so that the identification process is simplified.
Step 104: and analyzing the identification of the internet of things to be identified according to the coding type of the identification of the internet of things to be identified.
Specifically, after the identification result representing the coding category of the to-be-identified internet of things identifier is obtained, the coding category of the to-be-identified internet of things identifier can be obtained, and according to the coding category of the to-be-identified internet of things identifier, a corresponding identifier analysis service can be invoked to analyze the to-be-identified internet of things identifier, so that the description information of the internet of things object corresponding to the to-be-identified internet of things identifier is obtained. For example, if the code type of the to-be-identified internet of things identifier is Ecode code, the Chinese article code center may be invoked to analyze the to-be-identified internet of things identifier.
According to the embodiment of the invention, the identification of the Internet of things to be identified is converted into the polygon, and the converted polygon is identified by utilizing the pre-trained graph classification model, so that the identification result of the coding type of the identification of the Internet of things to be identified is obtained, and the automatic identification of the Internet of things of different coding systems can be realized without additionally creating a new identification system and changing the existing identification structure, thereby simplifying the identification process of the identification of the heterogeneous Internet of things and improving the identification efficiency.
Furthermore, the identification method of the embodiment of the invention does not need to force the internet of things objects to adopt a unified coding system, can convert the internet of things identifications of different coding systems into unified polygon images, and utilizes the pre-trained image classification model to identify the polygon image types corresponding to different coding systems, thereby realizing the identification of the internet of things identifications of different coding systems.
In an embodiment of the present invention, optionally, the process of converting the identifier of the internet of things to be identified into the polygon in step 102 may include:
determining the coding bit number of the identification of the internet of things to be identified, and converting each coding bit of the identification of the internet of things to be identified into a reference value;
constructing the polygon according to the coding bit number and the reference value of each coding bit;
the number of the vertexes of the polygon in the polygon pattern is equal to the number of the coding bits, the coding bits of the identification of the internet of things to be identified are in one-to-one correspondence with the vertexes of the polygon, the distance from each vertex to a datum point in the polygon is in a preset multiple relation with the datum value of the coding bits corresponding to the vertexes, and the included angles formed by every two adjacent vertexes and the datum point are the same.
It can be understood that, when the above reference points are uniquely determined in the corresponding polygons, in specific implementation, the corresponding polygon can be pre-determined and constructed in combination with the maximum reference value of the reference values of all the coding bits of the internet of things to be identified, for example, firstly, a circle is drawn by taking the pre-determined reference point as the center of a circle and the maximum reference value as the radius, and then the corresponding polygon is constructed based on the drawn circle.
In this way, the identification of the internet of things to be identified can be converted into a variable pattern meeting preset conditions.
Further, the converting each coded bit of the to-be-identified internet of things identifier into the reference value may be selected as: and converting each coding bit of the identification of the internet of things to be identified into an ASCII code.
In one embodiment, referring to fig. 2, the process of converting the identifier of the internet of things to be identified into a polygon may include the following steps:
step 201: determining a coding bit number n of an identifier (hereinafter referred to as an identifier) of the internet of things to be identified, and converting each coding bit of the identifier into an ASCII code;
step 202: selecting the maximum ASCII code from ASCII codes of all coding bits, and creating a blank image, wherein the length and width of the blank image are equal to two times of the maximum ASCII code;
step 203: drawing a circle in the blank image by taking the center of the blank image as the circle center and taking the maximum ASCII code as the radius;
step 204: dividing the circle n equally according to the coding digit n of the mark, and connecting the circle center and each equally dividing point on the circle respectively;
step 205: mapping each coded bit of the identifier into a point on the connecting line of the circle center and each bisection point according to the sequence (such as anticlockwise or clockwise), wherein the distance from the point to the circle center is equal to the ASCII code of the corresponding coded bit;
step 206: and connecting all the mapped points to obtain the polygon corresponding to the mark.
It can be understood that in the above embodiment, the reference value of the encoded bits is ASCII code; the circle center is the datum point in the polygon and is determined according to the maximum ASCII code; the point on the connecting line of the circle center of each coding bit map and the equal dividing point is the vertex of the polygon, and the number of the vertices of the polygon is equal to the coding bit number of the mark; the included angles formed by every two adjacent vertexes and the circle center are the same. In the above embodiment, the distance from the vertex to the center (reference point) of the polygon is equal to the ASCII code of the corresponding code bit (i.e. the preset multiple is 1), but other preset multiples are selected in addition to this, for example, 0.5, 1.5 or 2, etc., which is not limited by the embodiment of the present invention.
The process of converting labels into polygon patterns according to embodiments of the present invention will be described below with reference to FIGS. 3A, 3B and 3C, taking EAN-8 bar codes as an example.
Assuming that the to-be-identified identifier of a certain EAN-8 barcode is 87217582 as shown in fig. 3A, the number of encoding bits of the identifier is 8, each encoding bit of the identifier is converted into an ASCII code, and 38 37 32 31 37 35 38 32 is obtained, wherein the maximum ASCII code is 38, so that when a polygon is converted, a blank image with a size of 76×76 can be created first, the center o of the blank image is used as the center of a circle, and the maximum ASCII code 38 is used as the radius, and a circle is drawn in the blank image; secondly, dividing the circle 8 equally according to the coding bit number 8, and respectively connecting the circle center and 8 equally dividing points on the circle; thirdly, according to the ASCII code of each coding bit, mapping each coding bit into a point on the connecting line of the circle center and each equal division point according to the clockwise direction, wherein the distance from the point to the circle center is equal to the ASCII code of the corresponding coding bit; then, connecting all the mapped points to obtain an image containing a polygon figure, as shown in fig. 3B; finally, according to the image including the polygon, the required polygon, i.e. the polygon corresponding to the identifier 87217582, can be further obtained, as shown in fig. 3C.
In an embodiment of the present invention, optionally, before step 101, the method may further include:
obtaining an identification sample set, wherein the identification sample set comprises at least two types of identification sample subsets, and each type of identification sample subset corresponds to one coding type;
converting all the identification samples in the identification sample set into a polygon pattern; the mode of converting the identifier into the polygon is the same as the mode of converting the identifier of the internet of things to be identified into the polygon, and the conversion mode can be referred to and is not repeated here;
and training the classification model according to the polygon patterns corresponding to all the identification samples to obtain a pattern classification model.
The code category corresponding to the identification sample subset can be selected from Ecode, EAN-8, EAN-13, EAN-128, URL or OID, etc. The multi-deformation graph can be embodied in the form of an image, namely all the identification samples in the identification sample set can be converted into image samples comprising corresponding multi-deformation graphs, and training of a classification model is carried out according to the image samples. When training the classification model, firstly, the Convolutional Neural Network (CNN) is utilized to extract image features from the image sample, and then the training of the classification model is carried out based on a deep learning algorithm or a classical machine learning algorithm so as to obtain the required graph classification model.
Therefore, the automatic identification of the identification coding category can be converted into the classification problem of the graph based on the identification-graph conversion method, so that the accurate classification of the identification can be realized through the existing mature object or graph classification technology, the identification process is simplified, and the identification efficiency is improved.
Further, in order to improve the training efficiency, the training of the classification model according to the polygon patterns of all the identification samples, and the process of obtaining the pattern classification model may include:
normalizing polygon patterns of all the identification samples; the normalization processing mode can be selected to normalize the polygon map to be uniform in size;
and training the classification model according to the polygon patterns of all the identification samples after normalization processing to obtain a pattern classification model.
Thus, through the normalization processing procedure, the efficiency can be improved in the training process.
The above embodiment describes the identification method of the internet of things identifier of the present invention, and the following describes the identification device of the internet of things identifier of the present invention with reference to the embodiment and the accompanying drawings.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an identification device for an identifier of the internet of things according to an embodiment of the present invention, as shown in fig. 4, the identification device includes:
the first obtaining module 41 is configured to obtain an identifier of the internet of things to be identified;
the first conversion module 42 is configured to convert the to-be-identified internet of things identifier into a polygon;
the recognition module 43 is configured to recognize the polygon pattern by using a pre-trained pattern classification model, so as to obtain a recognition result that represents a coding category of the to-be-recognized internet of things identifier;
and the analyzing module 44 is configured to analyze the to-be-identified internet of things identifier according to the coding category of the to-be-identified internet of things identifier.
According to the embodiment of the invention, the identification of the Internet of things to be identified is converted into the polygon, and the converted polygon is identified by utilizing the pre-trained graph classification model, so that the identification result of the coding type of the identification of the Internet of things to be identified is obtained, and the automatic identification of the Internet of things of different coding systems can be realized without additionally creating a new identification system and changing the existing identification structure, thereby simplifying the identification process of the identification of the heterogeneous Internet of things and improving the identification efficiency.
In an embodiment of the present invention, optionally, the first conversion module 42 includes:
the determining unit is used for determining the coding bit number of the to-be-identified internet of things identifier and converting each coding bit of the to-be-identified internet of things identifier into a reference value;
a construction unit, configured to construct the polygon according to the coding bit number and the reference value of each coding bit;
the number of the vertexes of the polygon in the polygon pattern is equal to the number of the coding bits, the coding bits of the identification of the internet of things to be identified are in one-to-one correspondence with the vertexes of the polygon, the distance from each vertex to a datum point in the polygon is in a preset multiple relation with the datum value of the coding bits corresponding to the vertexes, and the included angles formed by every two adjacent vertexes and the datum point are the same.
Optionally, the determining unit is further configured to:
and converting each coding bit of the identification of the internet of things to be identified into an ASCII code.
Optionally, the identifying device further includes:
a second obtaining module, configured to obtain an identification sample set, where the identification sample set includes at least two types of identification sample subsets, each type of identification sample subset corresponds to a coding type;
the second conversion module is used for converting all the identification samples in the identification sample set into polygon patterns;
and the training module is used for training the classification model according to the polygon patterns corresponding to all the identification samples to obtain the pattern classification model.
Optionally, the training module includes:
the processing unit is used for carrying out normalization processing on the polygon patterns of all the identification samples;
and the training unit is used for training the classification model according to the polygon patterns of all the identification samples after normalization processing to obtain the pattern classification model.
In addition, the embodiment of the invention also provides a terminal device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the computer program can realize each process of the identification method embodiment of the internet of things identification when being executed by the processor, and can achieve the same technical effect, and in order to avoid repetition, the description is omitted.
Specifically, referring to fig. 5, the embodiment of the present invention further provides a terminal device, which includes a bus 51, a transceiver 52, an antenna 53, a bus interface 54, a processor 55, and a memory 56.
In an embodiment of the present invention, the terminal device further includes: a computer program stored on the memory 56 and executable on the processor 55. Specifically, when the computer program is executed by the processor 55, the processes of the above-mentioned method embodiment for identifying the identifier of the internet of things can be implemented, and the same technical effects can be achieved, so that repetition is avoided, and no further description is given here.
In fig. 5, a bus architecture (represented by bus 51), the bus 51 may comprise any number of interconnected buses and bridges, with the bus 51 linking together various circuits, including one or more processors, represented by processor 55, and memory, represented by memory 56. The bus 51 may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., which are well known in the art and, therefore, will not be described further herein. Bus interface 54 provides an interface between bus 51 and transceiver 52. The transceiver 52 may be one element or may be a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 55 is transmitted over a wireless medium via the antenna 53. Furthermore, the antenna 53 receives data and transmits the data to the processor 55.
The processor 55 is responsible for managing the bus 51 and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 56 may be used to store data used by processor 55 in performing operations.
Alternatively, the processor 55 may be CPU, ASIC, FPGA or a CPLD.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, realizes the processes of the above-mentioned identification method embodiment of the internet of things identifier, and can achieve the same technical effects, and in order to avoid repetition, the description is omitted here.
Computer-readable media include both permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (8)
1. The identification method of the Internet of things identification is characterized by comprising the following steps of:
acquiring an identifier of the Internet of things to be identified;
converting the to-be-identified internet of things identifier into a polygon;
identifying the polygon pattern by utilizing a pre-trained pattern classification model to obtain an identification result of the coding category representing the identification of the Internet of things to be identified;
analyzing the to-be-identified internet of things identifier according to the coding category of the to-be-identified internet of things identifier;
the converting the to-be-identified internet of things identifier into a polygon image comprises the following steps:
determining the coding bit number of the to-be-identified internet of things identifier, and converting each coding bit of the to-be-identified internet of things identifier into a reference value;
constructing the polygon according to the coding bit number and the reference value of each coding bit;
the number of the vertexes of the polygon in the polygon pattern is equal to the number of the coding bits, the coding bits of the identification of the internet of things to be identified are in one-to-one correspondence with the vertexes of the polygon, the distance from each vertex to a datum point in the polygon is in a preset multiple relation with the datum value of the coding bits corresponding to the vertexes, and the included angles formed by every two adjacent vertexes and the datum point are the same.
2. The method of claim 1, wherein the converting each coded bit of the to-be-identified internet of things identifier into a reference value includes:
and converting each coding bit of the identification of the internet of things to be identified into an ASCII code.
3. The method according to claim 1, wherein before the obtaining the identifier of the internet of things to be identified, the method further comprises:
obtaining an identification sample set, wherein the identification sample set comprises at least two types of identification sample subsets, and each type of identification sample subset corresponds to one coding type;
converting all the identification samples in the identification sample set into a polygon pattern;
and training a classification model according to the polygon patterns corresponding to all the identification samples to obtain the pattern classification model.
4. The method according to claim 1, wherein training the classification model according to the polygon patterns of all the identification samples to obtain the pattern classification model comprises:
normalizing polygon patterns of all the identification samples;
and training a classification model according to the polygon patterns of all the identification samples after normalization processing to obtain the pattern classification model.
5. An identification device of an internet of things identifier, which is characterized by comprising:
the first acquisition module is used for acquiring the identification of the Internet of things to be identified;
the first conversion module is used for converting the to-be-identified internet of things identifier into a polygon;
the recognition module is used for recognizing the polygon pattern by utilizing a pre-trained pattern classification model to obtain a recognition result of the coding category representing the identification of the internet of things to be recognized;
the analysis module is used for analyzing the to-be-identified internet of things identifier according to the coding category of the to-be-identified internet of things identifier;
wherein the first conversion module includes:
the determining unit is used for determining the coding bit number of the to-be-identified internet of things identifier and converting each coding bit of the to-be-identified internet of things identifier into a reference value;
a construction unit, configured to construct the polygon according to the coding bit number and the reference value of each coding bit;
the number of the vertexes of the polygon in the polygon pattern is equal to the number of the coding bits, the coding bits of the identification of the internet of things to be identified are in one-to-one correspondence with the vertexes of the polygon, the distance from each vertex to a datum point in the polygon is in a preset multiple relation with the datum value of the coding bits corresponding to the vertexes, and the included angles formed by every two adjacent vertexes and the datum point are the same.
6. The identification device of claim 5, wherein the determination unit is further configured to:
and converting each coding bit of the identification of the internet of things to be identified into an ASCII code.
7. Terminal device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when executed by the processor realizes the steps of the method for identifying an internet of things identity according to any one of claims 1 to 4.
8. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method for identifying an internet of things identifier according to any one of claims 1 to 4.
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| CN201910000936.7A CN111401486B (en) | 2019-01-02 | 2019-01-02 | Identification method and device for Internet of things identification and terminal equipment |
| PCT/CN2020/070091 WO2020140937A1 (en) | 2019-01-02 | 2020-01-02 | Internet of things recognition identifier method and apparatus, and terminal device |
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| CN112866375B (en) * | 2021-01-14 | 2024-01-23 | 国网上海市电力公司 | Code analysis system and method |
| CN113098992A (en) * | 2021-04-02 | 2021-07-09 | 周宏仁 | Encoding method and apparatus, storage medium, and electronic device |
| CN114584522B (en) * | 2022-01-21 | 2024-02-06 | 中国人民解放军国防科技大学 | Identification method, system, medium and terminal of Internet of things equipment |
| CN114328630B (en) * | 2022-01-24 | 2023-06-23 | 嘉应学院 | Equipment identification system based on Internet of things |
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