CN112305970A - Internet of things intelligent linkage control method and Internet of things intelligent linkage control center - Google Patents

Internet of things intelligent linkage control method and Internet of things intelligent linkage control center Download PDF

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CN112305970A
CN112305970A CN202011220898.5A CN202011220898A CN112305970A CN 112305970 A CN112305970 A CN 112305970A CN 202011220898 A CN202011220898 A CN 202011220898A CN 112305970 A CN112305970 A CN 112305970A
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沈寿娟
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
    • H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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Abstract

The invention provides an intelligent linkage control method of an internet of things and an intelligent linkage control center of the internet of things. The current working condition information and a plurality of communication interaction information of each Internet of things device can be collected; determining a communication weight distribution map of the Internet of things cluster according to the current working condition information and the plurality of communication interaction information of each Internet of things device; determining an influence area of a target weight node corresponding to the target Internet of things equipment in a communication weight distribution graph when a control instruction for adjusting the working condition of the target Internet of things equipment is received; and generating a linkage control instruction based on the influence area and the control instruction and issuing the linkage control instruction. Therefore, the relevance and the control linkage between the multiple pieces of internet of things equipment can be analyzed, the influence area of the target internet of things equipment is determined based on the communication weight distribution map, the linkage control instruction of the internet of things equipment related to the target internet of things equipment is determined, the linkage control of the multiple pieces of internet of things equipment is realized, and the control efficiency is improved.

Description

Internet of things intelligent linkage control method and Internet of things intelligent linkage control center
Technical Field
The invention relates to the technical field of Internet of things, in particular to an Internet of things intelligent linkage control method and an Internet of things intelligent linkage control center.
Background
With the development of science and technology and 5G communication, the application of the technology of the Internet of things is more and more mature, and in an automatic factory, the technology of the Internet of things can be utilized to realize efficient and uninterrupted production. However, in practical applications, the types and the number of the internet of things devices (production devices) in the automation plant are various, and when the working condition of a certain production line needs to be adjusted and controlled, different control instructions need to be issued respectively for a plurality of internet of things devices, which leads to low control efficiency.
Disclosure of Invention
In order to solve the problems, the invention provides an intelligent linkage control method of the Internet of things and an intelligent linkage control center of the Internet of things.
In a first aspect of the embodiments of the present invention, an intelligent linkage control method for an internet of things is provided, which is applied to an intelligent linkage control center for an internet of things communicating with a plurality of devices of the internet of things, and the method includes:
the method comprises the steps that current working condition information which is uploaded by each piece of Internet of things equipment and aims at a current production line and communication interaction information between each piece of Internet of things equipment and other pieces of Internet of things equipment in the Internet of things intelligent linkage control system under the corresponding current working condition information are periodically collected;
determining a communication weight distribution map of an Internet of things cluster formed by all Internet of things equipment in the Internet of things intelligent linkage control system in a current period according to current working condition information and a plurality of communication interaction information corresponding to each Internet of things equipment; the communication weight distribution graph comprises a plurality of weight nodes, each weight node represents one piece of Internet of things equipment, connecting lines with preset marks are arranged among at least part of the weight nodes, the preset marks are used for representing influence factors among the weight nodes, and the preset marks are obtained by comparing and analyzing running log files of the pieces of Internet of things equipment;
when a control instruction for adjusting the working condition of target Internet of things equipment in the Internet of things intelligent linkage control system is received in a current period, determining a target weight node corresponding to the target Internet of things equipment in the communication weight distribution map, and when the target weight node has a corresponding connecting line, determining an influence area of the target weight node in the communication weight distribution map according to a preset identification of the connecting line corresponding to the target weight node;
performing feature extraction on the control instruction to obtain instruction features corresponding to the control instruction, and mapping the instruction features to an influence area in the communication weight distribution map; generating control logic information for controlling each weight node to be processed according to the instruction characteristics and preset identifications corresponding to each weight node to be processed except the target weight node in the influence area; generating linkage control instructions aiming at all the Internet of things equipment in the current period according to the control instructions and all the generated control logic information; and issuing the linkage control instruction to each piece of Internet of things equipment in the affected area.
Optionally, the determining, according to the current working condition information and the plurality of communication interaction information corresponding to each piece of internet of things equipment, a communication weight distribution map of an internet of things cluster formed by all pieces of internet of things equipment in the internet of things intelligent linkage control system in a current period includes:
determining a working condition feature vector of current working condition information corresponding to each piece of Internet of things equipment and a communication feature vector of each piece of communication interaction information corresponding to each piece of Internet of things equipment, wherein the working condition feature vector and the communication feature vector have the same dimension;
determining a similarity value between a working condition feature vector corresponding to each piece of Internet of things equipment and each communication feature vector corresponding to the piece of Internet of things equipment, reserving the communication feature vectors with the similarity values larger than or equal to a set threshold value, and deleting the communication feature vectors with the similarity values smaller than the set threshold value; the set threshold value is determined according to an interface coding value corresponding to the communication interface type of each piece of Internet of things equipment, and the interface coding values of the communication interface types of different pieces of Internet of things equipment are different;
acquiring a time parameter corresponding to each reserved communication characteristic vector, and performing weighted summation on each reserved communication characteristic vector according to the time parameter to obtain a target communication vector corresponding to the working condition characteristic vector of each Internet of things device; the time parameter is used for representing the starting time and the ending time of the communication interaction information corresponding to the communication characteristic vector;
mapping a target communication vector corresponding to each piece of Internet of things equipment to a working condition characteristic vector corresponding to the piece of Internet of things equipment to obtain a mapping value of the target communication vector corresponding to the piece of Internet of things equipment on the working condition characteristic vector corresponding to the piece of Internet of things equipment, and taking the mapping value as a weight coefficient of the piece of Internet of things equipment;
the communication weight distribution map of the Internet of things cluster formed by all the Internet of things equipment in the Internet of things intelligent linkage control system in the current period is generated according to the weight coefficient corresponding to each piece of Internet of things equipment, and the one-to-one correspondence relationship between each piece of Internet of things equipment and the weight node in the communication weight distribution map is established in the communication weight distribution map according to the weight coefficient corresponding to each piece of Internet of things equipment.
Optionally, the determining, according to the preset identifier of the connection line corresponding to the target weight node, an influence area of the target weight node in the communication weight distribution map includes:
aiming at each connecting line corresponding to the target weight node, determining an influence factor between the target weight node corresponding to a preset identifier corresponding to the connecting line and an associated weight node corresponding to the connecting line;
sequencing all the determined influence factors corresponding to the target weight nodes to obtain a high-to-low influence factor sequencing sequence;
reconstructing the target weight node and all associated weight nodes corresponding to the target weight node in a mirror distribution graph corresponding to the communication weight distribution graph according to the influence factor sequencing sequence to obtain a reconstructed distribution graph;
and mapping the reconstruction distribution map to the communication weight distribution map by taking the position of the target weight node in the reconstruction distribution map as a reference to obtain an influence area of the target weight node in the communication weight distribution map.
Optionally, the performing feature extraction on the control instruction to obtain an instruction feature corresponding to the control instruction includes:
reading a source code instruction stream of the control instruction;
listing the logic information of each source code instruction stream and generating a logic information pool; the logic information pool is a partitioned area information pool, each area corresponds to an area identifier, each area identifier has at least one logic information, and each area of the logic information pool has a progressive relation from near to far;
reading a current instruction stream of the control instruction; extracting logic information in at least one logic information pool contained in the current instruction stream of the control instruction;
establishing a mapping relation between the current instruction stream and the logic information pool, and generating an instruction feature extraction logic according to the mapping relation; generating instruction feature extraction logic according to the mapping relation, wherein the generating instruction feature extraction logic comprises: converting each source code instruction stream into a logic input and output expression; respectively generating at least one logic direction information of each logic input and output expression; acquiring non-repetitive logic pointing information of the source code instruction stream to form a logic pointing information group; mapping each logic direction information in the logic direction information group to the logic information pool to form instruction feature extraction logic;
carrying out consistency judgment on logic information contained in the current instruction stream of the control instruction and each logic information in the instruction feature extraction logic; in the consistency judgment process, if all logic information in the instruction feature extraction logic is contained in the current instruction stream of the control instruction, determining the instruction feature extraction logic as a feature extraction path of the control instruction;
and loading the feature extraction path and the control instruction in a preset thread, and operating the thread to obtain the instruction feature corresponding to the control instruction.
Optionally, the generating, according to the instruction feature and a preset identifier corresponding to each to-be-processed weight node in the influence area except the target weight node, control logic information for controlling each to-be-processed weight node includes:
determining an instruction linkage distribution sequence of the instruction features in the influence area according to the mapping result of the instruction features in the influence area; the instruction linkage distribution sequence is used for representing the influence of the control instructions on the working condition of the Internet of things equipment corresponding to each weight node to be processed;
for each weight node to be processed, determining the relative position information of a preset identifier corresponding to the weight node to be processed in the instruction linkage distribution sequence; the relative position information comprises a first numerical value used for representing the row position of the preset identification in the instruction linkage distribution sequence and a second numerical value used for representing the column position of the preset identification in the instruction linkage distribution sequence;
according to the relative position information, weighting the mapping characteristics of the instruction characteristics included in the mapping result in the influence area to obtain the control logic characteristics corresponding to the weight node to be processed, and according to the control logic characteristics, obtaining the control logic information corresponding to the weight node to be processed.
Optionally, the generating, according to the control instruction and all the generated control logic information, a linkage control instruction for all the internet of things devices in the current period includes:
extracting the information flow of each piece of control logic information, determining an instruction field corresponding to each piece of control logic information from the information flow, and analyzing the instruction field to obtain a target instruction corresponding to each piece of control logic information;
for each target instruction, determining a correlation coefficient of the target instruction relative to the control instruction, and determining a device influence coefficient between the internet of things device corresponding to each target instruction and the target internet of things device corresponding to the control instruction according to the correlation coefficient; the device influence coefficient is used for representing the influence of the internet of things device corresponding to each target instruction on the target internet of things device when the corresponding target instruction is executed or the influence of the target internet of things device on the internet of things device corresponding to each target instruction when the control instruction is executed;
integrating the control command and the target commands according to the equipment influence coefficients, and distributing command identifications corresponding to the Internet of things equipment corresponding to the target commands to each target command to obtain the linkage control command; the instruction identification is used for indicating the Internet of things equipment to execute a corresponding target instruction in the linkage control instruction.
Optionally, the issuing the linkage control instruction to each internet of things device in the influence area includes:
determining a communication frequency band with each Internet of things device in the influence area;
converting the linkage control instruction into a corresponding radio frequency signal according to the communication frequency band of each piece of Internet of things equipment;
and transmitting each radio frequency signal to corresponding Internet of things equipment through a corresponding communication frequency band.
In a second aspect of the embodiments of the present invention, there is provided an intelligent linkage control device for an internet of things, which is applied to an intelligent linkage control center of an internet of things that communicates with a plurality of devices of the internet of things, the device including:
the information acquisition module is used for periodically acquiring current working condition information which is uploaded by each piece of Internet of things equipment and aims at a current production line and communication interaction information between each piece of Internet of things equipment and other pieces of Internet of things equipment in the Internet of things intelligent linkage control system under the corresponding current working condition information;
the distribution map determining module is used for determining a communication weight distribution map of an Internet of things cluster formed by all Internet of things equipment in the Internet of things intelligent linkage control system in a current period according to current working condition information and a plurality of communication interaction information corresponding to each Internet of things equipment; the communication weight distribution graph comprises a plurality of weight nodes, each weight node represents one piece of Internet of things equipment, connecting lines with preset marks are arranged among at least part of the weight nodes, the preset marks are used for representing influence factors among the weight nodes, and the preset marks are obtained by comparing and analyzing running log files of the pieces of Internet of things equipment;
the node determination module is used for determining a target weight node corresponding to the communication weight distribution map of the target internet of things equipment when receiving a control instruction for adjusting the working condition of the target internet of things equipment in the internet of things intelligent linkage control system in the current period, and determining an influence area of the target weight node in the communication weight distribution map according to a preset identification of a connecting line corresponding to the target weight node when the target weight node has the corresponding connecting line;
the linkage control module is used for extracting the characteristics of the control instruction to obtain the instruction characteristics corresponding to the control instruction and mapping the instruction characteristics to the influence area in the communication weight distribution map; generating control logic information for controlling each weight node to be processed according to the instruction characteristics and preset identifications corresponding to each weight node to be processed except the target weight node in the influence area; generating linkage control instructions aiming at all the Internet of things equipment in the current period according to the control instructions and all the generated control logic information; and issuing the linkage control instruction to each piece of Internet of things equipment in the affected area.
In a third aspect of the embodiments of the present invention, an intelligent linkage control center of an internet of things is provided, including: a processor and a memory and bus connected to the processor; the processor and the memory are communicated with each other through the bus; the processor is used for calling the computer program in the memory so as to execute the intelligent linkage control method of the Internet of things.
In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, and a program is stored thereon, and when being executed by a processor, the program implements the above-mentioned intelligent linkage control method for the internet of things.
According to the Internet of things intelligent linkage control method and the Internet of things intelligent linkage control center provided by the embodiment of the invention, firstly, the current working condition information and the plurality of communication interaction information of each Internet of things device are periodically collected. Secondly, a communication weight distribution graph of the Internet of things cluster is determined according to the current working condition information and the plurality of communication interaction information of each piece of Internet of things equipment, and the incidence relation among the plurality of pieces of Internet of things equipment can be represented through the communication weight distribution graph. And then, determining an influence area of a target weight node corresponding to the target internet of things equipment in the communication weight distribution map when a control instruction for adjusting the working condition of the target internet of things equipment is received. And finally, mapping the instruction characteristics of the control instruction to an influence area in the communication weight distribution map and determining the control logic information of each weight node to be processed in the influence area, so that a linkage control instruction is generated according to the control logic information and the control instruction and issued.
Therefore, the relevance and the control linkage between the multiple pieces of internet of things equipment can be analyzed, so that when the working condition of the target internet of things equipment is required to be adjusted, the influence area of the target internet of things equipment can be determined based on the communication weight distribution map, and the linkage control instruction of the internet of things equipment corresponding to the to-be-processed weight node associated with the target internet of things equipment is determined, so that the linkage control of the multiple pieces of internet of things equipment is realized, and the control efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic communication connection diagram of an intelligent linkage control system of the internet of things according to an embodiment of the present invention.
Fig. 2 is a flowchart of an intelligent linkage control method of the internet of things according to an embodiment of the present invention.
Fig. 3 is a functional module block diagram of an intelligent linkage control device of the internet of things according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of product modules of an intelligent linkage control center of the internet of things according to an embodiment of the present invention.
Icon:
100-an intelligent linkage control system of the Internet of things;
200-an intelligent linkage control center of the Internet of things; 201-an intelligent linkage control device of the Internet of things; 2011-information collection module; 2012-profile determination module; 2013-a node determining module; 2014-linkage control module; 211-a processor; 212-a memory; 213-a bus;
300-internet of things equipment.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.
In order to improve the control efficiency of the internet of things equipment in the automatic factory, the embodiment of the invention provides an internet of things intelligent linkage control method and an internet of things intelligent linkage control center, which can analyze the relevance among a plurality of internet of things equipment, thereby realizing linkage control of the plurality of internet of things equipment and improving the control efficiency.
Referring to fig. 1, an architecture schematic diagram of an intelligent coordinated control system 100 of the internet of things according to an embodiment of the present invention is shown, where the intelligent coordinated control system 100 of the internet of things includes an intelligent coordinated control center 200 of the internet of things and a plurality of devices 300 of the internet of things, which are in communication with each other. In this embodiment, the internet of things intelligent linkage control system 100 can be applied to an automated production plant. Accordingly, the internet of things device 300 may be a production device distributed in different areas or different production lines in an automation plant.
Referring to fig. 2, a flowchart of an intelligent linkage control method of the internet of things according to an embodiment of the present invention is shown, where the method is applied to the intelligent linkage control center 200 of the internet of things in fig. 1, and the method can be specifically implemented by the method described in the following steps.
And S21, periodically acquiring the current working condition information of each Internet of things device uploaded and aiming at the current production line and the communication interaction information between each Internet of things device and other Internet of things devices in the Internet of things intelligent linkage control system under the corresponding current working condition information.
In this embodiment, the control center periodically collects the relevant information may be understood as collecting the relevant information according to a set time interval. The set time interval can be flexibly set according to the density of the production line. In some periods, the line density is higher, the set time interval may be shortened, while in other periods, the line density is lower, the set time interval may be lengthened.
Step S22, determining a communication weight distribution map of an Internet of things cluster formed by all Internet of things equipment in the Internet of things intelligent linkage control system in a current period according to current working condition information and a plurality of communication interaction information corresponding to each Internet of things equipment; the communication weight distribution graph comprises a plurality of weight nodes, each weight node represents one piece of Internet of things equipment, connecting lines with preset marks exist among at least part of the weight nodes, the preset marks are used for representing influence factors among the weight nodes, and the preset marks are obtained by comparing and analyzing running log files of the pieces of Internet of things equipment.
Step S23, when a control instruction for adjusting the working condition of a target Internet of things device in the Internet of things intelligent linkage control system is received in a current period, determining a target weight node corresponding to the communication weight distribution map of the target Internet of things device, and when a corresponding connecting line exists in the target weight node, determining an influence area of the target weight node in the communication weight distribution map according to a preset identification of the connecting line corresponding to the target weight node.
In this embodiment, the control instruction may be initiated by a worker at the target internet of things device, or may be initiated by a third-party control platform, which is not limited herein.
Step S24, performing feature extraction on the control instruction to obtain an instruction feature corresponding to the control instruction, and mapping the instruction feature to an influence area in the communication weight distribution map; generating control logic information for controlling each weight node to be processed according to the instruction characteristics and preset identifications corresponding to each weight node to be processed except the target weight node in the influence area; generating linkage control instructions aiming at all the Internet of things equipment in the current period according to the control instructions and all the generated control logic information; and issuing the linkage control instruction to each piece of Internet of things equipment in the affected area.
It can be understood that, by the method described in the above steps S21-S24, first, current operating condition information and a plurality of communication interaction information of each internet of things device are periodically collected.
Secondly, a communication weight distribution graph of the Internet of things cluster is determined according to the current working condition information and the plurality of communication interaction information of each piece of Internet of things equipment, and the incidence relation among the plurality of pieces of Internet of things equipment can be represented through the communication weight distribution graph.
And then, determining an influence area of a target weight node corresponding to the target internet of things equipment in the communication weight distribution map when a control instruction for adjusting the working condition of the target internet of things equipment is received.
And finally, mapping the instruction characteristics of the control instruction to an influence area in the communication weight distribution map and determining the control logic information of each weight node to be processed in the influence area, so that a linkage control instruction is generated according to the control logic information and the control instruction and issued.
Therefore, the relevance and the control linkage between the multiple pieces of internet of things equipment can be analyzed, so that when the working condition of the target internet of things equipment is required to be adjusted, the influence area of the target internet of things equipment can be determined based on the communication weight distribution map, and the linkage control instruction of the internet of things equipment corresponding to the to-be-processed weight node associated with the target internet of things equipment is determined, so that the linkage control of the multiple pieces of internet of things equipment is realized, and the control efficiency is improved.
In specific implementation, in order to implement the device association and control linkage analysis of the internet of things devices 300, the influence relationship among the internet of things devices 300 needs to be accurately determined, and the communication weight distribution map can perform nodularization and wiring on the influence relationship. Therefore, in step S22, the determining, according to the current operating condition information corresponding to each internet of things device and the plurality of communication interaction information, a communication weight distribution map of an internet of things cluster formed by all internet of things devices in the internet of things intelligent linkage control system in the current period may specifically include the method described in the following steps S221 to S225.
Step S221, determining a working condition feature vector of the current working condition information corresponding to each Internet of things device and a communication feature vector of each communication interaction information corresponding to each Internet of things device, wherein the working condition feature vector and the communication feature vector have the same dimension.
Step S222, determining a similarity value between a working condition feature vector corresponding to each Internet of things device and each communication feature vector corresponding to the Internet of things device, reserving the communication feature vectors with the similarity values larger than or equal to a set threshold value, and deleting the communication feature vectors with the similarity values smaller than the set threshold value; the set threshold value is determined according to the interface coding value corresponding to the communication interface type of each piece of Internet of things equipment, and the interface coding values of the communication interface types of different pieces of Internet of things equipment are different.
In the embodiment, the communication feature vectors are screened, so that the equipment relevance feature and the control linkage feature of each piece of internet-of-things equipment can be accurately determined, and the reliability and the accuracy of the subsequently generated communication weight distribution map are ensured.
Step S223, acquiring a time parameter corresponding to each reserved communication characteristic vector, and performing weighted summation on each reserved communication characteristic vector according to the time parameter to obtain a target communication vector corresponding to the working condition characteristic vector of each Internet of things device; the time parameter is used for representing the starting time and the ending time of the communication interaction information corresponding to the communication characteristic vector.
Step S224, mapping the target communication vector corresponding to each Internet of things device to the working condition characteristic vector corresponding to the Internet of things device to obtain a mapping value of the target communication vector corresponding to the Internet of things device on the working condition characteristic vector corresponding to the Internet of things device, and taking the mapping value as a weight coefficient of the Internet of things device.
In this embodiment, the weight coefficient is used to determine the position of each internet of things device in the communication weight distribution map when the communication weight distribution map is generated.
Step S225, a communication weight distribution map of the Internet of things cluster formed by all the Internet of things devices in the Internet of things intelligent linkage control system in the current period is generated according to the weight coefficient corresponding to each Internet of things device, and a one-to-one correspondence relationship between each Internet of things device and the weight node in the communication weight distribution map is established in the communication weight distribution map according to the weight coefficient corresponding to each Internet of things device.
It can be understood that, through the contents described in the above steps S221 to S225, the communication weight distribution map can be accurately determined, so that the influence relationships among the internet of things devices 300 are nodularized and connected, and the subsequent device association and control linkage analysis on the internet of things devices 300 is facilitated.
In practical application, in order to accurately determine an influence area of a target internet of things device in a communication weight distribution graph, in step S23, the determining the influence area of the target weight node in the communication weight distribution graph according to a preset identifier of a connection line corresponding to the target weight node may specifically include the method described in the following steps S231 to S233.
Step S231, determining, for each connection line corresponding to the target weight node, an influence factor between the target weight node corresponding to the preset identifier corresponding to the connection line and the associated weight node corresponding to the connection line.
Step S232, sequencing all the determined influence factors corresponding to the target weight node to obtain a sequencing sequence of the influence factors from high to low; and reconstructing the target weight node and all associated weight nodes corresponding to the target weight node in the mirror distribution graph corresponding to the communication weight distribution graph according to the influence factor sequencing sequence to obtain a reconstructed distribution graph.
Step S233, mapping the reconstruction distribution map to the communication weight distribution map to obtain an influence region of the target weight node in the communication weight distribution map based on the position of the target weight node in the reconstruction distribution map.
It can be understood that through the contents described in the above steps S231 to S233, the influence factors of each connection line corresponding to the target weight node can be sorted, the target weight node and all associated weight nodes corresponding to the target weight node are reconstructed in the mirror distribution map corresponding to the communication weight distribution map based on the sorting sequence to obtain a reconstructed distribution map, and finally the reconstructed distribution map is mapped to the communication weight distribution map to obtain the influence region of the target weight node in the communication weight distribution map. Therefore, the reconstruction behavior in the communication weight distribution map can be avoided, the integrity and the accuracy of the communication weight distribution map are ensured, and the influence area of the target Internet of things equipment in the communication weight distribution map is accurately determined.
In a specific implementation, in order to accurately obtain the command characteristics of the control command, in step S24, the performing the feature extraction on the control command to obtain the command characteristics corresponding to the control command may specifically include the following method described in step S2411 to step S2416.
Step S2411, reading a source code instruction stream of the control instruction;
step S2412, listing the logic information of each source code instruction stream and generating a logic information pool; the logic information pool is a partitioned area information pool, each area corresponds to an area identifier, each area identifier has at least one logic information, and each area of the logic information pool has a progressive relation from near to far.
Step S2413, reading the current instruction stream of the control instruction; and extracting logic information in at least one logic information pool contained in the current instruction stream of the control instruction.
Step S2414, establishing a mapping relation between the current instruction stream and the logic information pool, and generating an instruction feature extraction logic according to the mapping relation; generating instruction feature extraction logic according to the mapping relation, wherein the generating instruction feature extraction logic comprises: converting each source code instruction stream into a logic input and output expression; respectively generating at least one logic direction information of each logic input and output expression; acquiring non-repetitive logic pointing information of the source code instruction stream to form a logic pointing information group; mapping each logic direction information in the logic direction information group to the logic information pool to form instruction feature extraction logic.
Step S2415, carrying out consistency judgment on logic information contained in the current instruction stream of the control instruction and each logic information in the instruction feature extraction logic; in the consistency judgment process, if all logic information in the instruction feature extraction logic is contained in the current instruction stream of the control instruction, the instruction feature extraction logic is determined as the feature extraction path of the control instruction.
Step S2416, loading the feature extraction path and the control instruction in a preset thread, and running the thread to obtain an instruction feature corresponding to the control instruction.
In the present embodiment, based on the contents described in the above steps S2411 to S2416, the command characteristics of the control command can be accurately obtained.
After the instruction feature is determined, in order to further determine control logic information, on the basis of the foregoing steps S2411 to S2416, in step S24, the control logic information for controlling each weight node to be processed is generated according to the instruction feature and the preset identifier corresponding to each weight node to be processed in the influence area except for the target weight node, which may specifically include the content described in the following steps S2421 to S2423.
Step S2421, determining an instruction linkage distribution sequence of the instruction features in the influence area according to the mapping result of the instruction features in the influence area.
In this embodiment, the instruction linkage distribution sequence is used to represent an influence of the control instruction on a working condition of the internet of things device corresponding to each weight node to be processed.
Step S2422, determining the relative position information of the preset identification corresponding to each weight node to be processed in the instruction linkage distribution sequence aiming at each weight node to be processed.
In this embodiment, the relative position information includes a first numerical value used for representing a row position of the preset identifier in the instruction linkage distribution sequence and a second numerical value used for representing a column position of the preset identifier in the instruction linkage distribution sequence.
Step S2423, according to the relative position information, weighting the mapping characteristics of the instruction characteristics included in the mapping result in the affected area to obtain the control logic characteristics corresponding to the weight node to be processed, and according to the control logic characteristics, obtaining the control logic information corresponding to the weight node to be processed.
It can be understood that, based on the contents described in the above steps S2421 to S2423, the control logic information corresponding to each weight node to be processed can be accurately determined, so as to provide an accurate data basis for the subsequent generation of the linkage control instruction.
On the basis, in step S24, the generating of the coordinated control instruction for all internet of things devices in the current cycle according to the control instruction and all the generated control logic information may specifically include the following steps.
Step S2431, extracting the information flow of each piece of control logic information, determining the instruction field corresponding to each piece of control logic information from the information flow, and analyzing the instruction field to obtain the target instruction corresponding to each piece of control logic information.
In this embodiment, the control logic information and the control instruction are stored in different data formats, and by determining the target instruction of each piece of control logic information, the data format of the control logic information can be converted into the target instruction consistent with the data format of the control instruction, and a uniform data basis can be provided for subsequently determining the linkage between the control instruction and the target instruction.
Step S2432, determining a correlation coefficient of each target instruction relative to the control instruction, and determining a device influence coefficient between the Internet of things device corresponding to each target instruction and the target Internet of things device corresponding to the control instruction according to the correlation coefficient; the device influence coefficient is used for representing the influence of the internet of things device corresponding to each target instruction on the target internet of things device when the corresponding target instruction is executed or the influence of the target internet of things device on the internet of things device corresponding to each target instruction when the control instruction is executed.
Step S2433, integrating the control instructions and the target instructions according to the equipment influence coefficients, and distributing instruction identifications corresponding to the Internet of things equipment corresponding to the target instructions to each target instruction to obtain the linkage control instructions; the instruction identification is used for indicating the Internet of things equipment to execute a corresponding target instruction in the linkage control instruction.
In this embodiment, the linkage control instruction may be understood as an instruction set for all the internet of things devices, where the instruction set includes an instruction corresponding to each internet of things device. It can be understood that if the instruction corresponding to one of the internet of things devices is updated, other instructions in the linkage control instruction are also updated. Of course, the updating action of the instruction is initiated by the intelligent linkage control center 200 of the internet of things.
It can be understood that based on the descriptions in the above steps S2431 to S2433, the data heterogeneity of the control logic information and the control command can be taken into account, the control logic information is further converted into the target command corresponding to the data structure of the control command, and then the association coefficient and the equipment influence coefficient are further determined, so that the target command and the control command are integrated to accurately obtain the linkage control command.
In a specific implementation, in step S24, the issuing of the linkage control command to each internet of things device in the affected area may specifically include the contents described in the following steps S2441 to S2443.
Step S2441, determining a communication frequency band of each Internet of things device in the influence area.
In this embodiment, the communication frequency bands of different internet of things devices are different.
And S2442, converting the linkage control instruction into a corresponding radio frequency signal according to the communication frequency band of each Internet of things device.
In the embodiment, the timeliness of linkage control instruction transmission can be improved by converting the linkage control instruction into different radio frequency signals.
And step S2443, transmitting each radio frequency signal to corresponding Internet of things equipment through a corresponding communication frequency band.
It can be understood that through the contents described in the above steps S2441 to S2443, the linkage control instruction can be converted according to the communication frequency bands of different pieces of internet of things equipment, so that each radio frequency signal is sent to the corresponding piece of internet of things equipment through the corresponding communication frequency band, and the timeliness of issuing the linkage control instruction is improved.
In an alternative embodiment, in order to ensure synchronous control over each internet of things device in the affected area, in step S24, the issuing of the coordinated control command to each internet of things device in the affected area may specifically include the contents described in steps S2451 to S2454 below.
Step S2451, determining the transmission delay between each Internet of things device in the influence area and each Internet of things device in the influence area.
Step S2452, determining the instruction analysis delay of each Internet of things device in the influence area.
Step S2453, determining an instruction sending delay corresponding to each Internet of things device in the affected area according to the transmission delay and the instruction analysis delay corresponding to each Internet of things device in the affected area.
And S2454, issuing the linkage control instruction in sequence according to the instruction sending delay corresponding to each Internet of things device in the influence area.
In this embodiment, based on the contents described in the above steps S2451 to S2454, the transmission delay and the instruction transmission delay of different pieces of internet-of-things equipment can be taken into consideration, so that the linkage control instruction is issued at different times according to the determined instruction transmission delay, and the synchronous control of each piece of internet-of-things equipment in the affected area is ensured.
In an alternative embodiment, in step S2452, the determining the instruction parsing delay of each internet of things device in the area of influence may specifically include what is described in the following steps.
(1) And acquiring instruction analysis thread parameters and thread nodes of each Internet of things device in the influence area.
(2) Under the condition that each Internet of things device in the influence area contains a delay node type according to the instruction analysis thread parameter, determining the distance between each thread node of each Internet of things device in the influence area under the non-delay node type and each thread node of each Internet of things device in the influence area under the delay node type according to the thread node and the node position of each Internet of things device in the influence area under the delay node type, and transferring the thread node of each Internet of things device in the influence area under the non-delay node type and the thread node under the delay node type, the distance of which is located in a set distance interval, to the corresponding delay node type.
(3) And determining the instruction analysis delay of each Internet of things device in the influence area according to the delay values of the thread nodes of each Internet of things device in the corresponding delay node category of each Internet of things device in the influence area.
It can be understood that through the content described in the above steps (1) to (3), the instruction analysis delay of each internet of things device in the affected area can be accurately determined.
On the basis, please refer to fig. 3 in combination, which is a block diagram of a module of the intelligent coordinated control device 201 of the internet of things according to the embodiment of the present invention, the intelligent coordinated control device 201 of the internet of things may include the following modules.
The information acquisition module 2011 is configured to periodically acquire current operating condition information, which is uploaded by each internet of things device and is for a current production line, and communication interaction information between each internet of things device and other internet of things devices in the internet of things intelligent linkage control system under the corresponding current operating condition information.
The distribution map determining module 2012 is configured to determine, according to the current working condition information and the plurality of communication interaction information corresponding to each piece of internet of things equipment, a communication weight distribution map of an internet of things cluster formed by all pieces of internet of things equipment in the internet of things intelligent linkage control system in a current period; the communication weight distribution graph comprises a plurality of weight nodes, each weight node represents one piece of Internet of things equipment, connecting lines with preset marks exist among at least part of the weight nodes, the preset marks are used for representing influence factors among the weight nodes, and the preset marks are obtained by comparing and analyzing running log files of the pieces of Internet of things equipment.
The node determining module 2013 is configured to determine a target weight node corresponding to the communication weight distribution map of the target internet of things device when a control instruction for adjusting the working condition of the target internet of things device in the internet of things intelligent linkage control system is received in a current period, and determine an influence area of the target weight node in the communication weight distribution map according to a preset identifier of a connection line corresponding to the target weight node when the target weight node has the corresponding connection line.
The linkage control module 2014 is used for performing feature extraction on the control instruction to obtain an instruction feature corresponding to the control instruction, and mapping the instruction feature to an influence area in the communication weight distribution map; generating control logic information for controlling each weight node to be processed according to the instruction characteristics and preset identifications corresponding to each weight node to be processed except the target weight node in the influence area; generating linkage control instructions aiming at all the Internet of things equipment in the current period according to the control instructions and all the generated control logic information; and issuing the linkage control instruction to each piece of Internet of things equipment in the affected area.
The embodiment of the invention also provides a computer readable storage medium, wherein a program is stored on the computer readable storage medium, and when the program is executed by a processor, the intelligent linkage control method for the Internet of things is realized.
The embodiment of the invention also provides a processor, wherein the processor is used for running the program, and the intelligent linkage control method of the Internet of things is executed when the program runs.
Referring to fig. 4, an embodiment of the present invention further provides an intelligent linkage control center 200 for an internet of things, which includes a processor 211, and a memory 212 and a bus 213 connected to the processor 211. Wherein, the processor 211 and the memory 212 are communicated with each other via a bus 213. The processor 211 is configured to call the program instructions in the memory 212 to execute the intelligent linkage control method of the internet of things.
In summary, the embodiment of the invention provides an intelligent linkage control method of an internet of things and an intelligent linkage control center of the internet of things.
Firstly, current working condition information and a plurality of communication interaction information of each Internet of things device are periodically collected.
Secondly, a communication weight distribution graph of the Internet of things cluster is determined according to the current working condition information and the plurality of communication interaction information of each piece of Internet of things equipment, and the incidence relation among the plurality of pieces of Internet of things equipment can be represented through the communication weight distribution graph.
And then, determining an influence area of a target weight node corresponding to the target internet of things equipment in the communication weight distribution map when a control instruction for adjusting the working condition of the target internet of things equipment is received.
And finally, mapping the instruction characteristics of the control instruction to an influence area in the communication weight distribution map and determining the control logic information of each weight node to be processed in the influence area, so that a linkage control instruction is generated according to the control logic information and the control instruction and issued.
Therefore, the relevance and the control linkage between the multiple pieces of internet of things equipment can be analyzed, so that when the working condition of the target internet of things equipment is required to be adjusted, the influence area of the target internet of things equipment can be determined based on the communication weight distribution map, and the linkage control instruction of the internet of things equipment corresponding to the to-be-processed weight node associated with the target internet of things equipment is determined, so that the linkage control of the multiple pieces of internet of things equipment is realized, and the control efficiency is improved.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or control center 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 control center. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or control center that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (9)

1. The intelligent linkage control method of the Internet of things is applied to an intelligent linkage control center of the Internet of things which is communicated with a plurality of pieces of equipment of the Internet of things, and comprises the following steps:
the method comprises the steps that current working condition information which is uploaded by each piece of Internet of things equipment and aims at a current production line and communication interaction information between each piece of Internet of things equipment and other pieces of Internet of things equipment in the Internet of things intelligent linkage control system under the corresponding current working condition information are periodically collected;
determining a communication weight distribution map of an Internet of things cluster formed by all Internet of things equipment in the Internet of things intelligent linkage control system in a current period according to current working condition information and a plurality of communication interaction information corresponding to each Internet of things equipment; the communication weight distribution graph comprises a plurality of weight nodes, each weight node represents one piece of Internet of things equipment, connecting lines with preset marks are arranged among at least part of the weight nodes, the preset marks are used for representing influence factors among the weight nodes, and the preset marks are obtained by comparing and analyzing running log files of the pieces of Internet of things equipment;
when a control instruction for adjusting the working condition of target Internet of things equipment in the Internet of things intelligent linkage control system is received in a current period, determining a target weight node corresponding to the target Internet of things equipment in the communication weight distribution map, and when the target weight node has a corresponding connecting line, determining an influence area of the target weight node in the communication weight distribution map according to a preset identification of the connecting line corresponding to the target weight node; wherein the control instruction is initiated by a third party control platform;
performing feature extraction on the control instruction to obtain instruction features corresponding to the control instruction, and mapping the instruction features to an influence area in the communication weight distribution map; generating control logic information for controlling each weight node to be processed according to the instruction characteristics and preset identifications corresponding to each weight node to be processed except the target weight node in the influence area; generating linkage control instructions aiming at all the Internet of things equipment in the current period according to the control instructions and all the generated control logic information; and issuing the linkage control instruction to each piece of Internet of things equipment in the affected area.
2. The method according to claim 1, wherein the determining a communication weight distribution map of the internet of things cluster formed by all internet of things devices in the internet of things intelligent linkage control system in a current period according to current working condition information corresponding to each internet of things device and a plurality of communication interaction information comprises:
determining a working condition feature vector of current working condition information corresponding to each piece of Internet of things equipment and a communication feature vector of each piece of communication interaction information corresponding to each piece of Internet of things equipment, wherein the working condition feature vector and the communication feature vector have the same dimension;
determining a similarity value between a working condition feature vector corresponding to each piece of Internet of things equipment and each communication feature vector corresponding to the piece of Internet of things equipment, reserving the communication feature vectors with the similarity values larger than or equal to a set threshold value, and deleting the communication feature vectors with the similarity values smaller than the set threshold value; the set threshold value is determined according to an interface coding value corresponding to the communication interface type of each piece of Internet of things equipment, and the interface coding values of the communication interface types of different pieces of Internet of things equipment are different;
acquiring a time parameter corresponding to each reserved communication characteristic vector, and performing weighted summation on each reserved communication characteristic vector according to the time parameter to obtain a target communication vector corresponding to the working condition characteristic vector of each Internet of things device; the time parameter is used for representing the starting time and the ending time of the communication interaction information corresponding to the communication characteristic vector;
mapping a target communication vector corresponding to each piece of Internet of things equipment to a working condition characteristic vector corresponding to the piece of Internet of things equipment to obtain a mapping value of the target communication vector corresponding to the piece of Internet of things equipment on the working condition characteristic vector corresponding to the piece of Internet of things equipment, and taking the mapping value as a weight coefficient of the piece of Internet of things equipment;
the communication weight distribution map of the Internet of things cluster formed by all the Internet of things equipment in the Internet of things intelligent linkage control system in the current period is generated according to the weight coefficient corresponding to each piece of Internet of things equipment, and the one-to-one correspondence relationship between each piece of Internet of things equipment and the weight node in the communication weight distribution map is established in the communication weight distribution map according to the weight coefficient corresponding to each piece of Internet of things equipment.
3. The method according to claim 2, wherein the determining an influence area of the target weight node in the communication weight distribution map according to the preset identifier of the connection line corresponding to the target weight node comprises:
aiming at each connecting line corresponding to the target weight node, determining an influence factor between the target weight node corresponding to a preset identifier corresponding to the connecting line and an associated weight node corresponding to the connecting line;
sequencing all the determined influence factors corresponding to the target weight nodes to obtain a high-to-low influence factor sequencing sequence;
reconstructing the target weight node and all associated weight nodes corresponding to the target weight node in a mirror distribution graph corresponding to the communication weight distribution graph according to the influence factor sequencing sequence to obtain a reconstructed distribution graph;
and mapping the reconstruction distribution map to the communication weight distribution map by taking the position of the target weight node in the reconstruction distribution map as a reference to obtain an influence area of the target weight node in the communication weight distribution map.
4. The method according to any one of claims 1 to 3, wherein the performing feature extraction on the control instruction to obtain an instruction feature corresponding to the control instruction comprises:
reading a source code instruction stream of the control instruction;
listing the logic information of each source code instruction stream and generating a logic information pool; the logic information pool is a partitioned area information pool, each area corresponds to an area identifier, each area identifier has at least one logic information, and each area of the logic information pool has a progressive relation from near to far;
reading a current instruction stream of the control instruction; extracting logic information in at least one logic information pool contained in the current instruction stream of the control instruction;
establishing a mapping relation between the current instruction stream and the logic information pool, and generating an instruction feature extraction logic according to the mapping relation; generating instruction feature extraction logic according to the mapping relation, wherein the generating instruction feature extraction logic comprises: converting each source code instruction stream into a logic input and output expression; respectively generating at least one logic direction information of each logic input and output expression; acquiring non-repetitive logic pointing information of the source code instruction stream to form a logic pointing information group; mapping each logic direction information in the logic direction information group to the logic information pool to form instruction feature extraction logic;
carrying out consistency judgment on logic information contained in the current instruction stream of the control instruction and each logic information in the instruction feature extraction logic; in the consistency judgment process, if all logic information in the instruction feature extraction logic is contained in the current instruction stream of the control instruction, determining the instruction feature extraction logic as a feature extraction path of the control instruction;
and loading the feature extraction path and the control instruction in a preset thread, and operating the thread to obtain the instruction feature corresponding to the control instruction.
5. The method according to claim 4, wherein the generating control logic information for controlling each weight node to be processed according to the instruction feature and a preset identifier corresponding to each weight node to be processed in the influence area except the target weight node comprises:
determining an instruction linkage distribution sequence of the instruction features in the influence area according to the mapping result of the instruction features in the influence area; the instruction linkage distribution sequence is used for representing the influence of the control instructions on the working condition of the Internet of things equipment corresponding to each weight node to be processed;
for each weight node to be processed, determining the relative position information of a preset identifier corresponding to the weight node to be processed in the instruction linkage distribution sequence; the relative position information comprises a first numerical value used for representing the row position of the preset identification in the instruction linkage distribution sequence and a second numerical value used for representing the column position of the preset identification in the instruction linkage distribution sequence;
according to the relative position information, weighting the mapping characteristics of the instruction characteristics included in the mapping result in the influence area to obtain the control logic characteristics corresponding to the weight node to be processed, and according to the control logic characteristics, obtaining the control logic information corresponding to the weight node to be processed.
6. The method of claim 5, wherein generating the coordinated control instructions for all the IOT devices in the current cycle according to the control instructions and all the generated control logic information comprises:
extracting the information flow of each piece of control logic information, determining an instruction field corresponding to each piece of control logic information from the information flow, and analyzing the instruction field to obtain a target instruction corresponding to each piece of control logic information;
for each target instruction, determining a correlation coefficient of the target instruction relative to the control instruction, and determining a device influence coefficient between the internet of things device corresponding to each target instruction and the target internet of things device corresponding to the control instruction according to the correlation coefficient; the device influence coefficient is used for representing the influence of the internet of things device corresponding to each target instruction on the target internet of things device when the corresponding target instruction is executed or the influence of the target internet of things device on the internet of things device corresponding to each target instruction when the control instruction is executed;
integrating the control command and the target commands according to the equipment influence coefficients, and distributing command identifications corresponding to the Internet of things equipment corresponding to the target commands to each target command to obtain the linkage control command; the instruction identification is used for indicating the Internet of things equipment to execute a corresponding target instruction in the linkage control instruction.
7. The method of claim 6, wherein issuing the coordinated control command to each Internet of things device in the area of influence comprises:
determining a communication frequency band with each Internet of things device in the influence area;
converting the linkage control instruction into a corresponding radio frequency signal according to the communication frequency band of each piece of Internet of things equipment;
and transmitting each radio frequency signal to corresponding Internet of things equipment through a corresponding communication frequency band.
8. The utility model provides a thing networking intelligence coordinated control center which characterized in that includes: a processor and a memory and bus connected to the processor; the processor and the memory are communicated with each other through the bus; the processor is used for calling a computer program in the memory to execute the intelligent linkage control method of the internet of things as claimed in any one of claims 1 to 7.
9. A computer-readable storage medium, on which a program is stored, which, when executed by a processor, implements the internet of things intelligent linkage control method of any one of claims 1 to 7.
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Application publication date: 20210202