An adaptive risk management system for communication pipeline projects based on the Internet of Things

Abstract

The present invention relates to the technical field of communication pipelines, and is used to solve the problem that it is impossible to accurately analyze the hardware influencing factors and data transmission load of the communication pipeline, resulting in data transmission blockage of the communication pipeline and low data transmission reliability and stability. In particular, a communication pipeline project adaptive risk management and control system based on the Internet of Things is disclosed, including a server, which is communicatively connected to a data acquisition unit, a hardware status risk analysis unit, a data volume risk analysis unit, a comprehensive risk analysis unit and a risk feedback management and control unit. The present invention clearly analyzes the degree of data volume blockage of each communication pipeline through real-time monitoring and judgment analysis of the hardware status and transmission data status of the communication pipeline project under the application of the Internet of Things, and adopts a priority adaptive allocation method to achieve efficient regulation of the data blocking risk of the communication pipeline project, thereby improving the security of the communication pipeline.

Description

Technical Field

[0001] The present invention relates to the technical field of communication pipelines, and in particular to an adaptive risk management and control system for communication pipeline projects based on the Internet of Things. Background Art

[0002] With the development of society and science and technology, communication pipeline technology is also constantly evolving. Communication pipelines have become one of the main infrastructures in current municipal construction. Communication pipelines are the main transmission tools and transmission equipment of current communication transmission technology. They are the main medium for people to exchange and transmit various information. Communication pipelines in the application of the Internet of Things carry a relatively large amount of data communication. Therefore, it is crucial to achieve adaptive control of data blocking risks in communication pipeline technology.

[0003] However, in the risk management of communication pipeline projects under IoT applications, it is impossible to accurately analyze the hardware influencing factors and data transmission load of the communication pipeline, resulting in data transmission blockage in the communication pipeline and low data transmission reliability and stability.

[0004] In order to solve the above-mentioned defects, a technical solution is now provided. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem that in the existing risk management of communication pipeline projects, the hardware influencing factors and data transmission load of the communication pipeline cannot be accurately analyzed, resulting in data transmission blockage of the communication pipeline and low data transmission reliability and stability. By accurately analyzing the hardware status of the communication pipeline project under the application of the Internet of Things, and using symbolic calibration, formula analysis and reference range substitution analysis, real-time monitoring and judgment analysis of the transmission data status of the communication pipeline project are realized, and the degree of data volume blockage of each communication pipeline is clearly analyzed. By using data integration and priority adaptive allocation, the data volume blockage risk of the communication pipeline project is efficiently regulated and processed, thereby ensuring the safety and reliability of the communication pipeline while promoting the stability of the operation of the Internet of Things, and proposing a communication pipeline project adaptive risk management system based on the Internet of Things.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An adaptive risk management and control system for communication pipeline projects based on the Internet of Things includes a server, which is communicatively connected to a data acquisition unit, a hardware status risk analysis unit, a data volume risk analysis unit, a comprehensive risk analysis unit, and a risk feedback management and control unit;

[0008] The data acquisition unit is used to collect hardware status information and transmission status information of each communication channel under the Internet of Things application, and send them to the hardware status risk analysis unit and the data volume risk analysis unit respectively;

[0009] The hardware status risk analysis unit is used to receive hardware status information of each communication channel of the Internet of Things, and perform basic transmission performance status analysis processing, thereby generating a signal indicating that the basic hardware status has a small impact on transmission risk and a signal indicating that the basic hardware status has a large impact on transmission risk, and sending the signal to the comprehensive risk analysis unit;

[0010] The data volume risk analysis unit is used to receive transmission status information of each communication channel of the Internet of Things, and perform data volume transmission status analysis and processing, thereby generating a transmission data volume under-signal, a transmission data volume normal signal, and a transmission data volume overload signal, and sending the signal to the comprehensive risk analysis unit;

[0011] The comprehensive risk analysis unit is used to receive the basic hardware status risk impact type judgment signal and the transmission data volume type judgment signal of each communication pipeline, and perform adaptive risk comprehensive control processing, thereby generating data volume priority processing instructions and factor priority processing instructions, and executing data volume priority control adaptive operations and influencing factor priority control adaptive operations respectively according to the data volume priority processing instructions and the factor priority processing instructions.

[0012] Furthermore, the specific steps for basic transmission performance status analysis and processing are as follows:

[0013] Obtain the communication pipeline cardinality in each communication pipeline of the Internet of Things in real time, set the gradient comparison intervals Q1 and Q2 of the communication pipeline cardinality, and substitute the communication pipeline cardinality in each communication pipeline into the preset gradient comparison intervals Q1 and Q2 for comparative analysis;

[0014] When the communication line cardinality in the communication pipeline is within the preset gradient comparison interval Q1, the corresponding communication pipeline is marked as a normal line cardinality signal, and each communication pipeline marked as a normal line cardinality signal is classified into a pipeline set A;

[0015] When the communication pipeline cardinality in the communication pipeline is within the preset gradient comparison interval Q2, the corresponding communication pipeline is marked as a signal with a large line cardinality, and each communication pipeline marked as a signal with a large line cardinality is classified into the second-category pipeline set B;

[0016] Based on the first-class pipeline set A and the second-class pipeline set B, the hardware status information of each communication pipeline is obtained in real time, and the first-class data analysis and processing and the second-class data analysis and processing are performed respectively, and accordingly, a signal that the basic hardware status has a small impact on the transmission risk and a signal that the basic hardware status has a large impact on the transmission risk are generated.

[0017] Furthermore, the specific steps for a type of data analysis and processing are as follows:

[0018] According to a type of pipeline set A, the communication pipelines in each communication pipeline are numbered in a clockwise direction;

[0019] Acquire the unit transmission distance in the hardware status information of each communication line of each communication pipeline in real time, set a distance reference threshold TT1 for the unit transmission distance, and compare and analyze the unit transmission distance of each communication line with the preset distance reference threshold TT1;

[0020] When the unit transmission distance is less than or equal to the preset distance reference threshold TT1, a signal with better distance characteristics is generated, and the corresponding communication pipeline is assigned a score and marked as X points;

[0021] When the unit transmission distance is greater than the preset distance reference threshold TT1, a poor distance characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y points, where X>Y;

[0022] Acquire the number of connected nodes from the hardware status information of each communication line of each communication pipeline in real time, set a node reference threshold TT2 for the number of connected nodes, and compare and analyze the number of connected nodes of each communication line with the preset node reference threshold TT2;

[0023] When the number of connected nodes is less than or equal to the preset node reference threshold TT2, a node characteristic better signal is generated, and the corresponding communication pipeline is assigned a score and marked as X points;

[0024] When the number of connected nodes is greater than the preset node reference threshold TT2, a poor node characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y;

[0025] Obtain the number and degree of bends in the hardware status information of each communication pipeline in real time, and mark them as zwc and zdg respectively, and perform formula analysis on them. The damage value of each communication pipeline is obtained, where e1 and e2 are the weight factor coefficients of the number of bends and the degree of bends respectively;

[0026] Set a damage reference threshold TT3 for the damage value, and compare and analyze the damage value of each communication pipeline with the preset damage reference threshold TT3;

[0027] When the damage value is less than the preset damage reference threshold TT3, a signal with better bending characteristics is generated, and the corresponding communication pipeline is assigned a score and marked as X points;

[0028] When the breakage value is greater than or equal to the preset breakage reference threshold TT3, a signal with poor bending characteristics is generated, and the corresponding communication pipeline is marked with a fractional assignment and marked as Y points;

[0029] The scores of the three hardware status data of each communication pipeline are superimposed and analyzed. If the sum of the scores of the three hardware status data of the communication pipeline is 3X or 2X + Y, the corresponding communication pipeline is calibrated as a signal with less impact on the transmission risk by the basic hardware status. If the sum of the scores of the three hardware status data of the communication pipeline is X + 2Y or 3Y, the corresponding communication pipeline is calibrated as a signal with greater impact on the transmission risk by the basic hardware status.

[0030] Furthermore, the specific operation steps of the secondary data analysis and processing are as follows:

[0031] According to the secondary pipeline set B, the values β corresponding to the sectional inclination angles of each connection node in the hardware status information of the corresponding communication pipeline of each communication pipeline in the secondary pipeline set B are obtained in real time ij , j = 1, 2, 3... m, and the values corresponding to the sectional inclination angles of each connection node of each communication pipeline are analyzed by averaging. According to the formula β i * =(β i1 +β i2 )>+β i3 +……+β im )÷m, the average sectional angle value β i * of each communication pipeline is obtained;

[0032] The values β corresponding to the sectional inclination angles of each connection node of each communication pipeline ij are analyzed by taking the difference with the corresponding average sectional angle value β i * . According to the formula α ij =丨β ij -β i * 丨, the sectional angle deviation value α ij of each connection node of each communication pipeline is obtained;

[0033] Taking the number of connection nodes as the abscissa and the sectional angle deviation value corresponding to each connection node as the ordinate, a two-dimensional rectangular coordinate system is established accordingly, and the sectional angle deviation values corresponding to each connection node are plotted on the two-dimensional rectangular coordinate system in the form of a broken line connection, and the sectional angle deviation broken line is obtained accordingly;

[0034] Calculate the total angle between the sectional angle deviation broken line and the horizontal line, set the reference value of the total angle, and compare and analyze the total angle with the preset reference value β Ca ;

[0035] When the total angle is less than the preset reference value β Ca When the total angle is greater than or equal to the reference value β, a uniform signal of the cross-section characteristic is generated, and the corresponding communication pipeline is assigned a score and marked as X points. Ca When , a section characteristic unevenness signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y points;

[0036] The scores of the four hardware status data of each communication pipeline are superimposed and analyzed. If the sum of the scores of the four hardware status data of the communication pipeline is 4X or 3X+Y, the corresponding communication pipeline is calibrated as a signal that the basic hardware status has a small impact on the transmission risk. If the sum of the scores of the four hardware status data of the communication pipeline is 2X+2Y or X+3Y or 4Y, the corresponding communication pipeline is calibrated as a signal that the basic hardware status has a large impact on the transmission risk.

[0037] Furthermore, the specific steps for analyzing and processing the data volume transmission status are as follows:

[0038] Obtain the transmission data volume and time interval value in the transmission status information of each communication pipeline of each communication pipeline in real time, and mark them as csl i and usl i , and analyze it by formula, according to the formula Qty i =f1*csl i +f2*usl i , get the transmission data state quantity of each communication pipeline, where f1 and f2 are the weight factor coefficients of the transmission data quantity and time interval value respectively, and f1 and f2 are both natural numbers;

[0039] Setting a data volume reference range Fa1 for the transmission data state volume, and comparing and analyzing the transmission data state volume of each communication pipeline with the preset data volume reference range Fa1;

[0040] When the transmission data state quantity is less than the minimum value of the preset data quantity reference range Fa1, a transmission data quantity under-representation signal is generated; when the transmission data state quantity is within the preset data quantity reference range Fa1, a transmission data quantity normal signal is generated; and when the transmission data state quantity is greater than the maximum value of the preset data quantity reference range Fa1, a transmission data quantity overload signal is generated.

[0041] Furthermore, the specific steps for adaptive risk comprehensive regulation are as follows:

[0042] At the same time, the basic hardware status risk impact type determination signal and the transmission data volume type determination signal of each communication pipeline of each communication pipeline are captured;

[0043] When two types of judgment signals are captured for the same communication pipeline, namely, a signal indicating that the basic hardware status has little impact on transmission risk and a signal indicating that the amount of transmission data is overloaded, a data volume priority processing instruction is generated for both signals;

[0044] When two types of judgment signals are captured for the same communication pipeline, namely, a signal indicating that the basic hardware status has a greater impact on the transmission risk and a signal indicating that the amount of transmitted data is overloaded, both generate factor priority processing instructions;

[0045] According to the generated data volume priority processing instruction and factor priority processing instruction, the data volume priority control adaptive operation and the influencing factor priority control adaptive operation are respectively executed.

[0046] Furthermore, the specific steps for data volume priority control adaptive operation are as follows:

[0047] When the communication pipeline is calibrated as a data volume priority processing instruction, the data volume priority processing instruction is followed, and the adjacent communication pipeline that transmits a signal with a relatively small amount of data is selected as the primary priority for data volume sharing operation, and the adjacent communication pipeline that transmits a signal with a normal amount of data is selected as the secondary priority for data volume sharing operation.

[0048] Furthermore, the specific steps of the adaptive operation of the influencing factors are as follows:

[0049] When a communication pipeline is marked as a factor-priority processing instruction, the data sharing operation is performed based on the factor-priority processing instruction and the similar communication pipeline whose basic hardware status has less impact on the transmission risk and transmits less data is selected as the first priority;

[0050] Select the communication pipelines with the lowest transmission risk due to the basic hardware status and the normal data transmission volume as the secondary priority for data sharing operation;

[0051] The communication pipelines close to the signals whose basic hardware status has a greater impact on the transmission risk and transmits a relatively small amount of data are selected as the third priority for data sharing operations.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention analyzes the cardinality of communication pipelines in each communication pipeline and classifies and regularizes each communication pipeline, thereby obtaining a Class I pipeline set A and a Class II pipeline set B. Based on this, the present invention uses threshold comparison analysis, score assignment, and numerical model analysis to accurately analyze the influencing factors of different types of communication pipeline hardware, laying the foundation for achieving efficient adaptive risk management and control of communication pipeline projects.

[0054] By using symbolic calibration, formula analysis, and reference range substitution analysis, we achieved real-time monitoring and judgment analysis of the transmission data status of the communication pipeline project, and clearly analyzed the degree of data congestion of each communication pipeline;

[0055] By utilizing data integration and adaptive priority allocation, the data congestion risk of communication pipeline projects is efficiently regulated and handled, thereby ensuring the safety and reliability of the communication pipeline while promoting the stability of the Internet of Things operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0057] Figure 1 This is the overall system block diagram of the present invention. DETAILED DESCRIPTION

[0058] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0059] like Figure 1 As shown, an adaptive risk management and control system for communication pipeline projects based on the Internet of Things includes a server, which is communicatively connected to a data acquisition unit, a hardware status risk analysis unit, a data volume risk analysis unit, a comprehensive risk analysis unit, and a risk feedback management and control unit;

[0060] The data acquisition unit is used to collect hardware status information and transmission status information of each communication channel under the Internet of Things application, and send them to the hardware status risk analysis unit and the data volume risk analysis unit respectively;

[0061] When the hardware status risk analysis unit receives the hardware status information of each communication channel of the Internet of Things, it performs basic transmission performance status analysis and processing based on it. The specific operation process is as follows:

[0062] Obtain the communication pipeline cardinality of each communication pipeline of the Internet of Things in real time, set the gradient comparison intervals Q1 and Q2 of the communication pipeline cardinality, and substitute the communication pipeline cardinality of each communication pipeline into the preset gradient comparison intervals Q1 and Q2 for comparative analysis, wherein the interval values ​​of Q1 and Q2 increase in a gradient manner;

[0063] When the communication line cardinality in the communication pipeline is within the preset gradient comparison interval Q1, the corresponding communication pipeline is marked as a normal line cardinality signal, and each communication pipeline marked as a normal line cardinality signal is classified into a pipeline set A;

[0064] When the communication pipeline cardinality in the communication pipeline is within the preset gradient comparison interval Q2, the corresponding communication pipeline is marked as a signal with a large line cardinality, and each communication pipeline marked as a signal with a large line cardinality is classified into the second-category pipeline set B;

[0065] Based on a set of pipelines A, the hardware status information of each communication pipeline is obtained in real time to perform a type of data analysis and processing, specifically:

[0066] According to a type of pipeline set A, the communication pipelines in each communication pipeline are numbered in a clockwise direction;

[0067] Acquire the unit transmission distance in the hardware status information of each communication line of each communication pipeline in real time, set a distance reference threshold TT1 for the unit transmission distance, and compare and analyze the unit transmission distance of each communication line with the preset distance reference threshold TT1;

[0068] When the unit transmission distance is less than or equal to the preset distance reference threshold TT1, a signal with better distance characteristics is generated, and the corresponding communication pipeline is assigned a score and marked as X points;

[0069] When the unit transmission distance is greater than the preset distance reference threshold TT1, a poor distance characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y points, where X>Y, and the specific score values ​​of X and Y are set by those skilled in the art in specific cases;

[0070] Acquire the number of connected nodes from the hardware status information of each communication line of each communication pipeline in real time, set a node reference threshold TT2 for the number of connected nodes, and compare and analyze the number of connected nodes of each communication line with the preset node reference threshold TT2;

[0071] When the number of connected nodes is less than or equal to the preset node reference threshold TT2, a node characteristic better signal is generated, and the corresponding communication pipeline is assigned a score and marked as X points;

[0072] When the number of connected nodes is greater than the preset node reference threshold TT2, a poor node characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y;

[0073] Obtain the number and degree of bends in the hardware status information of each communication pipeline in real time, and mark them as zwc and zdg respectively, and perform formula analysis on them. Obtain the damage value of each communication pipeline, where e1 and e2 are weight factor coefficients of the number of bends and the degree of bends, respectively, and i represents each communication pipeline, and i is a positive integer greater than or equal to 1;

[0074] Set a damage reference threshold TT3 for the damage value, and compare and analyze the damage value of each communication pipeline with the preset damage reference threshold TT3;

[0075] When the damage value is less than the preset damage reference threshold TT3, a signal with better bending characteristics is generated, and the corresponding communication pipeline is assigned a score and marked as X points;

[0076] When the damage value is greater than or equal to the preset damage reference threshold TT3, a poor bending characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y;

[0077] The scores of the three hardware status data of each communication pipeline are superimposed and analyzed. If the sum of the scores of the three hardware status data of the communication pipeline is 3X or 2X+Y, the corresponding communication pipeline is marked as a signal that the basic hardware status has a small impact on the transmission risk. If the sum of the scores of the three hardware status data of the communication pipeline is X+2Y or 3Y, the corresponding communication pipeline is marked as a signal that the basic hardware status has a large impact on the transmission risk.

[0078] It should be noted that the unit transmission distance refers to the data value of the transmission distance of each communication line from one transmitting end to another transmitting end; the number of connection nodes refers to the data value of the number of cable connection nodes of each communication line within the unit transmission distance; the number of bends refers to the data value of the number of cable bends of each communication line within the unit transmission distance; and the degree of bends refers to the data value of the bending angle of each bending point of the communication line within the unit transmission distance;

[0079] Based on the second-category pipeline set B, the hardware status information of each communication pipeline is obtained in real time to perform second-category data analysis and processing, specifically:

[0080] According to the second type of pipeline set B, the value β corresponding to the section inclination angle of each connection node in the hardware status information of the corresponding communication pipeline of each communication pipeline in the second type of pipeline set B is obtained in real time. ij , j = 1, 2, 3 ... m, where j represents each connection node of each communication pipeline, and the values ​​corresponding to the inclination angles of the sections of each connection node of each communication pipeline are averaged and analyzed according to the formula β i * =(βi1 +β i2 +β i3 +……+β im )÷m, to obtain the mean cross-section angle value β of each communication pipeline i * ;

[0081] The value β corresponding to the cross-section inclination angle of each connection node of each communication pipeline ij and the corresponding mean cross-section angle value β i * are subjected to difference analysis. According to the formula α ij =丨β ij -β i * 丨, to obtain the cross-section angle deviation value α of each connection node of each communication pipeline ij ;

[0082] Taking the number of connection nodes as the abscissa and the cross-section angle deviation value corresponding to each connection node as the ordinate, a two-dimensional rectangular coordinate system is established accordingly, and the cross-section angle deviation values corresponding to each connection node are plotted on the two-dimensional rectangular coordinate system in the way of connecting with broken lines, and the cross-section angle deviation broken line is obtained accordingly;

[0083] Calculate the total included angle between the cross-section angle deviation broken line and the horizontal line, set the reference value of the total included angle, and compare and analyze the total included angle with the preset reference value β Ca ;

[0084] When the total included angle is less than the preset reference value β Ca , a cross-section characteristic uniform signal is generated, and the corresponding communication pipeline is assigned a score and marked as X points. When the total included angle is greater than or equal to the reference value β Ca , a cross-section characteristic non-uniform signal is generated, the corresponding communication pipeline is assigned a score, and marked as Y points;

[0085] Repeat the data analysis and processing of the first type for the communication pipelines in each communication pipeline in the second type of pipeline set B, and accordingly obtain the scores of the other three hardware status data;

[0086] Perform superposition analysis on the scores of the four hardware status data of each communication pipeline. If the sum of the scores of the four hardware status data of the communication pipeline is 4X or 3X + Y, the corresponding communication pipeline is calibrated as a signal with less impact on the transmission risk by the basic hardware status. If the sum of the scores of the four hardware status data of the communication pipeline is 2X + 2Y or X + 3Y or 4Y, the corresponding communication pipeline is calibrated as a signal with greater impact on the transmission risk by the basic hardware status;

[0087] The generated signal indicating that the basic hardware status has a small impact on the transmission risk and the signal indicating that the basic hardware status has a large impact on the transmission risk are sent to the comprehensive risk analysis unit;

[0088] When the data volume risk analysis unit receives the transmission status information of each communication channel of the Internet of Things, it performs data volume transmission status analysis and processing based on the information. The specific operation process is as follows:

[0089] Obtain the transmission data volume and time interval value in the transmission status information of each communication pipeline of each communication pipeline in real time, and mark them as csl i and usl i , and analyze it by formula, according to the formula Qty i =f1*csl i +f2*usl i , the transmission data state quantity of each communication pipeline is obtained, where f1 and f2 are the weight factor coefficients of the transmission data quantity and time interval value respectively, and f1 and f2 are both natural numbers. The weight factor coefficient is used to balance the proportion of each data in the formula calculation, thereby improving the accuracy of the calculation result;

[0090] It should be noted that the transmission data volume refers to the data volume value of the size of the data packet transmitted from one end of the communication pipeline to the other end per unit time, and the time interval value refers to the data volume value of the time required for the transmission of a unit data packet from one end of the communication pipeline to the other end per unit time;

[0091] Setting a data volume reference range Fa1 for the transmission data state volume, and comparing and analyzing the transmission data state volume of each communication pipeline with the preset data volume reference range Fa1;

[0092] When the amount of data being transmitted is less than the minimum value of a preset data amount reference range Fa1, a data amount being insufficient signal is generated; when the amount of data being transmitted is within the preset data amount reference range Fa1, a data amount being normal signal is generated; and when the amount of data being transmitted is greater than the maximum value of the preset data amount reference range Fa1, a data amount being overload signal is generated.

[0093] and sending the generated insufficient data transmission signal, normal data transmission signal and overload data transmission signal to the comprehensive risk analysis unit;

[0094] When the risk comprehensive analysis unit receives the basic hardware status risk impact type determination signal and the transmission data volume type determination signal of each communication pipeline, it performs adaptive risk comprehensive control processing accordingly. The specific operation process is as follows:

[0095] At the same time, the basic hardware status risk impact type determination signal and the transmission data volume type determination signal of each communication pipeline of each communication pipeline are captured;

[0096] Among them, the basic hardware status risk impact type determination signal includes a signal that the basic hardware status has a small impact on the transmission risk and a signal that the basic hardware status has a large impact on the transmission risk; the transmission data volume type determination signal includes a signal that the transmission data volume is small, a signal that the transmission data volume is normal, and a signal that the transmission data volume is overloaded;

[0097] When two types of judgment signals are captured for the same communication pipeline, namely, a signal indicating that the basic hardware status has little impact on transmission risk and a signal indicating that the amount of transmission data is overloaded, a data volume priority processing instruction is generated for both signals;

[0098] When two types of judgment signals are captured for the same communication pipeline, namely, a signal indicating that the basic hardware status has a greater impact on the transmission risk and a signal indicating that the amount of transmitted data is overloaded, both generate factor priority processing instructions;

[0099] and respectively executing a data volume priority control adaptive operation and an influencing factor priority control adaptive operation according to the generated data volume priority processing instruction and factor priority processing instruction;

[0100] The specific process of data volume priority control adaptive operation is as follows:

[0101] When a communication pipeline is marked as a data volume priority processing instruction, the data volume priority processing instruction is used, and the adjacent communication pipeline that transmits a signal with a relatively small amount of data is selected as the first priority for data volume sharing operation, and the adjacent communication pipeline that transmits a signal with a normal amount of data is selected as the second priority for data volume sharing operation;

[0102] The specific process of influencing factors prioritizing adaptive operations is as follows:

[0103] When a communication pipeline is marked as a factor-priority processing instruction, the data sharing operation is performed based on the factor-priority processing instruction and the similar communication pipeline whose basic hardware status has less impact on the transmission risk and transmits less data is selected as the first priority;

[0104] Select the communication pipelines with the lowest transmission risk due to the basic hardware status and the normal data transmission volume as the secondary priority for data sharing operation;

[0105] The communication pipelines close to the signals whose basic hardware status has a greater impact on the transmission risk and transmits a relatively small amount of data are selected as the third priority for data sharing operations.

[0106] When in use, the present invention obtains hardware status information of each communication pipeline under the Internet of Things application in real time and performs basic transmission performance status analysis and processing. First, based on the analysis of the communication pipeline cardinality in each communication pipeline, each communication pipeline is classified and regularized, thereby obtaining a Class I pipeline set A and a Class II pipeline set B;

[0107] Based on a set of pipelines A, the system acquires three hardware status data of each communication pipeline in real time for data analysis and processing. Using threshold comparison analysis, score assignment, and data overlay analysis, it accurately analyzes the influencing factors of the communication pipeline hardware itself, laying the foundation for efficient adaptive risk management and control of communication pipeline projects.

[0108] Based on the Class II pipeline set B, four hardware status data items of each communication pipeline corresponding to the communication pipeline are obtained in real time for Class II data analysis and processing. By using data analysis, coordinate model analysis, and data judgment methods, a more comprehensive and in-depth analysis of the hardware risk status of the communication pipeline technology is achieved;

[0109] By acquiring the transmission status information of each communication pipeline in real time and analyzing the data transmission status, the system uses symbolic calibration, formula analysis and reference range substitution analysis to achieve real-time monitoring and judgment analysis of the transmission data status of the communication pipeline project, and clearly analyzes the degree of data congestion of each communication pipeline.

[0110] By utilizing data integration and adaptive priority allocation, the data congestion risk of communication pipeline projects is efficiently regulated and handled, thereby ensuring the safety and reliability of the communication pipeline while promoting the stability of the Internet of Things operation.

[0111] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An adaptive risk management and control system for communication pipeline projects based on the Internet of Things, characterized by: The server includes a data acquisition unit, a hardware status risk analysis unit, a data volume risk analysis unit, a comprehensive risk analysis unit, and a risk feedback control unit. The data acquisition unit is used to collect hardware status information and transmission status information of each communication channel under the Internet of Things application, and send them to the hardware status risk analysis unit and the data volume risk analysis unit respectively; The hardware status risk analysis unit is used to receive hardware status information of each communication channel of the Internet of Things, and perform basic transmission performance status analysis processing, thereby generating a signal indicating that the basic hardware status has a small impact on transmission risk and a signal indicating that the basic hardware status has a large impact on transmission risk, and sending the signal to the comprehensive risk analysis unit; The data volume risk analysis unit is used to receive transmission status information of each communication channel of the Internet of Things, and perform data volume transmission status analysis and processing, thereby generating a transmission data volume under-signal, a transmission data volume normal signal, and a transmission data volume overload signal, and sending the signal to the comprehensive risk analysis unit; The risk comprehensive analysis unit is used to receive the basic hardware status risk impact type determination signal and the transmission data volume type determination signal of each communication pipeline, and perform adaptive risk comprehensive control processing, thereby generating a data volume priority processing instruction and a factor priority processing instruction, and respectively executing a data volume priority control adaptive operation and an influencing factor priority control adaptive operation according to the data volume priority processing instruction and the factor priority processing instruction; The specific steps for basic transmission performance status analysis and processing are as follows: Obtain the communication pipeline cardinality in each communication pipeline of the Internet of Things in real time, set the gradient comparison intervals Q1 and Q2 of the communication pipeline cardinality, and substitute the communication pipeline cardinality in each communication pipeline into the preset gradient comparison intervals Q1 and Q2 for comparative analysis; When the communication line cardinality in the communication pipeline is within the preset gradient comparison interval Q1, the corresponding communication pipeline is marked as a normal line cardinality signal, and each communication pipeline marked as a normal line cardinality signal is classified into a pipeline set A; When the communication pipeline cardinality in the communication pipeline is within the preset gradient comparison interval Q2, the corresponding communication pipeline is marked as a signal with a large line cardinality, and each communication pipeline marked as a signal with a large line cardinality is classified into the second-category pipeline set B; Based on the first-class pipeline set A and the second-class pipeline set B, the hardware status information of each communication pipeline is obtained in real time, and the first-class data analysis and processing and the second-class data analysis and processing are performed respectively, and accordingly, a signal that the basic hardware status has a small impact on the transmission risk and a signal that the basic hardware status has a large impact on the transmission risk are generated.

2. The adaptive risk management and control system for communication pipeline projects based on the Internet of Things according to claim 1 is characterized in that: The specific steps for the first type of data analysis and processing are as follows: According to a type of pipeline set A, the communication pipelines in each communication pipeline are numbered in a clockwise direction; Acquire the unit transmission distance in the hardware status information of each communication line of each communication pipeline in real time, set a distance reference threshold TT1 for the unit transmission distance, and compare and analyze the unit transmission distance of each communication line with the preset distance reference threshold TT1; When the unit transmission distance is less than or equal to the preset distance reference threshold TT1, a signal with better distance characteristics is generated, and the corresponding communication pipeline is assigned a score and marked as X points; When the unit transmission distance is greater than the preset distance reference threshold TT1, a poor distance characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y points, where X>Y; Acquire the number of connected nodes from the hardware status information of each communication line of each communication pipeline in real time, set a node reference threshold TT2 for the number of connected nodes, and compare and analyze the number of connected nodes of each communication line with the preset node reference threshold TT2; When the number of connected nodes is less than or equal to the preset node reference threshold TT2, a node characteristic better signal is generated, and the corresponding communication pipeline is assigned a score and marked as X points; When the number of connected nodes is greater than the preset node reference threshold TT2, a poor node characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y; Real-time acquisition of the number and degree of bends in the hardware status information of each communication pipeline of each communication pipeline, and data analysis to obtain the damage value of each communication pipeline; Set a damage reference threshold TT3 for the damage value, and compare and analyze the damage value of each communication pipeline with the preset damage reference threshold TT3; When the damage value is less than the preset damage reference threshold TT3, a signal with better bending characteristics is generated, and the corresponding communication pipeline is assigned a score and marked as X points; When the damage value is greater than or equal to the preset damage reference threshold TT3, a poor bending characteristic signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y; The scores of the three hardware status data of each communication pipeline are superimposed and analyzed. If the sum of the scores of the three hardware status data of the communication pipeline is 3X or 2X+Y, the corresponding communication pipeline is calibrated as a signal that the basic hardware status has a small impact on the transmission risk. If the sum of the scores of the three hardware status data of the communication pipeline is X+2Y or 3Y, the corresponding communication pipeline is calibrated as a signal that the basic hardware status has a large impact on the transmission risk.

3. The adaptive risk management and control system for communication pipeline projects based on the Internet of Things according to claim 1 is characterized in that: The specific steps for analyzing and processing the second type of data are as follows: Based on the second-category pipeline set B, the value corresponding to the section inclination angle of each connection node in the hardware status information of the corresponding communication pipeline of each communication pipeline in the second-category pipeline set B is obtained in real time, and the value corresponding to the section inclination angle of each connection node of each communication pipeline is averaged and analyzed to obtain the average section angle value of each communication pipeline; Perform difference analysis on the value corresponding to the inclination angle of the section of each connection node of each communication pipeline and the corresponding mean section angle value to obtain the section angle deviation value of each connection node of each communication pipeline; A two-dimensional rectangular coordinate system is established with the number of connection nodes as the horizontal coordinate and the section angle deviation value corresponding to each connection node as the vertical coordinate. The section angle deviation value corresponding to each connection node is plotted on the two-dimensional rectangular coordinate system by connecting them with a broken line, and a section angle deviation broken line is obtained accordingly. Calculate the total angle between the section angle deviation line and the horizontal line, set the reference value of the total angle, and compare the total angle with the preset reference value β Ca Conduct comparative analysis; When the total angle is less than the preset reference value β Ca When the total angle is greater than or equal to the reference value β, a uniform signal of the cross-section characteristic is generated, and the corresponding communication pipeline is assigned a score and marked as X points. Ca When , a section characteristic unevenness signal is generated, and the corresponding communication pipeline is assigned a score and marked as Y points; The scores of the four hardware status data of each communication pipeline are superimposed and analyzed. If the sum of the scores of the four hardware status data of the communication pipeline is 4X or 3X+Y, the corresponding communication pipeline is calibrated as a signal that the basic hardware status has a small impact on the transmission risk. If the sum of the scores of the four hardware status data of the communication pipeline is 2X+2Y or X+3Y or 4Y, the corresponding communication pipeline is calibrated as a signal that the basic hardware status has a large impact on the transmission risk.

4. The adaptive risk management and control system for communication pipeline projects based on the Internet of Things according to claim 1 is characterized in that: The specific steps for analyzing and processing data transmission status are as follows: Real-time acquisition of the transmission data volume and time interval value in the transmission status information of each communication pipeline of each communication pipeline, and data analysis thereof to obtain the transmission data status volume of each communication pipeline; Setting a data volume reference range Fa1 for the transmission data state volume, and comparing and analyzing the transmission data state volume of each communication pipeline with the preset data volume reference range Fa1; When the transmission data state quantity is less than the minimum value of the preset data quantity reference range Fa1, a transmission data quantity under-representation signal is generated; when the transmission data state quantity is within the preset data quantity reference range Fa1, a transmission data quantity normal signal is generated; and when the transmission data state quantity is greater than the maximum value of the preset data quantity reference range Fa1, a transmission data quantity overload signal is generated.

5. The adaptive risk management and control system for communication pipeline projects based on the Internet of Things according to claim 1 is characterized in that: The specific steps for adaptive risk comprehensive control are as follows: At the same time, the basic hardware status risk impact type determination signal and the transmission data volume type determination signal of each communication pipeline of each communication pipeline are captured; When two types of judgment signals are captured for the same communication pipeline, namely, a signal indicating that the basic hardware status has little impact on transmission risk and a signal indicating that the amount of transmission data is overloaded, a data volume priority processing instruction is generated for both signals; When two types of judgment signals are captured for the same communication pipeline, namely, a signal indicating that the basic hardware status has a greater impact on the transmission risk and a signal indicating that the amount of transmitted data is overloaded, both generate factor priority processing instructions; According to the generated data volume priority processing instruction and factor priority processing instruction, the data volume priority control adaptive operation and the influencing factor priority control adaptive operation are respectively executed.

6. The adaptive risk management and control system for communication pipeline projects based on the Internet of Things according to claim 5 is characterized in that: The specific steps for data volume priority control adaptive operation are as follows: When the communication pipeline is calibrated as a data volume priority processing instruction, the data volume priority processing instruction is followed, and the adjacent communication pipeline that transmits a signal with a relatively small amount of data is selected as the primary priority for data volume sharing operation, and the adjacent communication pipeline that transmits a signal with a normal amount of data is selected as the secondary priority for data volume sharing operation.

7. The adaptive risk management and control system for communication pipeline projects based on the Internet of Things according to claim 5 is characterized in that: The specific steps for prioritizing the influencing factors to regulate the adaptive operation are as follows: When a communication pipeline is marked as a factor-priority processing instruction, the data sharing operation is performed based on the factor-priority processing instruction and the similar communication pipeline whose basic hardware status has less impact on the transmission risk and transmits less data is selected as the first priority; Select the communication pipelines with the lowest transmission risk due to the basic hardware status and the normal transmission data volume as the secondary priority for data sharing operation; The basic hardware status has a greater impact on the transmission risk of the signal and the similar communication pipeline of the signal with a relatively small amount of transmission data is selected as the third priority for data sharing operation.

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