Communication machine room environment monitoring system and method based on edge computing

Abstract

The invention discloses a communication machine room environment monitoring system and method based on edge computing, and the system comprises a data collection device, an edge gateway end, and a machine room monitoring terminal device, and the edge gateway end comprises a communication machine room map construction module, a risk assessment module, and a grading processing module. The computer room monitoring terminal is used for receiving the environment data and the equipment operation data information transmitted by the data acquisition equipment through the data communication link, comprehensively processing and analyzing the environment data and the equipment operation data to generate a data analysis result, and displaying the environment state and the equipment operation state of the computer room through the computer room monitoring terminal. According to the invention, by combining the construction of the communication machine room map and the risk assessment technology, the safety and efficiency of communication machine room monitoring are remarkably improved, abnormal conditions can be found in time and response can be made, stable operation of the communication machine room is ensured, and the reliability and safety of a communication network are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a communication room environment monitoring system and method based on edge computing. Background Art

[0002] For computer rooms where various devices are placed, it is necessary to monitor the environment of the computer room and the operation of various equipment in the computer room (such as refrigeration equipment, servers, power supplies, etc.) to achieve scientific management of the computer room and ensure its operational safety. At present, with the continuous development of Internet of Things technology, in order to realize the rapid processing of data collected by Internet of Things devices, edge computing devices will be set up between Internet of Things devices and servers.

[0003] However, in the related technology, the computer room monitoring system usually includes a monitoring main server, a gateway and a data acquisition device. On the one hand, the data collected by the data acquisition device is uploaded to the monitoring main server through the gateway for processing, but the deployment cost of the monitoring system is high when the monitoring main server is used to deploy the computer room monitoring system. On the other hand, the current computer room monitoring system is not ideal in terms of comprehensive monitoring of the communication room, and cannot perform intelligent analysis and prediction on the environmental impact of the computer room, the performance of the computer room equipment, and the healthy operation status of the equipment. It also does not have the ability to identify and process risk events at the edge of the communication room, as well as risk assessment operations. At the same time, it lacks the computer room operation feature labels that form environmental data and equipment operation data through natural language processing technology and feature extraction, and match them with the communication room map. It is difficult to combine the communication room map with the construction and application of risk event identification and processing and risk assessment. For this reason, we propose a communication room environment monitoring system and method based on edge computing. Summary of the invention

[0004] In view of the above problems existing in the existing communication room monitoring, the present invention is proposed.

[0005] Therefore, one of the objects of the present invention is to provide a communication room environment monitoring system and method based on edge computing, which receives environmental data and equipment operation data in the communication room at the edge end, constructs a communication room map, and comprehensively processes and analyzes the room operation data to generate data analysis results, thereby realizing the combined processing and application of the communication room map with risk event identification and risk assessment, and adding the identification and computational analysis of room risk events in the communication room map to perform integrated risk assessment, thereby further improving the monitoring security of the communication room.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: On the one hand, the present invention provides a communication room environment monitoring system based on edge computing, comprising: Data collection equipment, the data collection equipment is used to collect environmental data and equipment operation data in the communication room; An edge gateway end, wherein a first data communication link is established between the edge gateway end and the data acquisition device, wherein the first data communication link is used to receive environmental data and equipment operation data information transmitted from the data acquisition device through the data communication link, and to perform comprehensive processing and analysis on the environmental data and equipment operation data to generate data analysis results, wherein the edge gateway end includes a communication room map construction module, a risk assessment module, and a hierarchical processing module; A computer room monitoring terminal device, wherein the computer room monitoring terminal device establishes a second communication connection with the edge gateway end, and the monitoring device is used to receive the data analysis results sent by the edge gateway end based on the second communication connection, and display the data analysis results and perform daily computer room data maintenance to display the environmental status of the computer room and the operating status of the equipment; the computer room monitoring terminal device includes a risk response module, a visualization module, a data maintenance module, and a system upgrade module.

[0007] As a preferred solution of the present invention, wherein: the communication room graph construction module obtains the environmental data and equipment operation data information, that is, connects to the cloud computing platform of the data acquisition equipment through the API interface, and reads the cleaned data through the HTTP hypertext transfer protocol, extracts and integrates the risk chain knowledge data of the communication room for the environmental data and equipment operation data information, and forms a communication room risk knowledge graph. Specifically, an entity recognition function is constructed based on a statistical learning method, and after completing the identification and extraction of entities for the collected environmental data and equipment operation data information, the relationship between entities is obtained through the shortest dependency path algorithm. According to the graphic construction method of the communication room graph construction module, the extracted entities and the relationship between entities are converted into the form of a knowledge graph, and a comprehensive communication room risk chain knowledge graph is constructed and stored.

[0008] As a preferred solution of the present invention, the risk assessment module uses a machine learning algorithm to perform intelligent analysis and modeling on the room risk monitoring data in the communication room risk knowledge graph to achieve intelligent monitoring, fault diagnosis and predictive analysis processing of the communication room.

[0009] As a preferred solution of the present invention, wherein: the risk assessment module includes a feature extraction unit, a division unit, a machine processing unit, a training unit and a parameter adjustment unit; The feature extraction unit is used to extract features from the risk monitoring data of the communication room in the risk knowledge graph of the communication room, determine feature data according to the characteristics of the communication room monitoring data and the risk threshold, including feature selection, feature transformation and feature synthesis operations, and divide the extracted features into a training set and a test set through a division unit for training and evaluation of the machine learning model; The machine processing unit is used to determine the machine learning algorithm and establish the assessment model and data of each type of risk in the communication room map according to the type and characteristics of the feature data; The training unit is used to train the established machine learning model based on the training set, and then evaluate the trained model using the test set divided by the dividing unit to evaluate the performance and generalization ability of the model; The parameter adjustment unit is used to adjust the assessment model parameters of each type of risk and change the feature selection. In the process of adjusting the model parameters, a loss function is used to calculate the difference between the model prediction value and the true label.

[0010] As a preferred solution of the present invention, wherein: the risk assessment module also includes a communication room risk chain fusion assessment unit, and the communication room risk chain fusion assessment unit constructs a risk assessment model based on a Monte Carlo simulation model, specifically by defining risk events of the communication room risk chain, determining parameter information that affects the occurrence of risk events in the communication room, and then running the Monte Carlo simulation model to calculate the probability of occurrence of risks in the communication room, identifying high-risk equipment on the risk chain in the communication room risk knowledge graph, and performing early warning processing.

[0011] As a preferred solution of the present invention, the communication room risk probability is calculated by constructing a risk type classification function based on a support vector machine algorithm, wherein the risk type classification function is to classify the risk type according to the risk event occurrence parameters affecting the communication room risk chain, and calculate the communication room risk probability, specifically as follows: ; in, is the calculated value of the communication room risk occurrence probability, is the number of parameters affecting the occurrence of risk events in the risk chain of the communication room, is the number of risk events affecting the risk chain of the communication room, is the ranking ordinal number of the number of parameters affecting the occurrence of risk events in the risk chain of the communication room, For the The parameters of the risk chain of the communication room that affect the occurrence of risk events, For the The parameters of the risk chain of the communication room that affect the occurrence of risk events, is a natural constant; The identification of high-risk devices on the risk chain in the risk knowledge graph of the communication room is based on a multi-factor evaluation method to construct a risk score function for the communication room. The risk score function of the communication room divides the risk level according to the probability of risk occurrence and the risk type, and calculates the current risk score of the communication room by introducing the weights of different risk events in the knowledge graph of the risk chain of the communication room. The risk score function of the communication room is specifically expressed as follows: ; in, Calculate the score value for the current risk of the communication room. For the current communication room The weight value of is the weight of the risk event in the communication room risk chain, is the weight of the risk type in the communication room risk chain, For the risk events of the communication room risk chain, is the risk type of the communication room risk chain. is the bias term.

[0012] As a preferred solution of the present invention, wherein: the risk event affecting the risk chain of the communication room is the failure of equipment in the communication room, and the parameter information affecting the occurrence of the risk event in the communication room is determined, specifically using the hierarchical analysis method to determine the parameters affecting the occurrence of the risk event, and constructing a risk event simulation scenario based on the parameters, wherein the parameters include at least the ambient temperature and relative humidity information of the communication center room, cleanliness information, electrostatic interference information, noise information, lightning protection and grounding information, lighting information, safety information and equipment failure information in the communication room.

[0013] As a preferred solution of the present invention, the hierarchical processing module is used to hierarchically process the risk events of the risk chain of the communication room at different periods in the communication room map, specifically by obtaining the comprehensive evaluation membership of the communication room at different periods. Finally, the comprehensive evaluation membership is converted into a numerical value according to the average method, as follows: ; in, For the communication room Sample data, that is, Risk event parameter information of the risk chain of each communication room, Indicates the communication room The comprehensive evaluation membership of sample data is Indicates The weight of the comprehensive evaluation membership of the samples in each period, and greater than 0, For the The sorting sequence of the sample data.

[0014] As a preferred solution of the present invention, the computer room monitoring terminal device includes a risk response module, a visualization module, a data maintenance module, and a system upgrade module.

[0015] On the one hand, the present invention provides a communication room environment monitoring method based on edge computing, comprising the following steps: Step 1: Collect environmental data and equipment operation data in the computer room; Step 2: Establishing a first data communication link between the edge gateway and the data acquisition device to receive environmental data and device operation data information transmitted from the data acquisition device through the data communication link, and comprehensively processing and analyzing the environmental data and device operation data to generate data analysis results; Step three, establish a second communication connection between the computer room monitoring terminal device and the edge gateway, send the data analysis results based on the second communication connection, display the data analysis results and perform daily computer room data maintenance to show the environmental status of the computer room and the equipment operation status.

[0016] Compared with the prior art, the present invention has the following beneficial effects: after receiving the environmental data and equipment operation data in the communication room at the edge end, the present invention constructs a communication room map, and comprehensively processes and analyzes the room operation data to generate data analysis results, thereby realizing the combined processing and application of the communication room map with risk event identification processing and risk assessment, and adding the identification and computational analysis of room risk events in the communication room map to perform integrated risk assessment, thereby further improving the monitoring security of the communication room. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them: Figure 1 It is a schematic diagram of the module structure of the communication room environment monitoring system based on edge computing of the present invention; Figure 2 Schematic diagram of the module structure of the risk assessment module in the system of the present invention; Figure 3 It is a flow chart of the communication room environment monitoring method based on edge computing of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0019] Reference Figures 1 to 3 , is an embodiment of the present invention, which provides a communication room environment monitoring system and method based on edge computing, including: Data acquisition equipment, which is used to collect environmental data and equipment operation data in the communication room; The edge gateway end establishes a first data communication link with the data acquisition device, and the first data communication link is used to receive environmental data and equipment operation data information transmitted from the data acquisition device through the data communication link, and comprehensively process and analyze the environmental data and equipment operation data to generate data analysis results. The edge gateway end includes a communication room map construction module, a risk assessment module, and a hierarchical processing module; The computer room monitoring terminal equipment establishes a second communication connection with the edge gateway end. The monitoring equipment is used to receive the data analysis results sent by the edge gateway end based on the second communication connection, and display the data analysis results and perform daily computer room data maintenance to display the environmental status of the computer room and the equipment operation status; the computer room monitoring terminal equipment includes a risk response module, a visualization module, a data maintenance module, and a system upgrade module.

[0020] Specifically, in this embodiment, the communication room graph construction module obtains environmental data and equipment operation data information, that is, connects to the cloud computing platform of the data acquisition equipment through the API interface, and reads the cleaned data through the HTTP hypertext transfer protocol, extracts and integrates the risk chain knowledge data of the communication room from the environmental data and equipment operation data information, and forms a communication room risk knowledge graph. Specifically, an entity recognition function is constructed based on a statistical learning method, and after completing the recognition and extraction of entities for the collected environmental data and equipment operation data information, the relationship between entities is obtained through the shortest dependency path algorithm. According to the graphic construction method of the communication room graph construction module, the relationship between the extracted entities and the entities is converted into the form of a knowledge graph, and a comprehensive communication room risk chain knowledge graph is constructed and stored.

[0021] In this embodiment, the risk assessment module specifically uses a machine learning algorithm to perform intelligent analysis and modeling on the risk monitoring data of the communication room in the risk knowledge graph, so as to realize intelligent monitoring, fault diagnosis and predictive analysis processing of the communication room.

[0022] like Figure 2 As shown, in addition, the risk assessment module in this embodiment includes a feature extraction unit, a division unit, a machine processing unit, a training unit and a parameter adjustment unit; The feature extraction unit is used to extract features from the risk monitoring data of the communication room in the risk knowledge graph of the communication room, determine the feature data according to the characteristics and risk threshold of the communication room monitoring data, including feature selection, feature transformation and feature synthesis operations, and divide the extracted features into training sets and test sets through the division unit for training and evaluation of machine learning models; The machine processing unit is used to determine the machine learning algorithm and establish the assessment model and data of each type of risk in the communication room map according to the type and characteristics of the feature data; The training unit is used to train the established machine learning model based on the training set, and then evaluate the trained model using the test set divided by the division unit to evaluate the performance and generalization ability of the model; The parameter adjustment unit is used to adjust the assessment model parameters of each type of risk and change the feature selection. In the process of adjusting the model parameters, the loss function is used to calculate the difference between the model prediction value and the true label.

[0023] Based on the above, this embodiment uses machine learning algorithms to build intelligent machine learning models, which can accurately and efficiently analyze and predict the operating status and performance of edge computing devices, thereby enhancing the coverage and monitoring effect of the monitoring system.

[0024] When the model predicts a potential failure, the system can immediately issue an alarm and automatically start the preset automated response mechanism to achieve rapid repair of the failure and performance optimization. This automated alarm and repair process more effectively meets the monitoring needs in the edge computing environment and ensures the stability and reliability of the system.

[0025] like Figure 2 As shown, the risk assessment module of this embodiment specifically also includes a communication room risk chain fusion assessment unit. The communication room risk chain fusion assessment unit constructs a risk assessment model based on a Monte Carlo simulation model, specifically by defining risk events of the communication room risk chain, determining parameter information that affects the occurrence of risk events in the communication room, and then running the Monte Carlo simulation model to calculate the probability of occurrence of risks in the communication room, identify high-risk equipment on the risk chain in the communication room risk knowledge graph, and perform early warning processing.

[0026] Among them, Monte Carlo simulation is a computational analysis method based on random numbers, which uses randomness and probability to study and solve various problems. The principle of the Monte Carlo simulation model is to simulate various uncertain factors in the system through random sampling, and then perform a large number of repeated calculations to obtain the probability distribution of the problem, thereby solving uncertain problems.

[0027] It should be emphasized that this embodiment constructs a risk type classification function based on the support vector machine algorithm when calculating the probability of risk occurrence in the communication room. The risk type classification function classifies the risk type according to the risk event occurrence parameters affecting the risk chain of the communication room, and calculates the probability of risk occurrence in the communication room, as follows: ; in, is the calculated value of the communication room risk occurrence probability, is the number of parameters affecting the occurrence of risk events in the risk chain of the communication room, is the number of risk events affecting the risk chain of the communication room, is the ranking ordinal number of the number of parameters affecting the occurrence of risk events in the risk chain of the communication room, For the The parameters of the risk chain of the communication room that affect the occurrence of risk events, For the The parameters of the risk chain of the communication room that affect the occurrence of risk events, is a natural constant; Identifying high-risk equipment on the risk chain in the risk knowledge graph of the communication room is based on the multi-factor evaluation method to construct a risk score function for the communication room. The risk score function of the communication room divides the risk level according to the probability of risk occurrence and the risk type, and calculates the current risk score of the communication room by introducing the weights of different risk events in the knowledge graph of the risk chain of the communication room. The risk score function of the communication room is specifically expressed as follows: ; in, Calculate the score value for the current risk of the communication room. For the current communication room The weight value of is the weight of the risk event in the communication room risk chain, is the weight of the risk type in the communication room risk chain, For the risk events of the communication room risk chain, is the risk type of the communication room risk chain. is the bias term.

[0028] It should be noted that in this embodiment, the risk event affecting the risk chain of the communication room is the equipment failure of the communication room. The parameter information affecting the occurrence of the risk event in the communication room is determined. Specifically, the parameters affecting the occurrence of the risk event are determined by the hierarchical analysis method, and the risk event simulation scenario is constructed according to the parameters. The parameters at least include the ambient temperature and relative humidity information of the communication center room, cleanliness information, electrostatic interference information, noise information, lightning protection grounding information, lighting information, safety information, and equipment failure information of the communication room. For details, please refer to the relevant index requirements for anti-static interference in the communication room, which need to comply with the YD / T 1821-2018 standard.

[0029] It should be emphasized in this embodiment that the above-mentioned classification processing module is used to classify the risk events of the communication room risk chain at different periods in the communication room map, specifically by obtaining the comprehensive evaluation membership of the communication room at different periods. Finally, the comprehensive evaluation membership is converted into a numerical value according to the average method, as follows: ; in, For the communication room Sample data, that is, Risk event parameter information of the risk chain of each communication room, Indicates the communication room The comprehensive evaluation membership of sample data is Indicates The weight of the comprehensive evaluation membership of the samples in each period, and greater than 0, For the The sorting sequence of the sample data.

[0030] Based on the above, this embodiment realizes the comprehensive processing and analysis of the computer room operation data, generates data analysis results, realizes the combined processing and application of the communication room map and risk event identification processing and risk assessment, and adds the identification and computational analysis of computer room risk events in the communication room map to perform integrated risk assessment, further improving the monitoring security of the communication room.

[0031] like Figure 3 As shown, based on the above system, this embodiment also provides a communication room environment monitoring method based on edge computing, including the following steps: Step 1: Collect environmental data and equipment operation data in the computer room; Step 2: Establishing a first data communication link between the edge gateway and the data acquisition device to receive environmental data and device operation data information transmitted from the data acquisition device through the data communication link, and comprehensively processing and analyzing the environmental data and device operation data to generate data analysis results; Step three, establish a second communication connection between the computer room monitoring terminal device and the edge gateway, analyze the data based on the second communication connection, display the data analysis results and perform daily computer room data maintenance to show the environmental status of the computer room and the equipment operation status.

[0032] It is further explained that the present invention further constructs a comprehensive map of the communication room by receiving the environmental parameters and equipment operation status data in the communication room in real time at the edge computing layer. The map not only includes the physical layout and equipment configuration of the room, but also integrates the operation data and environmental monitoring data of the equipment. Through in-depth comprehensive processing and analysis of these data, the present invention can generate detailed data analysis results, which are not only used to identify and process risk events in the communication room, but also realize a comprehensive assessment of the risks in the room. In addition, the present invention realizes a fusion risk assessment of risk events by adding the identification and calculation and analysis functions of potential risk events in the communication room map. This fusion risk assessment method can more accurately predict and identify possible risk factors, so that preventive measures can be taken in advance to avoid or reduce the impact of risk events on the operation of the communication room.

[0033] In summary, the present invention significantly improves the safety and efficiency of communication room monitoring by combining the construction of communication room maps and risk assessment technology. By real-time monitoring and analysis of the environment and equipment status in the room, the present invention can promptly detect abnormal situations and respond to them, ensuring the stable operation of the communication room and enhancing the reliability and safety of the communication network.

[0034] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0035] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0036] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0037] Any process or method description in the flow chart or otherwise described herein can be understood to represent a module, fragment or portion of a code including one or more executable instructions for implementing the steps of a specific logical function or process. And the scope of the preferred embodiment of the present application includes other implementations, in which the functions may not be performed in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved.

[0038] It should be understood that the various parts of the present application can be implemented with hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium, and when the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0039] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0040] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. The communication room environment monitoring system based on edge computing is characterized by: include: Data collection equipment, the data collection equipment is used to collect environmental data and equipment operation data in the communication room; An edge gateway end, wherein a first data communication link is established between the edge gateway end and the data acquisition device, wherein the first data communication link is used to receive environmental data and equipment operation data information transmitted from the data acquisition device through the data communication link, and to perform comprehensive processing and analysis on the environmental data and equipment operation data to generate data analysis results, wherein the edge gateway end includes a communication room map construction module, a risk assessment module, and a hierarchical processing module; A computer room monitoring terminal device, wherein the computer room monitoring terminal device establishes a second communication connection with the edge gateway end, and the monitoring device is used to receive the data analysis results sent by the edge gateway end based on the second communication connection, and to display the data analysis results and perform daily computer room data maintenance to display the environmental status of the computer room and the equipment operation status.

2. The communication room environment monitoring system based on edge computing according to claim 1, characterized in that: The communication room graph construction module obtains the environmental data and equipment operation data information, that is, connects to the cloud computing platform of the data acquisition equipment through the API interface, and reads the cleaned data through the HTTP hypertext transfer protocol, extracts and integrates the risk chain knowledge data of the communication room from the environmental data and equipment operation data information, and forms a communication room risk knowledge graph. Specifically, an entity recognition function is constructed based on a statistical learning method. After completing the recognition and extraction of entities for the collected environmental data and equipment operation data information, the relationship between entities is obtained through the shortest dependency path algorithm. According to the graphic construction method of the communication room graph construction module, the relationship between the extracted entities and entities is converted into the form of a knowledge graph, and a comprehensive communication room risk chain knowledge graph is constructed and stored.

3. The communication room environment monitoring system based on edge computing according to claim 1, characterized in that: The risk assessment module uses a machine learning algorithm to perform intelligent analysis and modeling on the risk monitoring data of the communication room in the risk knowledge graph of the communication room, so as to realize intelligent monitoring, fault diagnosis and predictive analysis processing of the communication room.

4. The communication room environment monitoring system based on edge computing according to claim 3 is characterized in that: The risk assessment module includes a feature extraction unit, a division unit, a machine processing unit, a training unit and a parameter adjustment unit; The feature extraction unit is used to extract features from the risk monitoring data of the communication room in the risk knowledge graph of the communication room, determine feature data according to the characteristics of the communication room monitoring data and the risk threshold, including feature selection, feature transformation and feature synthesis operations, and divide the extracted features into a training set and a test set through a division unit for training and evaluation of the machine learning model; The machine processing unit is used to determine the machine learning algorithm and establish the assessment model and data of each type of risk in the communication room map according to the type and characteristics of the feature data; The training unit is used to train the established machine learning model based on the training set, and then evaluate the trained model using the test set divided by the dividing unit to evaluate the performance and generalization ability of the model; The parameter adjustment unit is used to adjust the assessment model parameters of each type of risk and change the feature selection. In the process of adjusting the model parameters, a loss function is used to calculate the difference between the model prediction value and the true label.

5. The communication room environment monitoring system based on edge computing according to claim 3, characterized in that: The risk assessment module also includes a communication room risk chain fusion assessment unit, which constructs a risk assessment model based on a Monte Carlo simulation model, specifically by defining risk events of the communication room risk chain, determining parameter information that affects the occurrence of risk events in the communication room, and then running the Monte Carlo simulation model to calculate the probability of occurrence of risks in the communication room, identify high-risk equipment on the risk chain in the communication room risk knowledge graph, and perform early warning processing.

6. The communication room environment monitoring system based on edge computing according to claim 5, characterized in that: The probability of communication room risk occurrence is calculated by constructing a risk type classification function based on the support vector machine algorithm. The risk type classification function classifies the risk type according to the risk event occurrence parameters affecting the communication room risk chain, and calculates the probability of communication room risk occurrence, as follows: ； in, is the calculated value of the communication room risk occurrence probability, is the number of parameters affecting the occurrence of risk events in the risk chain of the communication room, is the number of risk events affecting the risk chain of the communication room, is the ranking ordinal number of the number of parameters affecting the occurrence of risk events in the risk chain of the communication room, For the The parameters of the risk chain of the communication room that affect the occurrence of risk events, For the The parameters of the risk chain of the communication room that affect the occurrence of risk events, is a natural constant; The identification of high-risk devices on the risk chain in the risk knowledge graph of the communication room is based on a multi-factor evaluation method to construct a risk score function for the communication room. The risk score function of the communication room divides the risk level according to the probability of risk occurrence and the risk type, and calculates the current risk score of the communication room by introducing the weights of different risk events in the knowledge graph of the risk chain of the communication room. The risk score function of the communication room is specifically expressed as follows: ； in, Calculate the score value for the current risk of the communication room. For the current communication room The weight value of is the weight of the risk event in the communication room risk chain, is the weight of the risk type in the communication room risk chain, For the risk events of the communication room risk chain, is the risk type of the communication room risk chain. is the bias term.

7. The communication room environment monitoring system based on edge computing according to claim 5, characterized in that: The risk event affecting the risk chain of the communication room is equipment failure in the communication room. The parameter information affecting the occurrence of the risk event in the communication room is determined by specifically using the hierarchical analysis method to determine the parameters affecting the occurrence of the risk event, and constructing a risk event simulation scenario based on the parameters. The parameters include at least the ambient temperature and relative humidity information of the communication center room, cleanliness information, electrostatic interference information, noise information, lightning protection and grounding information, lighting information, safety information, and equipment failure information in the communication room.

8. The communication room environment monitoring system based on edge computing according to claim 5, characterized in that: The hierarchical processing module is used to hierarchically process the risk events of the risk chain of the communication room at different periods in the communication room map, specifically by obtaining the comprehensive evaluation membership of the communication room at different periods Finally, the comprehensive evaluation membership is converted into a numerical value according to the average method, as follows: ； in, For the communication room Sample data, that is, Risk event parameter information of the risk chain of each communication room, Indicates the communication room The comprehensive evaluation membership of sample data is Indicates The weight of the comprehensive evaluation membership of the samples in each period, and greater than 0, For the The sorting sequence of the sample data.

9. The communication room environment monitoring system based on edge computing according to claim 1, characterized in that: The computer room monitoring terminal device includes a risk response module, a visualization module, a data maintenance module, and a system upgrade module.

10. A method applied to the communication room environment monitoring system based on edge computing as claimed in claim 1, characterized in that: The following steps are involved: Step 1: Collect environmental data and equipment operation data in the computer room; Step 2: Establishing a first data communication link between the edge gateway and the data acquisition device to receive environmental data and device operation data information transmitted from the data acquisition device through the data communication link, and comprehensively processing and analyzing the environmental data and device operation data to generate data analysis results; Step three, establish a second communication connection between the computer room monitoring terminal device and the edge gateway, send the data analysis results based on the second communication connection, display the data analysis results and perform daily computer room data maintenance to show the environmental status of the computer room and the equipment operation status.

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