Smart city municipal facility clustering management method and system

Abstract

The invention relates to the technical field of municipal facility management, in particular to a smart city municipal facility clustering management method and system, and the system comprises a municipal facility management center, a centralized control aging evaluation unit, a clustering risk unit, a management effect evaluation feedback unit, a clustering optimization unit and a management response unit. Whether the municipal facilities can be normally managed or not is analyzed and planned from the perspective of clustering control connection, and clustering management defect risk analysis is further performed from the perspective of control risks of control nodes corresponding to the municipal facilities, so that the safety and stability of current clustering management are improved; the clustering operation and maintenance management efficiency level condition of the currently planned municipal facilities is analyzed from two points of equipment operation and maintenance and equipment supervision based on an information progressive mode, and analysis is performed from the management expression direction of each management perspective, so that reasonable and targeted optimization management is performed on the current cluster management system. The clustering operation and maintenance management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of municipal facility management, and particularly to a method and system for cluster management of smart city municipal facilities. Background Art

[0002] The centralized management and control of multiple devices are crucial for improving the effectiveness of monitoring systems. Through the application of networked monitoring systems, centralized management software, and automated management and intelligent control, etc., managers can achieve remote unified management and centralized control of multiple devices, improving management efficiency and convenience;

[0003] However, in the prior art, it is impossible to conduct safety supervision on the connections of municipal facilities, thereby reducing the stability of cluster management of municipal facilities. At the same time, it is impossible to conduct risk analysis on the control nodes of each municipal facility, resulting in an increased risk of anomalies in the cluster management of municipal facilities, which is not conducive to the stable control of municipal facilities. Moreover, it is impossible to understand whether the current cluster operation and maintenance management is qualified, and it is also impossible to understand whether the current cluster management system needs to be optimized, thereby reducing the intelligent efficiency and stable high efficiency of the current cluster management system;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for cluster management of smart city municipal facilities to solve the above-mentioned technical defects. The present invention analyzes and plans whether the municipal facilities can be normally managed from the perspective of cluster control connection to ensure the stability and security of the Internet of Things of each planned municipal facility. And through the way of information feedback, further analyze the defect risks of cluster management from the perspective of control risks of the corresponding control nodes of the planned municipal facilities to improve the safety and stability of the current cluster management. Based on the way of information progression, analyze the efficiency level of the current cluster operation and maintenance management of the planned municipal facilities from two aspects of equipment operation and maintenance and equipment supervision, and at the same time analyze from the management performance directions of each management aspect, and then conduct reasonable and targeted optimization management on the current cluster management system to improve the efficiency of cluster operation and maintenance management.

[0006] The purpose of the present invention can be achieved by the following technical solutions: A system for cluster management of smart city municipal facilities includes a municipal facility management center, a centralized control timeliness evaluation unit, a cluster risk unit, a management efficiency evaluation feedback unit, a cluster optimization unit, and a management response unit;

[0007] The municipal facility management center is used to retrieve the Internet of Things status information of the planned municipal facilities in the target area and send it to the centralized control timeliness evaluation unit. The centralized control timeliness evaluation unit is used to conduct a centralized management effectiveness evaluation and analysis on the received Internet of Things status information to obtain a management risk signal or a management normal signal;

[0008] When a management normal signal is generated, the clustered risk unit is used to conduct a clustered management defect risk analysis on the control risk information of the collected control nodes to obtain a stable signal or a risk signal;

[0009] When a stable signal is generated, the management effectiveness evaluation feedback unit is used to conduct a clustered operation effectiveness quantitative evaluation feedback analysis on the operation and maintenance management information of the collected planned municipal facilities to obtain a compliance signal or a deviation signal;

[0010] When a stable signal is generated, the clustering optimization unit is used to conduct a clustering management performance evaluation and optimization management analysis on the clustering management projects of the collected planned municipal facilities to obtain a normal signal or an optimization signal.

[0011] Preferably, the centralized management effectiveness evaluation and analysis process is as follows:

[0012] Obtain the control nodes of the current municipal facilities in the target area, and at the same time obtain the total number of planned municipal facilities corresponding to the clustered management in the target area and the planned municipal facilities. Obtain the Internet of Things status information of the planned municipal facilities and the control nodes in the target area. The Internet of Things status information includes the connection status and the disconnection status, and conduct a discrimination process on the current municipal facilities to generate a connection signal or a loss signal.

[0013] Preferably, obtain the number of planned municipal facilities corresponding to the generated connection signal, set the ratio between the number of planned municipal facilities corresponding to the generated connection signal and the total number of planned municipal facilities as the management planning index, and conduct a discrimination process on the management planning index: if the management planning index is not equal to the preset management planning index threshold, generate a management risk signal; if the management planning index is equal to the preset management planning index threshold, generate a management normal signal.

[0014] Preferably, the clustered management defect risk analysis process is as follows:

[0015] Obtain the control risk information of the control nodes corresponding to the planned municipal facilities within the target area. The control risk information includes the joint control evaluation value and the potential risk index. Compare and analyze the joint control evaluation value and the potential risk index with the preset joint control evaluation value threshold and the preset potential risk index threshold. If the joint control evaluation value is greater than or equal to the preset joint control evaluation value threshold, and the potential risk index is greater than or equal to the preset potential risk index threshold, then set the corresponding control node as a risk node. Obtain the number of risk nodes, set the ratio of the number of risk nodes to the total number of control nodes as the cluster management evaluation coefficient, and perform discriminant processing on the cluster management evaluation coefficient to obtain a stable signal or a risk signal.

[0016] Preferably, the joint control evaluation value represents the number of times of control delay or inability to control during the control process of the control node for the planned municipal facilities; the potential risk index represents the product value obtained by multiplying the number of times of state performance defects of the control node by the frequency after data normalization processing. The state performance defects include voltage fluctuations of node equipment and node equipment failures.

[0017] Preferably, the process of cluster operation efficiency quantitative evaluation and feedback analysis is as follows:

[0018] Obtain the operation and maintenance management information of the planned municipal facilities within the target area. The operation and maintenance management information includes the operation and maintenance evaluation index and the facility management value. Label the operation and maintenance evaluation index and the facility management value as YP and SG respectively. Substitute the operation and maintenance evaluation index YP and the facility management value SG into the formula to obtain the cluster operation efficiency evaluation coefficient J, and perform discriminant processing on the cluster operation efficiency evaluation coefficient J to obtain a compliance signal or a deviation signal;

[0019] The operation and maintenance evaluation index represents the number of times of historical operation and maintenance delays or repeated operation and maintenance of the planned municipal facilities. Repeated operation and maintenance means that the number of times of operation and maintenance management of the planned municipal facilities within the preset time period exceeds 1 time; the facility management value represents the product value obtained by multiplying the number of historical update delays of the planned municipal facilities by the total delay duration after data normalization processing.

[0020] Preferably, the process of cluster management performance evaluation and optimization management analysis is as follows:

[0021] Collect the duration between the start time of cluster management of the planned municipal facilities within the target area and the current cluster management time, and set it as the analysis duration. Obtain the cluster management items of the planned municipal facilities within the target area during the analysis duration. The cluster management items include data backup and facility monitoring. Set the parameters in the cluster management items as g, where g is a natural number greater than zero. Obtain the characteristic curves of the operation efficiency values corresponding to each parameter;

[0022] The maximum peak value and the minimum valley value are obtained from the operating efficiency value characteristic curve. The difference between the maximum peak value and the minimum valley value is set as the floating evaluation value, and discriminant processing is performed on the floating evaluation value: if the floating evaluation value is less than the preset floating evaluation value threshold, a stable instruction is generated; if the floating evaluation value is greater than or equal to the preset floating evaluation value threshold, a fluctuation instruction is generated. The total number of parameters corresponding to the generated fluctuation instruction is obtained, and the ratio of the total number of parameters corresponding to the generated fluctuation instruction to g is set as the cluster optimization requirement coefficient, and discriminant processing is performed on the cluster optimization requirement coefficient to obtain a normal signal or an optimization signal.

[0023] The beneficial effects of the present invention are as follows:

[0024] (1) The present invention analyzes from the perspective of the connection of planned municipal facilities, that is, analyzes whether the planned municipal facilities can be normally managed from the perspective of cluster control connection to ensure the IoT stability and security of each planned municipal facility. At the same time, it helps to improve the cluster management efficiency of planned municipal facilities. And through the way of information feedback, further analyze the defect risk of cluster management from the perspective of the control risk of the control nodes corresponding to the planned municipal facilities, so as to intuitively understand whether there is a risk in the current cluster management through the way of information feedback, so as to perform targeted management on the control nodes to improve the security and stability of the current cluster management.

[0025] (2) The present invention analyzes the cluster operation and maintenance management efficiency level of the current planned municipal facilities from two aspects of equipment operation and maintenance and equipment supervision based on the way of information progression, so as to perform targeted adjustment of cluster operation and maintenance management based on the feedback level, so as to improve the cluster operation and maintenance management efficiency. At the same time, analyze from the management performance direction of each management angle, and then perform reasonable and targeted optimization management on the current cluster management system, thereby improving the cluster management efficiency. Description of the Drawings

[0026] The present invention will be further described below with reference to the accompanying drawings;

[0027] Figure 1 is the system flow block diagram of the present invention;

[0028] Figure 2 is the method analysis diagram of the third embodiment of the present invention. Detailed Embodiment

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] Example 1:

[0031] Please refer to Figures 1 to 2 As shown in the figure, the present invention is a cluster management system for municipal facilities in a smart city, including a municipal facility management center, a centralized control timeliness evaluation unit, a clustering risk unit, a management efficiency evaluation feedback unit, a clustering optimization unit, and a management response unit. The municipal facility management center is unidirectionally communicatively connected to the centralized control timeliness evaluation unit. The centralized control timeliness evaluation unit is unidirectionally communicatively connected to both the clustering risk unit and the management response unit. The clustering risk unit is unidirectionally communicatively connected to the management efficiency evaluation feedback unit, the clustering optimization unit, and the management response unit. Both the management efficiency evaluation feedback unit and the clustering optimization unit are unidirectionally communicatively connected to the management response unit;

[0032] The municipal facility management center is used to retrieve the Internet of Things status information of the planned municipal facilities in the target area and send the Internet of Things status information to the centralized control timeliness evaluation unit;

[0033] The centralized control timeliness evaluation unit is used to conduct a centralized management effectiveness evaluation and analysis on the received Internet of Things status information, that is, to analyze whether the planned municipal facilities can be normally managed from the perspective of clustering control connection to ensure the Internet of Things stability and security of each planned municipal facility, and at the same time help improve the clustering management efficiency of the planned municipal facilities. The specific process of centralized management effectiveness evaluation and analysis is as follows:

[0034] Obtain the control nodes of the current municipal facilities in the target area, and at the same time obtain the total number and planned municipal facilities of the planned municipal facilities corresponding to the clustering management in the target area. Obtain the Internet of Things status information of the planned municipal facilities and the control nodes in the target area. The Internet of Things status information includes the connection status and the disconnection status, and conduct discrimination processing on the current municipal facilities:

[0035] If the planned municipal facility and the control node are in a connected state, a connection signal is generated;

[0036] If the planned municipal facility and the control node are in a disconnected state, a lost signal is generated;

[0037] Obtain the number of planned municipal facilities corresponding to the generated connection signal, set the ratio between the number of planned municipal facilities corresponding to the generated connection signal and the total number of planned municipal facilities as the management planning index, and conduct discrimination processing on the management planning index:

[0038] If the management planning index is not equal to the preset management planning index threshold, a management risk signal is generated;

[0039] If the management planning index is equal to the preset management planning index threshold, a management normal signal is generated, and the management risk signal or the management normal signal is sent to the management response unit. After receiving the management risk signal or the management normal signal, the management response unit immediately performs the preset warning operations corresponding to the management risk signal or the management normal signal to ensure the IoT stability and security of each planned municipal facility, and at the same time helps to improve the cluster management efficiency of the planned municipal facilities;

[0040] When the management normal signal is generated, a cluster management defect risk analysis is further performed from the perspective of the control risk of the corresponding control node of the planned municipal facility through information feedback. That is, the cluster risk unit is used to respond to the management normal signal, collect the control risk information of the control node, and at the same time perform a cluster management defect risk analysis on the control risk information, so as to intuitively understand whether there is a risk in the current cluster management through information feedback, so as to perform targeted management on the control node to improve the security and stability of the current cluster management. The specific process of the cluster management defect risk analysis is as follows:

[0041] Obtain the control risk information of the corresponding control node of the planned municipal facility in the target area. The control risk information includes the joint control evaluation value and the potential risk index. Compare and analyze the joint control evaluation value and the potential risk index with the preset joint control evaluation value threshold and the preset potential risk index threshold. If the joint control evaluation value is greater than or equal to the preset joint control evaluation value threshold and the potential risk index is greater than or equal to the preset potential risk index threshold, the corresponding control node is set as a risk node, obtain the number of risk nodes, set the ratio of the number of risk nodes to the total number of control nodes as the cluster management evaluation coefficient, and perform a discrimination process on the cluster management evaluation coefficient:

[0042] If the cluster management evaluation coefficient is less than the preset cluster management evaluation coefficient threshold, a stable signal is generated;

[0043] If the cluster management evaluation coefficient is greater than or equal to the preset cluster management evaluation coefficient threshold, a risk signal is generated, and the stable signal or the risk signal is sent to the management response unit. After receiving the stable signal or the risk signal, the management response unit immediately performs the preset warning operations corresponding to the stable signal or the risk signal, so as to intuitively understand whether there is a risk in the current cluster management through information feedback, so as to perform targeted management on the control node to improve the security and stability of the current cluster management;

[0044] In the embodiment of the present invention, the joint control evaluation value represents the number of times of control delay or inability to control during the control process of the control node for the planned municipal facility. It should be noted that the larger the value of the joint control evaluation value, the greater the control risk of the control node;

[0045] In the embodiments of the present invention, the potential risk index represents the product value obtained by multiplying the number of times of state performance defects occurring in the control node by the frequency value after data normalization. The state performance defects include voltage fluctuations of node devices, node device failures, etc. It should be noted that potential control risk analysis is carried out from the perspective of the state performance of the control node to understand whether the control node has an impact on the cluster management.

[0046] Embodiment 2:

[0047] When a stable signal is generated, analyze the cluster operation and maintenance management efficiency level of the currently planned municipal facilities from two aspects: equipment operation and maintenance and equipment supervision, so as to make targeted adjustments to the cluster operation and maintenance management based on the feedback level situation to improve the cluster operation and maintenance management efficiency. That is, the management efficiency evaluation feedback unit is used to respond to the stable signal, collect the operation and maintenance management information of the planned municipal facilities, and at the same time conduct a cluster operation efficiency quantitative evaluation feedback analysis on the operation and maintenance management information. The specific process of the cluster operation efficiency quantitative evaluation feedback analysis is as follows:

[0048] Obtain the operation and maintenance management information of the planned municipal facilities in the target area. The operation and maintenance management information includes the operation and maintenance evaluation index and the facility management value. Label the operation and maintenance evaluation index and the facility management value as YP and SG respectively, and substitute the operation and maintenance evaluation index YP and the facility management value SG into the formula to obtain the cluster operation efficiency evaluation coefficient. Among them, a1 and a2 are the preset weight factor coefficients of the operation and maintenance evaluation index YP and the facility management value SG respectively, a3 is the preset error correction factor coefficient, a1, a2, and a3 are all greater than zero, J is the cluster operation efficiency evaluation coefficient, and discriminant processing is performed on the cluster operation efficiency evaluation coefficient J:

[0049] If the cluster operation efficiency evaluation coefficient J is less than the preset cluster operation efficiency evaluation coefficient threshold, a passing signal is generated;

[0050] If the cluster operation efficiency evaluation coefficient J is greater than or equal to the preset cluster operation efficiency evaluation coefficient threshold, a deviation signal is generated, and the passing signal or the deviation signal is sent to the management response unit. After receiving the passing signal or the deviation signal, the management response unit immediately performs the preset warning operation corresponding to the passing signal or the deviation signal, that is, analyzes the cluster operation and maintenance management efficiency level of the currently planned municipal facilities from two aspects: equipment operation and maintenance and equipment supervision, so as to make targeted adjustments to the cluster operation and maintenance management based on the feedback level situation to improve the cluster operation and maintenance management efficiency;

[0051] In the embodiments of the present invention, the operation and maintenance evaluation index represents the number of times corresponding to the historical operation and maintenance delay or repeated operation and maintenance of the planned municipal facilities. Repeated operation and maintenance means that the number of times of operation and maintenance management of the planned municipal facilities within the preset time period exceeds 1 time. It should be noted that the larger the value of the operation and maintenance evaluation index, the greater the abnormal risk of the cluster operation and maintenance management efficiency of the currently planned municipal facilities;

[0052] In an embodiment of the present invention, the facility management value is the product obtained by multiplying the corresponding number of historical update delays of planned municipal facilities by the total delay duration after data normalization processing. It should be noted that the facility management value is an influence parameter reflecting the risk of equipment cluster management efficiency. The reasonable update of facilities helps to ensure the maximization of the value of facilities, thereby improving the overall management efficiency;

[0053] When a stable signal is generated, the cluster optimization unit is used to respond to the stable signal, collect the cluster management items of the planned municipal facilities, and conduct cluster management performance evaluation and optimization management analysis on the cluster management items, so as to analyze from the management performance directions of various management perspectives, and then conduct reasonable and targeted optimization management on the current cluster management system, thereby improving the cluster management efficiency. The specific process of cluster management performance evaluation and optimization management analysis is as follows:

[0054] Collect the duration between the start time of cluster management of the planned municipal facilities in the target area and the current cluster management time, and set it as the analysis duration. Obtain the cluster management items of the planned municipal facilities in the target area during the analysis duration. The cluster management items include data backup, facility monitoring, etc. Set the parameter in the cluster management items as g, where g is a natural number greater than zero, and obtain the operating efficiency value characteristic curves corresponding to each parameter;

[0055] In an embodiment of the present invention, when g = 1, it represents data backup, and when g = 2, it represents facility monitoring, and so on;

[0056] Obtain the maximum peak value and the minimum valley value from the operating efficiency value characteristic curves, set the difference between the maximum peak value and the minimum valley value as the floating evaluation value, and conduct discriminant processing on the floating evaluation value:

[0057] If the floating evaluation value is less than the preset floating evaluation value threshold, a stable instruction is generated. If the floating evaluation value is greater than or equal to the preset floating evaluation value threshold, a fluctuation instruction is generated. Obtain the total number of parameters corresponding to the generated fluctuation instruction, set the ratio between the total number of parameters corresponding to the generated fluctuation instruction and g as the cluster optimization demand coefficient, and conduct discriminant processing on the cluster optimization demand coefficient:

[0058] If the cluster optimization demand coefficient is less than the preset cluster optimization demand coefficient threshold, a normal signal is generated;

[0059] If the cluster optimization requirement coefficient is greater than or equal to the preset cluster optimization requirement coefficient threshold, an optimization signal is generated, and a normal signal or an optimization signal is sent to the management response unit. After receiving the normal signal or the optimization signal, the management response unit immediately performs the preset warning operation corresponding to the normal signal or the optimization signal, so as to analyze from the management performance direction of each management perspective, and then perform reasonable and targeted optimization management on the current cluster management system, thereby improving the cluster management efficiency.

[0060] Embodiment 3:

[0061] A method for cluster management of municipal facilities in a smart city, comprising the following steps:

[0062] Step 1: Retrieve the IoT status information of the planned municipal facilities, and substitute the IoT status information into Step 2 for centralized management effectiveness evaluation and analysis;

[0063] Step 2: Conduct centralized management effectiveness evaluation and analysis on the IoT status information, and perform discrimination processing on the obtained management planning index. If a management risk signal is generated, output feedback. If a management normal signal is generated, proceed to Step 3;

[0064] Step 3: Conduct cluster management defect risk analysis on the collected control risk information through information feedback, and perform discrimination processing on the obtained cluster management evaluation coefficient. If a stable signal is generated, proceed to Step 4 and Step 5. If a risk signal is generated, output feedback;

[0065] Step 4: Based on the stable signal, conduct cluster operation efficiency quantitative evaluation and feedback analysis on the collected operation and maintenance management information, and perform discrimination processing on the obtained cluster operation efficiency evaluation coefficient J, and output and feedback the generated compliance signal or deviation signal;

[0066] Step 5: Based on the stable signal, conduct cluster management performance evaluation and optimization management analysis on the collected cluster management projects, and perform discrimination processing on the obtained cluster optimization requirement coefficient, and output and feedback the generated normal signal or optimization signal;

[0067] In summary, the present invention analyzes from the connection perspective of the planned municipal facilities, that is, analyzes whether the planned municipal facilities can be normally managed from the perspective of cluster control connection, so as to ensure the IoT stability and security of each planned municipal facility, and at the same time helps to improve the cluster management efficiency of the planned municipal facilities. And through information feedback, further conduct cluster management defect risk analysis from the control risk perspective of the corresponding control nodes of the planned municipal facilities, so as to intuitively understand whether there are risks in the current cluster management through information feedback, so as to conduct targeted management on the control nodes to improve the security and stability of the current cluster management;

[0068] Analyze the efficiency level of the clustered operation and maintenance management of current planned municipal facilities from two aspects: equipment operation and maintenance and equipment supervision based on the information progression method, so as to make targeted adjustments to the clustered operation and maintenance management based on the feedback level, improve the efficiency of the clustered operation and maintenance management. At the same time, analyze from the management performance directions of each management aspect, and then optimize the current cluster management system reasonably and pertinently, so as to improve the cluster management efficiency.

[0069] The setting of the threshold value is for the convenience of comparison. Regarding the size of the threshold value, it depends on the amount of sample data and the base quantity set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantified value.

[0070] The size of the coefficient is a specific value obtained by quantifying each parameter for the convenience of subsequent comparison. Regarding the size of the coefficient, it depends on the amount of sample data and the initial operation coefficient set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantified value.

[0071] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients in the formulas are set by those skilled in the art according to the actual situation. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A cluster management system for municipal facilities in a smart city, characterized in that, It includes a municipal facilities management center, a centralized control timeliness evaluation unit, a clustered risk unit, a management effectiveness evaluation feedback unit, a clustered optimization unit, and a management response unit; The municipal facilities management center is used to retrieve the Internet of Things status information of the planned municipal facilities in the target area and send it to the centralized control timeliness evaluation unit. The centralized control timeliness evaluation unit is used to conduct a centralized management effectiveness evaluation and analysis on the received Internet of Things status information to obtain a management risk signal or a management normal signal; When a management normal signal is generated, the clustered risk unit is used to conduct a clustered management defect risk analysis on the control risk information of the collected control nodes to obtain a stable signal or a risk signal; When a stable signal is generated, the management effectiveness evaluation feedback unit is used to conduct a clustered operation effectiveness quantitative evaluation feedback analysis on the operation and maintenance management information of the collected planned municipal facilities to obtain a compliance signal or a deviation signal; When a stable signal is generated, the clustered optimization unit is used to conduct a clustered management performance evaluation and optimized management analysis on the clustered management projects of the collected planned municipal facilities to obtain a normal signal or an optimization signal.

2. The cluster management system for urban-rural public facilities according to claim 1, wherein The process of the centralized management effectiveness evaluation and analysis is as follows: Obtain the control nodes of the current municipal facilities in the target area, and at the same time obtain the total number of planned municipal facilities and the planned municipal facilities corresponding to the clustered management in the target area. Obtain the Internet of Things status information of the planned municipal facilities and the control nodes in the target area. The Internet of Things status information includes the connection status and the disconnection status, and conduct a discrimination process on the current municipal facilities to generate a connection signal or a loss signal.

3. The cluster management system for urban construction facilities in a smart city according to claim 2, characterized in that, Obtain the number of planned municipal facilities corresponding to the generated connection signal, set the ratio between the number of planned municipal facilities corresponding to the generated connection signal and the total number of planned municipal facilities as the management planning index, and conduct a discrimination process on the management planning index: if the management planning index is not equal to the preset management planning index threshold, generate a management risk signal; If the management planning index is equal to the preset management planning index threshold, generate a management normal signal.

4. A cluster management system for urban infrastructure in a smart city according to claim 1, characterized in that, The process of the clustered management defect risk analysis is as follows: Obtain the control risk information of the control nodes corresponding to the planned municipal facilities in the target area. The control risk information includes the joint control evaluation value and the potential risk index. Compare and analyze the joint control evaluation value and the potential risk index with the preset joint control evaluation value threshold and the preset potential risk index threshold. If the joint control evaluation value is greater than or equal to the preset joint control evaluation value threshold and the potential risk index is greater than or equal to the preset potential risk index threshold, set the corresponding control node as a risk node, obtain the number of risk nodes, set the ratio of the number of risk nodes to the total number of control nodes as the clustered management evaluation coefficient, and conduct a discrimination process on the clustered management evaluation coefficient to obtain a stable signal or a risk signal.

5. The cluster management system for smart city municipal facilities according to claim 4, characterized in that, The joint control evaluation value represents the number of times of control delay or inability to control during the control process of the control node for the planned municipal facilities; the potential risk index represents the product value obtained by multiplying the number of times and frequency of the state performance defects of the control node after data normalization processing. The state performance defects include node device voltage fluctuations and node device failures.

6. The cluster management system for smart city municipal facilities according to claim 1, characterized in that, The process of the clustered operation effectiveness quantitative evaluation feedback analysis is as follows: Obtain the operation and maintenance management information of the planned municipal facilities within the target area. The operation and maintenance management information includes the operation and maintenance evaluation index and the facility management value. Label the operation and maintenance evaluation index and the facility management value as YP and SG respectively. Substitute the operation and maintenance evaluation index YP and the facility management value SG into the formula to obtain the cluster operation efficiency evaluation coefficient J, and perform discriminant processing on the cluster operation efficiency evaluation coefficient J to obtain a compliance signal or a deviation signal. The operation and maintenance evaluation index represents the number of times corresponding to the historical operation and maintenance delay or repeated operation and maintenance of the planned municipal facilities. Repeated operation and maintenance means that the number of times of operation and maintenance management of the planned municipal facilities exceeds 1 time within the preset duration. The facility management value represents the product value obtained by multiplying the number of historical update delays of the planned municipal facilities by the total delay duration after data normalization processing.

7. A cluster management system for urban infrastructure in a smart city according to claim 1, characterized in that, The cluster management performance evaluation and optimization management analysis process is as follows: Collect the duration between the start time of the cluster management of the planned municipal facilities in the target area and the current cluster management time, and set it as the analysis duration. Obtain the cluster management items of the planned municipal facilities in the target area during the analysis duration. The cluster management items include data backup and facility monitoring. Set the parameters in the cluster management items as g, where g is a natural number greater than zero. Obtain the characteristic curves of the operation efficiency values corresponding to each parameter. Obtain the maximum peak value and the minimum valley value from the characteristic curve of the operation efficiency value. Set the difference between the maximum peak value and the minimum valley value as the floating evaluation value, and perform discriminant processing on the floating evaluation value: If the floating evaluation value is less than the preset floating evaluation value threshold, generate a stability instruction. If the floating evaluation value is greater than or equal to the preset floating evaluation value threshold, generate a fluctuation instruction. Obtain the total number of parameters corresponding to the generated fluctuation instruction. Set the ratio between the total number of parameters corresponding to the generated fluctuation instruction and g as the cluster optimization demand coefficient, and perform discriminant processing on the cluster optimization demand coefficient to obtain a normal signal or an optimization signal.

8. A method for cluster management of municipal facilities in a smart city, which is applied to the cluster management system of municipal facilities in a smart city according to any one of claims 1-7, characterized in that, It includes the following steps: Step 1: Retrieve the Internet of Things status information of the planned municipal facilities and substitute the Internet of Things status information into Step 2 for centralized management effectiveness evaluation and analysis. Step 2: Conduct centralized management effectiveness evaluation and analysis on the Internet of Things status information, and perform discriminant processing on the obtained management planning index. If a management risk signal is generated, output feedback. If a management normal signal is generated, proceed to Step 3. Step 3: Conduct cluster management defect risk analysis on the collected control risk information through information feedback, and perform discriminant processing on the obtained cluster management evaluation coefficient. If a stability signal is generated, proceed to Step 4 and Step 5. If a risk signal is generated, output feedback. Step 4: Based on the stability signal, conduct cluster operation efficiency quantitative evaluation and feedback analysis on the collected operation and maintenance management information, and perform discriminant processing on the obtained cluster operation efficiency evaluation coefficient J, and output the generated compliance signal or deviation signal as feedback. Step 5: Based on the stability signal, conduct cluster management performance evaluation and optimization management analysis on the collected cluster management items, and perform discriminant processing on the obtained cluster optimization demand coefficient, and output the generated normal signal or optimization signal as feedback.

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