Equipment monitoring method and system based on intelligent station

Abstract

The present invention discloses an equipment monitoring method and system based on an intelligent station, and relates to the technical field of equipment monitoring. For a number of parking spaces in a parking lot, the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring equipment of each parking space when sending parking status information of the parking space to a management platform are obtained, and clustering is performed as the data points of each parking space to determine the state unqualified coefficient; when the state unqualified coefficient is less than a first preset state unqualified coefficient threshold, the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold are determined according to the state unqualified coefficient of the parking space and the first preset monitoring equipment monitoring cycle and the first preset state unqualified coefficient threshold, and it is re-determined whether the monitoring equipment needs to be replaced and repaired, so that the state of the monitoring equipment of the parking space can be detected in time, and replaced or repaired, so that the work of the management platform is orderly and the impact on the operation efficiency of the parking lot is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment monitoring, and in particular to an equipment monitoring method and system based on an intelligent station. Background Art

[0002] Smart parking lots are comprehensive management platforms that integrate advanced information technology and intelligent equipment. They are mainly used to improve parking lot management efficiency and user experience. In smart parking lot scenarios, smart parking lots use license plate recognition systems to enable fast entry and exit. They are also equipped with intelligent navigation functions to help drivers quickly find vacant parking spaces. In addition, using big data analysis, smart parking lots can monitor the usage status of each parking space in the parking lot in real time, optimize parking space allocation, reduce congestion, and improve vehicle turnover.

[0003] Among them, when judging the usage status of each parking space, a number of detection and monitoring devices, such as cameras and sensors, are installed on each parking space to monitor the parking status of each parking space in real time and send it to the management platform in time so that the management platform can perform subsequent operations, so that drivers can park efficiently and improve the convenience of scheduling;

[0004] However, in actual situations, if there is a problem with the parking space monitoring equipment and it is not detected in time and the monitoring equipment is not replaced or repaired, it may lead to inaccurate parking status monitoring of the parking space, which may cause chaos in the subsequent work of the entire management platform and affect the operational efficiency of the parking lot. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems and provide an equipment monitoring method and system based on an intelligent station.

[0006] In a first aspect of the present invention, a device monitoring method based on a smart station is first proposed, the method comprising:

[0007] For several parking spaces in the parking lot, obtain the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring device of each parking space when sending parking status information of the parking space to the management platform;

[0008] The data upload abnormality coefficient, the signal connection instability coefficient and the maintenance coefficient are used as data points of each parking space to obtain a data set, and the data set is clustered to determine the state unqualified coefficient of each parking space monitoring device;

[0009] Comparing the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold, and determining the state of each parking space monitoring device as a fault state and a temporary normal state according to the comparison result;

[0010] When the status of the monitoring equipment of the parking space is temporarily normal, the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold are determined according to the unqualified coefficient of the status corresponding to the parking space and the first preset monitoring equipment monitoring cycle and the first preset state unqualified coefficient threshold, and the monitoring equipment of each parking space is re-determined whether it needs to be replaced and repaired according to the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold.

[0011] Optionally, the data upload abnormality coefficient includes:

[0012] For each parking space in the parking lot, obtain the timestamp of each monitoring device in the parking space sending parking status information to the management platform within a preset time period, calculate the interval between adjacent timestamps, and sequence them based on time to obtain the time interval sequence of the corresponding monitoring device;

[0013] Compare the time interval in the time interval sequence with the preset time interval, record the data greater than the preset time interval as the delayed time interval, divide the total number of delayed time intervals by the total number of time interval sequences, and obtain the data upload time delay coefficient of the monitoring device corresponding to the monitoring device;

[0014] Calculate the average of the data upload time delay coefficients of all monitoring devices in the parking space as the delay coefficient of the corresponding parking space;

[0015] Obtain the total number of times all monitoring devices of each parking space send parking status information to the management platform, and obtain the total number of times the parking status information uploaded by all monitoring devices is inconsistent, and divide the total number of times the parking status information is inconsistent by the total number of times the parking status information is sent to obtain the data inconsistency coefficient of the corresponding parking space;

[0016] The delay coefficient and data inconsistency coefficient of each parking space are normalized, and the data upload abnormality coefficient of the corresponding parking space is obtained according to the normalized delay coefficient and data inconsistency coefficient. The calculation formula is: , where Upload the anomaly coefficient for the data, and are the normalized delay coefficient and data inconsistency coefficient, and They are respectively the preset weight coefficients of the normalized delay coefficient and the data inconsistency coefficient.

[0017] Optionally, the signal connection instability coefficient includes:

[0018] Continuously acquiring the network signal value of the connection between each monitoring device of the parking space and the management platform within a preset time period at multiple times to obtain a network signal value sequence;

[0019] Calculate the standard deviation of the network signal value, and use the standard deviation of the network signal value as the network signal fluctuation value;

[0020] Compare each signal value in the network signal value sequence with a preset minimum signal value, and record a value less than the preset minimum signal value as the minimum signal value;

[0021] Divide the total number of low signal values ​​in the network signal value sequence by the number of all values ​​in the network signal value sequence to obtain a signal failure value;

[0022] The network signal fluctuation values ​​and signal unqualified values ​​of all monitoring devices are normalized, and the signal connection instability coefficient of the corresponding parking space is obtained according to the normalized network signal fluctuation values ​​and signal unqualified values. The calculation formula is: , where is the signal connection instability coefficient, and are the normalized network signal fluctuation value and signal unqualified value, Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. and are the preset proportional coefficients corresponding to the normalized network signal fluctuation value and the signal unqualified value, respectively, and and Both are greater than 0.

[0023] Optionally, the maintenance factor includes:

[0024] For each parking space in the parking lot, obtain the time interval from the last maintenance of each monitoring device in the parking space within a preset time period as the actual maintenance time interval;

[0025] Obtain the average maintenance time interval of each monitoring device, and calculate the difference between the average maintenance time interval and the actual maintenance time interval as the maintenance interval coefficient;

[0026] The total number of failures and the average cost of each failure of each monitoring device in the parking space within the preset time period are obtained, and the total number of failures, the average time for each failure repair, and the maintenance interval coefficient are normalized. According to the normalized total number of failures, the average time for each repair, and the maintenance interval coefficient, the maintenance coefficient of the corresponding parking space is obtained. The calculation formula is:

[0027] , where is the maintenance factor, , and are the normalized total number of failures, the average time spent on each maintenance, and the maintenance interval coefficient, respectively. Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. , , are respectively the normalized total number of failures, the average time spent on each maintenance, and the preset proportional coefficients corresponding to the maintenance interval coefficient, and , , Both are greater than 0.

[0028] Optionally, clustering the data set to determine the status unqualified coefficient of each parking space monitoring device includes:

[0029] The steps to cluster the data set using the K-means clustering method are:

[0030] Step 1: Used to determine the optimal number of clusters for the data set using the elbow method;

[0031] Step 2: Randomly select a corresponding number of data points as initial clusters according to the optimal number of clusters;

[0032] Step 3: For each data point, use the Euclidean distance algorithm to calculate the distance between the data point and each initial cluster center, and assign the data point to the cluster to which the nearest cluster center belongs. After traversing all data points, the initial cluster center is obtained.

[0033] Step 4: Calculate the average value of all data points for each initial cluster and use the average value as the new cluster center;

[0034] Step 5: It is used to determine whether the cluster center has changed. If it has changed, repeat steps 3 and 4 until the cluster center no longer changes, and obtain the final cluster and the final cluster center;

[0035] The final clusters and the final cluster centers are mapped to three-dimensional coordinates to obtain the status unqualified coefficient of each parking space monitoring device.

[0036] Optionally, the final clusters and the final cluster centers are mapped to three-dimensional coordinates to obtain the state unqualified coefficients of each parking space monitoring device, including:

[0037] Calculate the weight coefficient of each final cluster, the calculation formula is: ,in Expressed as The weight coefficients of the final clusters, Represented as the number of all data points in the dataset, Indicates The number of data points in the final clusters;

[0038] Calculate the distance of each data point in each final cluster to the coordinate origin in three-dimensional coordinates to obtain the preliminary coordinate distance of the data point, and multiply the preliminary coordinate distance of the data point by the weight coefficient corresponding to the final cluster in which the data point is located to obtain the actual coordinate distance of the data point;

[0039] The actual coordinate distance of each data point is used as the status failure coefficient of the corresponding parking space monitoring device.

[0040] Optionally, determining whether each parking space monitoring device needs to be replaced or repaired according to the comparison result includes:

[0041] Compare the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold value. If the state unqualified coefficient is not less than the first preset state unqualified coefficient threshold value, it is determined that the corresponding parking space monitoring device needs to be replaced and repaired, and the management platform marks the parking state of the corresponding parking space as a fault state;

[0042] If the status unqualified coefficient is less than the first preset status unqualified coefficient threshold, it is determined that the corresponding parking space monitoring equipment does not need to be replaced and repaired temporarily, and the management platform marks the parking status of the corresponding parking space as temporarily normal.

[0043] Optionally, determining the second preset monitoring device monitoring period and the second preset state unqualified coefficient threshold according to the state unqualified coefficient corresponding to the parking space, the first preset monitoring device monitoring period, and the first preset state unqualified coefficient threshold includes:

[0044] ;

[0045] In the formula, , , , , They are respectively the state unqualified coefficient, the first preset monitoring device monitoring period, the first preset state unqualified coefficient threshold, the second preset monitoring device monitoring period and the second preset state unqualified coefficient threshold.

[0046] Optionally, re-determining whether the monitoring device of each parking space needs to be replaced and repaired according to the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold includes:

[0047] When the parking state of the parking space is temporarily normal, after the second preset monitoring device monitoring cycle, the state unqualified coefficient of the monitoring device of each parking space is obtained, and the state unqualified coefficient of the monitoring device of each parking space is compared with the second preset state unqualified coefficient threshold;

[0048] If the status unqualified coefficient is less than the second preset status unqualified coefficient threshold, the monitoring equipment of the corresponding parking space does not need to be replaced and repaired; if the status unqualified coefficient is not less than the second preset status unqualified coefficient threshold, the monitoring equipment of the corresponding parking space needs to be replaced and repaired.

[0049] In a second aspect of the present invention, a device monitoring system based on an intelligent station is proposed, comprising:

[0050] Data acquisition module: for several parking spaces in the parking lot, obtain the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring equipment of each parking space when sending parking status information of the parking space to the management platform;

[0051] Cluster analysis module: taking the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient as the data points of each parking space, obtaining a data set, clustering the data set to determine the state unqualified coefficient of each parking space monitoring device;

[0052] Classification module: compare the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold, and determine the state of each parking space monitoring device as a fault state and a temporary normal state according to the comparison result;

[0053] Judgment module: When the status of the monitoring device of the parking space is temporarily normal, the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold are determined according to the unqualified coefficient of the status corresponding to the parking space and the first preset monitoring device monitoring cycle and the first preset state unqualified coefficient threshold, and the monitoring equipment of each parking space is re-judged whether it needs to be replaced and repaired according to the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold.

[0054] Beneficial effects of the present invention:

[0055] The present invention proposes an equipment monitoring method and system based on an intelligent station. For several parking spaces in a parking lot, a data upload abnormality coefficient, a signal connection instability coefficient and a maintenance coefficient of a monitoring device of each parking space are obtained when the monitoring device sends parking status information of the parking space to a management platform, and the data are used as data points of each parking space to obtain a data set, and the data set is clustered to determine the state unqualified coefficient of each parking space monitoring device; the state unqualified coefficient of each parking space is compared with a first preset state unqualified coefficient threshold, and the state of each parking space monitoring device is determined to be a fault state and a temporary normal state according to the comparison result; when the state of the monitoring device of the parking space is a temporary normal state, a second preset monitoring device monitoring cycle and a second preset state unqualified coefficient threshold are determined according to the state unqualified coefficient corresponding to the parking space, the first preset monitoring device monitoring cycle, and the first preset state unqualified coefficient threshold, and the monitoring device of each parking space is re-determined whether it needs to be replaced and repaired. In this way, in actual situations, the state of the monitoring device of the parking space can be detected in time, and the monitoring device can be replaced or repaired in time, so as to ensure that the parking state monitoring of the parking space is accurate, so that the work of the management platform is orderly, and the impact on the operation efficiency of the parking lot is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described below in conjunction with the accompanying drawings.

[0057] Figure 1 It is a flow chart of the equipment monitoring method based on the intelligent station;

[0058] Figure 2 This is a framework diagram of the equipment monitoring system based on smart stations. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0061] The embodiment of the present invention provides a device monitoring method based on an intelligent station. Figure 1 , Figure 1 A flow chart of a device monitoring method based on a smart station provided in an embodiment of the present invention. The method comprises the following steps:

[0062] For several parking spaces in the parking lot, obtain the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring device of each parking space when sending parking status information of the parking space to the management platform;

[0063] The data upload abnormality coefficient, the signal connection instability coefficient and the maintenance coefficient are used as data points of each parking space to obtain a data set, and the data set is clustered to determine the state unqualified coefficient of each parking space monitoring device;

[0064] Comparing the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold, and determining the state of each parking space monitoring device as a fault state and a temporary normal state according to the comparison result;

[0065] When the status of the monitoring equipment of the parking space is temporarily normal, the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold are determined according to the unqualified coefficient of the status corresponding to the parking space and the first preset monitoring equipment monitoring cycle and the first preset state unqualified coefficient threshold, and the monitoring equipment of each parking space is re-determined whether it needs to be replaced and repaired according to the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold.

[0066] Based on the equipment monitoring method based on the smart station provided by the embodiment of the present invention, through the above-mentioned method, in actual situations, it is possible to timely detect the status of the parking space monitoring equipment, and timely replace or repair the monitoring equipment to ensure accurate parking status monitoring of the parking space, so that the management platform can work in an orderly manner and reduce the impact on the operating efficiency of the parking lot.

[0067] In one embodiment, the data upload abnormality coefficient includes:

[0068] For each parking space in the parking lot, obtain the timestamp of each monitoring device in the parking space sending parking status information to the management platform within a preset time period, calculate the interval between adjacent timestamps, and sequence them based on time to obtain the time interval sequence of the corresponding monitoring device;

[0069] Compare the time interval in the time interval sequence with the preset time interval, record the data greater than the preset time interval as the delayed time interval, divide the total number of delayed time intervals by the total number of time interval sequences, and obtain the data upload time delay coefficient of the monitoring device corresponding to the monitoring device;

[0070] Calculate the average of the data upload time delay coefficients of all monitoring devices in the parking space as the delay coefficient of the corresponding parking space;

[0071] Obtain the total number of times all monitoring devices of each parking space send parking status information to the management platform, and obtain the total number of times the parking status information uploaded by all monitoring devices is inconsistent, and divide the total number of times the parking status information is inconsistent by the total number of times the parking status information is sent to obtain the data inconsistency coefficient of the corresponding parking space;

[0072] The delay coefficient and data inconsistency coefficient of each parking space are normalized, and the data upload abnormality coefficient of the corresponding parking space is obtained according to the normalized delay coefficient and data inconsistency coefficient. The calculation formula is: , where Upload the anomaly coefficient for the data, and are the normalized delay coefficient and data inconsistency coefficient, and They are respectively the preset weight coefficients of the normalized delay coefficient and the data inconsistency coefficient.

[0073] It should be noted that , It is set by professionals according to the actual situation. Generally, , The sum of is 1, for example , They can be 0.5, 0.5, or other numbers respectively, and are not specifically limited.

[0074] It should be noted that commonly used normalization methods include Min-Max normalization, Z-Score normalization, etc. The specific processing method is selected by professionals according to the actual situation and is not limited or elaborated.

[0075] It should be noted that the preset time period and preset time interval are set by professionals according to the actual situation. For example, every 5 minutes can be set as a preset time interval, or it can be other numbers, which are not limited or elaborated on. In addition, each time the information is sent, the monitoring device will be accompanied by a timestamp to record the specific time when the information was sent. The management platform will receive these timestamps and store them in the database for subsequent analysis. At the same time, the management platform will record the total number of parking status information sent by each monitoring device within the preset time period, and identify the total number of inconsistencies in the parking status information uploaded by all monitoring devices each time the parking status information is sent.

[0076] It should be noted that when the time delay of each monitoring device of the parking space sending the parking status information of the parking space to the management platform is greater and the proportion of inconsistent parking status information uploaded by different monitoring devices at each upload is greater, that is, the greater the delay coefficient, the greater the data inconsistency coefficient, that is, the greater the data upload abnormality coefficient, it means that there is a problem with the monitoring device of the parking space, and if it is not detected in time and the equipment is replaced or repaired, it may cause inaccurate parking status monitoring of the parking space, which may cause confusion in the subsequent work of the entire management platform and affect the operation efficiency of the parking lot. The reason is that when the data upload abnormality coefficient is larger, it means that the reliability and accuracy of the monitoring equipment are decreasing; this situation indicates that the equipment may have a fault or malfunction, and cannot collect and transmit data normally, resulting in the management platform being unable to obtain real-time and accurate parking space usage status; if these problems are not detected in time and the equipment is replaced or repaired, it will cause the parking lot management platform to deviate from the real-time monitoring of the parking space, thereby affecting the allocation of parking spaces, user navigation and parking experience. In addition, data inconsistency may cause confusion in management decisions, affect vehicle scheduling, charging and service quality, and thus reduce the overall operation efficiency of the parking lot.

[0077] In one embodiment, the signal connection instability coefficient includes:

[0078] Continuously acquiring the network signal value of the connection between each monitoring device of the parking space and the management platform within a preset time period at multiple times to obtain a network signal value sequence;

[0079] Calculate the standard deviation of the network signal value, and use the standard deviation of the network signal value as the network signal fluctuation value;

[0080] Compare each signal value in the network signal value sequence with a preset minimum signal value, and record a value less than the preset minimum signal value as the minimum signal value;

[0081] Divide the total number of low signal values ​​in the network signal value sequence by the number of all values ​​in the network signal value sequence to obtain a signal failure value;

[0082] The network signal fluctuation values ​​and signal unqualified values ​​of all monitoring devices are normalized, and the signal connection instability coefficient of the corresponding parking space is obtained according to the normalized network signal fluctuation values ​​and signal unqualified values. The calculation formula is: , where is the signal connection instability coefficient, and are the normalized network signal fluctuation value and signal unqualified value, Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. and are the preset proportional coefficients corresponding to the normalized network signal fluctuation value and the signal unqualified value, respectively, and and Both are greater than 0.

[0083] It should be noted that and It is set by professionals according to the actual situation. Generally, and The sum of is 1, for example and They can be 0.4, 0.6, or other numbers respectively, and are not specifically limited.

[0084] It should be noted that the preset minimum signal value is set by professionals based on actual conditions, and no specific restrictions or elaborations are made; the network signal value is the signal strength, usually expressed in decibel milliwatts (dBm), which reflects the signal strength between the monitoring device and the management platform. The higher the signal strength, the more stable the connection; in addition, the network signal value can be obtained in real time through the network monitoring tool of the management platform and the signal strength between the monitoring devices, or it can be obtained by other means, and no specific restrictions or elaborations are made.

[0085] It should be noted that the greater the fluctuation value of the network signal connecting the monitoring equipment and the management platform, the greater the signal unqualified value, that is, the greater the signal connection instability coefficient, it means that there is a problem with the parking space monitoring equipment. If it is not detected in time and the equipment is not replaced or repaired, it may cause inaccurate parking status monitoring of the parking space, and may cause subsequent chaos in the work of the entire management platform, affecting the operating efficiency of the parking lot. The reason is that the greater the signal connection instability coefficient, the more likely it is that the monitoring equipment will not be able to accurately and in real time transmit parking status information; if this situation is not detected in time and the equipment is not replaced or repaired, the parking status monitoring of the parking lot will become inaccurate, resulting in the management platform being unable to accurately grasp the usage of each parking space, which will cause vehicles to enter and exit smoothly and unreasonable allocation of parking resources, ultimately affecting the operating efficiency of the parking lot.

[0086] In one embodiment, the maintenance factor includes:

[0087] For each parking space in the parking lot, obtain the time interval from the last maintenance of each monitoring device in the parking space within a preset time period as the actual maintenance time interval;

[0088] Obtain the average maintenance time interval of each monitoring device, and calculate the difference between the average maintenance time interval and the actual maintenance time interval as the maintenance interval coefficient;

[0089] The total number of failures and the average cost of each failure of each monitoring device in the parking space within the preset time period are obtained, and the total number of failures, the average time for each failure repair, and the maintenance interval coefficient are normalized. According to the normalized total number of failures, the average time for each repair, and the maintenance interval coefficient, the maintenance coefficient of the corresponding parking space is obtained. The calculation formula is:

[0090] , where is the maintenance factor, , and are the normalized total number of failures, the average time spent on each maintenance, and the maintenance interval coefficient, respectively. Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. , , are respectively the normalized total number of failures, the average time spent on each maintenance, and the preset proportional coefficients corresponding to the maintenance interval coefficient, and , , Both are greater than 0.

[0091] It should be noted that , , , is set by professionals according to the actual situation. Generally, , , The sum of is 1, for example , , They can be 0.3, 0.3, 0.4 respectively, or other numbers, without limitation.

[0092] It should be noted that the actual maintenance time interval, average maintenance time interval, total number of failures, average maintenance cost and maintenance time of each parking space monitoring device can be obtained through the historical data records of the parking lot monitoring system. It can also be obtained in other ways, which are not limited or elaborated on.

[0093] It should be noted that the smaller the maintenance interval coefficient of the monitoring equipment, the greater the total number of failures of each monitoring equipment in the parking space within the preset time period, the greater the average cost of each failure, that is, the larger the maintenance coefficient, which means that there is a problem with the monitoring equipment of the parking space, and if it is not detected and replaced or repaired in time, it may cause inaccurate parking status monitoring of the parking space, which may cause confusion in the subsequent work of the entire management platform and affect the operation efficiency of the parking lot. The reason is that when the maintenance interval coefficient of the monitoring equipment is small, it means that the longer the time since the last maintenance of the equipment, it may imply that the equipment has not undergone necessary maintenance or inspection during long-term operation, thereby increasing the risk of potential failures; the more total failures within the preset time period, the more frequent the equipment failures and the poor reliability; the higher the average cost of each failure, the more difficult the maintenance or the need to replace key components. These factors lead to a larger maintenance coefficient; this means that the performance degradation or aging problem of the monitoring equipment has not been detected and handled in time, which may cause inaccurate parking space status information, and then cause the parking lot management platform to misjudge the parking space occupancy, resulting in confusion in scheduling and parking guidance, thereby affecting the overall operation efficiency.

[0094] In one embodiment, clustering the data set to determine the status unqualified coefficient of each parking space monitoring device includes:

[0095] The steps to cluster the data set using the K-means clustering method are:

[0096] Step 1: Used to determine the optimal number of clusters for the data set using the elbow method;

[0097] Step 2: Randomly select a corresponding number of data points as initial clusters according to the optimal number of clusters;

[0098] Step 3: For each data point, use the Euclidean distance algorithm to calculate the distance between the data point and each initial cluster center, and assign the data point to the cluster to which the nearest cluster center belongs. After traversing all data points, the initial cluster center is obtained.

[0099] Step 4: Calculate the average value of all data points for each initial cluster and use the average value as the new cluster center;

[0100] Step 5: It is used to determine whether the cluster center has changed. If it has changed, repeat steps 3 and 4 until the cluster center no longer changes, and obtain the final cluster and the final cluster center;

[0101] The final clusters and the final cluster centers are mapped to three-dimensional coordinates to obtain the status unqualified coefficient of each parking space monitoring device.

[0102] In one implementation, according to the above method, the optimal clustering results of the data set can be obtained. These clustering results can be used to identify different clusters in the data set, as well as the center and characteristics of each cluster. Such clustering results are helpful for further data analysis and interpretation.

[0103] It should be noted that clustering the data set by K-means clustering is simple and efficient, and can quickly process large-scale data sets; K-means clustering is a commonly used unsupervised learning algorithm, which is used to divide the data set into pre-defined K clusters; the goal of this algorithm is to divide the data points into K clusters, so that each data point belongs to the cluster represented by the cluster center closest to it, and the data points within the cluster are as similar as possible, while the data points between different clusters may not be similar;

[0104] Cluster analysis can help evaluate the degree of unqualified status of each parking space monitoring device; if the data upload abnormality coefficient of each parking space is larger, the signal connection instability coefficient is larger, and the maintenance coefficient is larger, it means that the state of the monitoring equipment of each parking space is more unqualified; conversely, if the data upload abnormality coefficient of each parking space is smaller, the signal connection instability coefficient is smaller, and the maintenance coefficient is smaller, it means that the state of the monitoring equipment of each parking space is less unqualified; through cluster analysis, we can understand the degree of unqualified status of the monitoring equipment of each parking space, and thus determine whether to repair the monitoring equipment corresponding to the parking space.

[0105] Therefore, a data set is obtained by taking the data upload anomaly coefficient, signal connection instability coefficient and maintenance coefficient of each parking space as the data point of each parking space, and the data set is clustered to determine the degree of unqualified status of the monitoring equipment of each parking space; and the data upload anomaly coefficient, signal connection instability coefficient and maintenance coefficient of each parking space present a common linear relationship. The larger the data upload anomaly coefficient of each parking space, the larger the signal connection instability coefficient and the larger the maintenance coefficient, the greater the corresponding degree of unqualified status of the monitoring equipment of each parking space.

[0106] It should be noted that step 1: using the elbow method to determine the optimal number of clusters for the data set; the elbow method is one of the common methods used to determine the optimal number of clusters K in K-means clustering. The basic idea is to find an "elbow point" by observing the relationship between the number of clusters K and the total internal deviation square sum (WCSS) of the clustering results. The K value corresponding to the "elbow point" is the position where the rate of decrease of WCSS slows down significantly after the number of clusters increases to a certain extent. WCSS refers to the sum of the squares of the distances from each data point to the center of the cluster to which it belongs, which indicates the compactness of the clustering results.

[0107] Step 2: According to the optimal number of clusters, randomly select the corresponding number of data points from the data points as the initial cluster centers of clustering. The initial cluster centers refer to the K cluster centers randomly selected before starting the clustering process. These initial cluster centers are the starting points of the algorithm.

[0108] Step 3: For each data point in the data set, calculate the distance between it and each cluster center using the Euclidean distance. For example, calculate the data point and the initial cluster centers The distance between , and its calculation formula is , and assign the data point to the cluster to which the nearest cluster center belongs. Euclidean distance refers to the distance between two points in Euclidean space, and is also one of the most commonly used distance metrics. In K-means clustering, Euclidean distance is usually used to calculate the distance between a data point and a cluster center.

[0109] Step 4: For each cluster, calculate the mean of all its data points and use the mean as the new cluster center. The calculation formula is: ,in Expressed as The set of data points in a cluster, Expressed as The new cluster centers of the clusters;

[0110] Step 5: Repeat steps 3 and 4 until the cluster center no longer changes, and obtain the final cluster and the final cluster center.

[0111] It should be specifically explained that the step of assigning a data point to the cluster to which the nearest cluster center belongs is to sort the distances between the data point and each cluster center from large to small, and select the smallest distance to assign the data point to the cluster to which it belongs.

[0112] In one embodiment, the final clusters and the final cluster centers are mapped to three-dimensional coordinates to obtain the state unqualified coefficients of each parking space monitoring device, including:

[0113] Calculate the weight coefficient of each final cluster, the calculation formula is: ,in Expressed as The weight coefficients of the final clusters, Represented as the number of all data points in the dataset, Indicates The number of data points in the final clusters;

[0114] Calculate the distance of each data point in each final cluster to the coordinate origin in three-dimensional coordinates to obtain the preliminary coordinate distance of the data point, and multiply the preliminary coordinate distance of the data point by the weight coefficient corresponding to the final cluster in which the data point is located to obtain the actual coordinate distance of the data point;

[0115] The actual coordinate distance of each data point is used as the status failure coefficient of the corresponding parking space monitoring device.

[0116] In one implementation, according to the above method, the obtained unqualified coefficient of the status of the monitoring equipment of each parking space is more accurate and can better reflect the degree of unqualified status of the monitoring equipment of each parking space.

[0117] It should be noted that, because the data upload anomaly coefficient, signal connection instability coefficient and maintenance coefficient are selected as data points for clustering, these three data points can now be used as coordinates and mapped to the three-dimensional coordinate axis, and each parking space will be mapped as a point on the three-dimensional coordinate axis; after the clustering is completed, all the data points will be distributed in different final clustering clusters on the three-dimensional coordinate axis. The closer the final clustering cluster is to the original center and the smaller the state unqualified coefficient of each parking space monitoring device corresponding to the data point included therein is, the better the state of the parking space monitoring device is, and vice versa; at the same time, the weight coefficient of each final clustering cluster is calculated to correct the distance from the data point to the original center. In this way, the different importance of each final clustering cluster can be ensured, and the influence of noise and outliers on the clustering results can be reduced to a certain extent, so that the final calculated state unqualified coefficient of each parking space monitoring device is more accurate.

[0118] In one implementation, the unqualified status coefficient of the monitoring equipment calculated by the above method has the advantages of multi-dimensional analysis, identification of group characteristics, improved accuracy, visual display and dynamic adjustment; this method can comprehensively evaluate the unqualified status of the monitoring equipment, reduce the impact of noise and outliers, so that the finally calculated unqualified status coefficient can more accurately reflect the unqualified status of the monitoring equipment of the corresponding parking space.

[0119] In one embodiment, determining whether each parking space monitoring device needs to be replaced or repaired according to the comparison result includes:

[0120] Compare the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold value. If the state unqualified coefficient is not less than the first preset state unqualified coefficient threshold value, it is determined that the corresponding parking space monitoring device needs to be replaced and repaired, and the management platform marks the parking state of the corresponding parking space as a fault state;

[0121] If the status unqualified coefficient is less than the first preset status unqualified coefficient threshold, it is determined that the corresponding parking space monitoring equipment does not need to be replaced and repaired temporarily, and the management platform marks the parking status of the corresponding parking space as temporarily normal.

[0122] It should be noted that the first preset state unqualified coefficient threshold is selected by professionals according to actual conditions and is not limited or elaborated;

[0123] It should be noted that if the status unqualified coefficient of a certain parking space is greater than or equal to the first preset status unqualified coefficient threshold, it means that the monitoring equipment of the parking space may have more serious performance problems or frequent failures, which affect the accurate monitoring of the parking space status; in this case, the management platform will automatically determine that the monitoring equipment of the parking space needs to be replaced or repaired; at the same time, the management platform will mark the parking status of the parking space as "faulty status" to remind the operation and maintenance personnel to handle it in time and avoid vehicle misparking or system misguidance; and re-monitor the parking status of the corresponding parking space by replacing the repaired monitoring equipment and uploading it to the management platform to ensure the accuracy of the parking status information of each parking space received by the management platform;

[0124] On the contrary, if the status unqualified coefficient of a parking space is less than the first preset status unqualified coefficient threshold, it means that the operating status of the monitoring equipment of the parking space is temporarily good and does not need to be replaced or repaired. At this time, the parking space still uses the original monitoring equipment to monitor the parking status of the corresponding parking space and upload it to the management platform. The management platform will determine that the equipment can temporarily work normally and maintain accurate monitoring of the parking space status, but it still needs to be observed and judged again; therefore, the management platform temporarily marks the parking status of the parking space as "normal status" to ensure that the vehicle can be parked according to the correct guidance information, thereby improving the management efficiency of the parking lot.

[0125] In one embodiment, determining the second preset monitoring device monitoring period and the second preset state unqualified coefficient threshold according to the state unqualified coefficient corresponding to the parking space, the first preset monitoring device monitoring period, and the first preset state unqualified coefficient threshold includes:

[0126] ;

[0127] In the formula, , , , , They are respectively the state unqualified coefficient, the first preset monitoring device monitoring period, the first preset state unqualified coefficient threshold, the second preset monitoring device monitoring period and the second preset state unqualified coefficient threshold.

[0128] It should be noted that the first preset monitoring device monitoring period and the first preset state unqualified coefficient threshold are selected by professionals according to actual conditions and are not limited or elaborated.

[0129] In one embodiment, re-determining whether the monitoring device of each parking space needs to be replaced and repaired according to the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold includes:

[0130] When the parking state of the parking space is temporarily normal, after the second preset monitoring device monitoring cycle, the state unqualified coefficient of the monitoring device of each parking space is obtained, and the state unqualified coefficient of the monitoring device of each parking space is compared with the second preset state unqualified coefficient threshold;

[0131] If the status unqualified coefficient is less than the second preset status unqualified coefficient threshold, the monitoring equipment of the corresponding parking space does not need to be replaced and repaired; if the status unqualified coefficient is not less than the second preset status unqualified coefficient threshold, the monitoring equipment of the corresponding parking space needs to be replaced and repaired.

[0132] It should be noted that when the monitoring equipment of a parking space does not need to be replaced or repaired, the original monitoring equipment is still used to monitor the parking status of the corresponding parking space and upload it to the management platform; when the monitoring equipment of a parking space needs to be replaced or repaired, the parking status of the corresponding parking space is re-monitored by replacing the repaired monitoring equipment and uploaded to the management platform to ensure the accuracy of the parking status information of each parking space received by the management platform;

[0133] It should be noted that the monitoring equipment of each parking space is re-judged whether it needs to be replaced and repaired through the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold. This can reduce the risk of missed judgment of the first state judgment of the monitoring equipment. The initial assessment may be affected by instantaneous data fluctuations or accidental failures, resulting in missed judgment of the actual performance state of the equipment. By setting the second preset monitoring equipment monitoring cycle, the equipment can be further observed and data collected, thereby forming a more comprehensive and accurate evaluation basis to ensure the accuracy of the state judgment of the monitoring equipment of each parking space.

[0134] Based on the same inventive concept, the present invention also provides an equipment monitoring system based on an intelligent station. Figure 2 , Figure 2 A framework diagram of an equipment monitoring system based on an intelligent station provided in an embodiment of the present invention, the system comprising:

[0135] Data acquisition module: for several parking spaces in the parking lot, obtain the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring equipment of each parking space when sending parking status information of the parking space to the management platform;

[0136] Cluster analysis module: the data upload abnormal coefficient, signal connection instability coefficient and maintenance coefficient are used as data points of each parking space to obtain a data set, and the data set is clustered to determine the status unqualified coefficient of each parking space monitoring device;

[0137] Classification module: compare the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold, and determine the state of each parking space monitoring device as a fault state and a temporary normal state according to the comparison result;

[0138] Judgment module: When the status of the monitoring device of the parking space is temporarily normal, the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold are determined according to the unqualified coefficient of the status corresponding to the parking space and the first preset monitoring device monitoring cycle and the first preset state unqualified coefficient threshold, and the monitoring equipment of each parking space is re-judged whether it needs to be replaced and repaired according to the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold.

[0139] Based on the equipment monitoring system based on the smart station provided by the embodiment of the present invention, through the above-mentioned method, in actual situations, it is possible to timely detect the status of the monitoring equipment of the parking space, and replace or repair the monitoring equipment in time to ensure accurate parking status monitoring of the parking space, make the management platform work in an orderly manner, and reduce the impact on the operating efficiency of the parking lot.

[0140] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. The equipment monitoring method based on the intelligent station is characterized in that: The following steps are involved: For several parking spaces in the parking lot, obtain the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring device of each parking space when sending parking status information of the parking space to the management platform; The data upload abnormality coefficient, the signal connection instability coefficient and the maintenance coefficient are used as data points of each parking space to obtain a data set, and the data set is clustered to determine the state unqualified coefficient of each parking space monitoring device; Comparing the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold, and determining the state of each parking space monitoring device as a fault state and a temporary normal state according to the comparison result; When the state of the monitoring device of the parking space is temporarily normal, determine the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold according to the state unqualified coefficient corresponding to the parking space, the first preset monitoring device monitoring cycle, and the first preset state unqualified coefficient threshold, and re-judge whether the monitoring device of each parking space needs to be replaced and repaired according to the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold; The data upload abnormality coefficients include: For each parking space in the parking lot, obtain the timestamp of each monitoring device in the parking space sending parking status information to the management platform within a preset time period, calculate the interval between adjacent timestamps, and sequence them based on time to obtain the time interval sequence of the corresponding monitoring device; Compare the time interval in the time interval sequence with the preset time interval, record the data greater than the preset time interval as the delayed time interval, divide the total number of delayed time intervals by the total number of time interval sequences, and obtain the data upload time delay coefficient of the monitoring device corresponding to the monitoring device; Calculate the average of the data upload time delay coefficients of all monitoring devices in the parking space as the delay coefficient of the corresponding parking space; Obtain the total number of times all monitoring devices of each parking space send parking status information to the management platform, and obtain the total number of times the parking status information uploaded by all monitoring devices is inconsistent, and divide the total number of times the parking status information is inconsistent by the total number of times the parking status information is sent to obtain the data inconsistency coefficient of the corresponding parking space; The delay coefficient and data inconsistency coefficient of each parking space are normalized, and the data upload abnormality coefficient of the corresponding parking space is obtained according to the normalized delay coefficient and data inconsistency coefficient. The calculation formula is: , where Upload the anomaly coefficient for the data, and are the normalized delay coefficient and data inconsistency coefficient, and are respectively the preset weight coefficients of the normalized delay coefficient and the data inconsistency coefficient; The signal connection instability coefficient includes: Continuously acquiring the network signal value of the connection between each monitoring device of the parking space and the management platform within a preset time period at multiple times to obtain a network signal value sequence; Calculate the standard deviation of the network signal value, and use the standard deviation of the network signal value as the network signal fluctuation value; Compare each signal value in the network signal value sequence with a preset minimum signal value, and record a value less than the preset minimum signal value as the minimum signal value; Divide the total number of low signal values ​​in the network signal value sequence by the number of all values ​​in the network signal value sequence to obtain a signal failure value; The network signal fluctuation values ​​and signal unqualified values ​​of all monitoring devices are normalized, and the signal connection instability coefficient of the corresponding parking space is obtained according to the normalized network signal fluctuation values ​​and signal unqualified values. The calculation formula is: , where is the signal connection instability coefficient, and are the normalized network signal fluctuation value and signal unqualified value, Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. and are the preset proportional coefficients corresponding to the normalized network signal fluctuation value and the signal unqualified value, respectively, and and All are greater than 0; The maintenance factors include: For each parking space in the parking lot, obtain the time interval from the last maintenance of each monitoring device in the parking space within a preset time period as the actual maintenance time interval; Obtain the average maintenance time interval of each monitoring device, and calculate the difference between the average maintenance time interval and the actual maintenance time interval as the maintenance interval coefficient; The total number of failures and the average cost of each failure of each monitoring device in the parking space within the preset time period are obtained, and the total number of failures, the average time for each failure repair, and the maintenance interval coefficient are normalized. According to the normalized total number of failures, the average time for each repair, and the maintenance interval coefficient, the maintenance coefficient of the corresponding parking space is obtained. The calculation formula is: , where is the maintenance factor, , and are the normalized total number of failures, the average time spent on each maintenance, and the maintenance interval coefficient, respectively. Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. , , are the normalized total number of failures, the average time spent on each maintenance, and the preset proportional coefficients corresponding to the maintenance interval coefficient, respectively. , , Both are greater than 0.

2. The device monitoring method based on the intelligent station according to claim 1 is characterized in that: Clustering the data set to determine the state unqualified coefficient of each parking space monitoring device includes: The steps to cluster the data set using the K-means clustering method are: Step 1: Used to determine the optimal number of clusters for the data set using the elbow method; Step 2: Randomly select a corresponding number of data points as initial clusters according to the optimal number of clusters; Step 3: For each data point, use the Euclidean distance algorithm to calculate the distance between the data point and each initial cluster center, and assign the data point to the cluster to which the nearest cluster center belongs. After traversing all data points, the initial cluster center is obtained. Step 4: Calculate the average value of all data points for each initial cluster and use the average value as the new cluster center; Step 5: It is used to determine whether the cluster center has changed. If it has changed, repeat steps 3 and 4 until the cluster center no longer changes, and obtain the final cluster and the final cluster center; The final clusters and the final cluster centers are mapped to three-dimensional coordinates to obtain the status unqualified coefficient of each parking space monitoring device.

3. The device monitoring method based on the intelligent station according to claim 2 is characterized in that: The final clusters and the final cluster centers are mapped to three-dimensional coordinates, and the unqualified coefficients of the status of each parking space monitoring device are obtained, including: Calculate the weight coefficient of each final cluster, the calculation formula is: ,in Expressed as The weight coefficients of the final clusters, Represented as the number of all data points in the dataset, Indicates The number of data points in the final clusters; Calculate the distance of each data point in each final cluster to the coordinate origin in three-dimensional coordinates to obtain the preliminary coordinate distance of the data point, and multiply the preliminary coordinate distance of the data point by the weight coefficient corresponding to the final cluster in which the data point is located to obtain the actual coordinate distance of the data point; The actual coordinate distance of each data point is used as the status failure coefficient of the corresponding parking space monitoring device.

4. The device monitoring method based on the intelligent station according to claim 1 is characterized in that: Determine whether each parking space monitoring device needs to be replaced or repaired based on the comparison results, including: Compare the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold value. If the state unqualified coefficient is not less than the first preset state unqualified coefficient threshold value, it is determined that the corresponding parking space monitoring device needs to be replaced and repaired, and the management platform marks the parking state of the corresponding parking space as a fault state; If the status unqualified coefficient is less than the first preset status unqualified coefficient threshold, it is determined that the corresponding parking space monitoring equipment does not need to be replaced and repaired temporarily, and the management platform marks the parking status of the corresponding parking space as temporarily normal.

5. The device monitoring method based on the intelligent station according to claim 1 is characterized in that: Determining the second preset monitoring device monitoring period and the second preset state unqualified coefficient threshold according to the state unqualified coefficient corresponding to the parking space, the first preset monitoring device monitoring period, and the first preset state unqualified coefficient threshold includes: ； ； In the formula, , , , , They are respectively the state unqualified coefficient, the first preset monitoring device monitoring period, the first preset state unqualified coefficient threshold, the second preset monitoring device monitoring period and the second preset state unqualified coefficient threshold.

6. The device monitoring method based on the intelligent station according to claim 1 is characterized in that: Re-determining whether the monitoring equipment of each parking space needs to be replaced and repaired according to the second preset monitoring equipment monitoring cycle and the second preset state unqualified coefficient threshold includes: When the parking state of the parking space is temporarily normal, after the second preset monitoring device monitoring cycle, the state unqualified coefficient of the monitoring device of each parking space is obtained, and the state unqualified coefficient of the monitoring device of each parking space is compared with the second preset state unqualified coefficient threshold; If the status unqualified coefficient is less than the second preset status unqualified coefficient threshold, the monitoring equipment of the corresponding parking space does not need to be replaced and repaired; if the status unqualified coefficient is not less than the second preset status unqualified coefficient threshold, the monitoring equipment of the corresponding parking space needs to be replaced and repaired.

7. An equipment monitoring system based on a smart station, used to implement the equipment monitoring method based on a smart station as described in any one of claims 1 to 6, characterized in that: The system comprises: Data acquisition module: for several parking spaces in the parking lot, obtain the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient of the monitoring equipment of each parking space when sending parking status information of the parking space to the management platform; Cluster analysis module: taking the data upload abnormality coefficient, signal connection instability coefficient and maintenance coefficient as the data points of each parking space, obtaining a data set, clustering the data set to determine the state unqualified coefficient of each parking space monitoring device; Classification module: compare the state unqualified coefficient of each parking space with the first preset state unqualified coefficient threshold, and determine the state of each parking space monitoring device as a fault state and a temporary normal state according to the comparison result; Judgment module: when the state of the monitoring device of the parking space is temporarily normal, determine the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold according to the state unqualified coefficient corresponding to the parking space and the first preset monitoring device monitoring cycle and the first preset state unqualified coefficient threshold, and re-judge whether the monitoring device of each parking space needs to be replaced and repaired according to the second preset monitoring device monitoring cycle and the second preset state unqualified coefficient threshold; The data upload abnormality coefficients include: For each parking space in the parking lot, obtain the timestamp of each monitoring device in the parking space sending parking status information to the management platform within a preset time period, calculate the interval between adjacent timestamps, and sequence them based on time to obtain the time interval sequence of the corresponding monitoring device; Compare the time interval in the time interval sequence with the preset time interval, record the data greater than the preset time interval as the delayed time interval, divide the total number of delayed time intervals by the total number of time interval sequences, and obtain the data upload time delay coefficient of the monitoring device corresponding to the monitoring device; Calculate the average of the data upload time delay coefficients of all monitoring devices in the parking space as the delay coefficient of the corresponding parking space; Obtain the total number of times all monitoring devices of each parking space send parking status information to the management platform, and obtain the total number of times the parking status information uploaded by all monitoring devices is inconsistent, and divide the total number of times the parking status information is inconsistent by the total number of times the parking status information is sent to obtain the data inconsistency coefficient of the corresponding parking space; The delay coefficient and data inconsistency coefficient of each parking space are normalized, and the data upload abnormality coefficient of the corresponding parking space is obtained according to the normalized delay coefficient and data inconsistency coefficient. The calculation formula is: , where Upload the anomaly coefficient for the data, and are the normalized delay coefficient and data inconsistency coefficient, and are respectively the preset weight coefficients of the normalized delay coefficient and the data inconsistency coefficient; The signal connection instability coefficient includes: Continuously acquiring the network signal value of the connection between each monitoring device of the parking space and the management platform within a preset time period at multiple times to obtain a network signal value sequence; Calculate the standard deviation of the network signal value, and use the standard deviation of the network signal value as the network signal fluctuation value; Compare each signal value in the network signal value sequence with a preset minimum signal value, and record a value less than the preset minimum signal value as the minimum signal value; Divide the total number of low signal values ​​in the network signal value sequence by the number of all values ​​in the network signal value sequence to obtain a signal failure value; The network signal fluctuation values ​​and signal unqualified values ​​of all monitoring devices are normalized, and the signal connection instability coefficient of the corresponding parking space is obtained according to the normalized network signal fluctuation values ​​and signal unqualified values. The calculation formula is: , where is the signal connection instability coefficient, and are the normalized network signal fluctuation value and signal unqualified value, Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. and are the preset proportional coefficients corresponding to the normalized network signal fluctuation value and the signal unqualified value, respectively, and and All are greater than 0; The maintenance factors include: For each parking space in the parking lot, obtain the time interval from the last maintenance of each monitoring device in the parking space within a preset time period as the actual maintenance time interval; Obtain the average maintenance time interval of each monitoring device, and calculate the difference between the average maintenance time interval and the actual maintenance time interval as the maintenance interval coefficient; The total number of failures and the average cost of each failure of each monitoring device in the parking space within the preset time period are obtained, and the total number of failures, the average time for each failure repair, and the maintenance interval coefficient are normalized. According to the normalized total number of failures, the average time for each repair, and the maintenance interval coefficient, the maintenance coefficient of the corresponding parking space is obtained. The calculation formula is: , where is the maintenance factor, , and are the normalized total number of failures, the average time spent on each maintenance, and the maintenance interval coefficient, respectively. Indicates the sequence number of the parking space monitoring device. Indicates the total number of parking space monitoring devices. , , are the normalized total number of failures, the average time spent on each maintenance, and the preset proportional coefficients corresponding to the maintenance interval coefficient, respectively. , , Both are greater than 0.

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