Service full-link monitoring method, equipment and medium

Abstract

The invention provides a service full-link monitoring method and device and a medium, and relates to the technical field of data processing, and the method comprises the steps: extracting a first service attribute corresponding to a corresponding service after judging that a demand end sends a service monitoring demand; traversing a corresponding first link in a database based on the first service attribute, and carrying out classified statistics on all link nodes in the first link to obtain a first active node and a first passive node; extracting a service monitoring scene corresponding to the service, and screening the first active node and the first passive node based on the scene attribute of the service monitoring scene to obtain a second active node and a second passive node; and the second active node and the second passive node are combined according to the sequence to obtain a total link for monitoring, and service full-link monitoring can be realized according to an actual service scene.

Description

Technical Field

[0001] The present invention relates to data processing technologies, and in particular, to a method, device, and medium for monitoring the entire business link. Background Art

[0002] In power grid marketing operations, complex operations such as equipment transportation and fault repair often involve multi-link coordination. For example, a transformer replacement operation needs to go through link nodes such as "warehouse pickup, long-distance transportation, temporary storage at a transfer station, and on-site installation". The execution efficiency and data accuracy of each node directly affect the reliability of the operation.

[0003] Traditional monitoring methods rely on static link templates, such as node monitoring in a fixed transportation route, and cannot dynamically adapt to path changes in actual business scenarios, such as route adjustments due to sudden traffic control, changes in equipment status, or differences in personnel operations such as delays in on-site code scanning confirmation. This leads to lagging monitoring data, incomplete node coverage, making it difficult to detect abnormal breakpoints in the link in real time and unable to achieve full-link monitoring of the operation, thus affecting the operation execution result.

[0004] Therefore, how to achieve full-link monitoring of operations according to actual business scenarios has become an urgent problem to be solved. Summary of the Invention

[0005] The present invention provides a method, device, and medium for monitoring the entire business link, which can achieve full-link monitoring of operations according to actual business scenarios.

[0006] In a first aspect of the present invention, a method for monitoring the entire business link is provided, including: After determining that the demand side sends a business monitoring requirement, extract the first business attribute corresponding to the corresponding business; Based on the first business attribute, traverse the corresponding first link in the database, and classify and count all link nodes in the first link to obtain the first active nodes and the first passive nodes; Extract the business monitoring scenario corresponding to the business, and filter the first active nodes and the first passive nodes based on the scenario attributes of the business monitoring scenario to obtain the second active nodes and the second passive nodes; Combine the second active nodes and the second passive nodes in sequence to obtain the total link for monitoring.

[0007] Optionally, in a possible implementation manner of the first aspect, the extracting the first business attribute corresponding to the corresponding business after determining that the demand side sends a business monitoring requirement includes: After determining that the demand side sends a business monitoring requirement to the server, extract the target business within the business monitoring requirement; Determine the first business attribute corresponding to the target business. Each business has a preset business attribute, and the business attribute has no relevance to the entity's business monitoring scenario.

[0008] Optionally, in a possible implementation of the first aspect, traversing the corresponding first link in the database based on the first service attribute, and classifying and counting all link nodes in the first link to obtain a first active node and a first passive node, includes: Traversing all links corresponding to the first service attribute in the database to obtain a first link; Sequentially traversing each link node in the first link, and dividing the link nodes into a first active node and a first passive node according to the first device and the first method extracted from the information in the link node; Counting the union of the path point label, the personnel label, and the device label corresponding to each node in the first link to obtain a first label set.

[0009] Optionally, in a possible implementation of the first aspect, dividing the link nodes into a first active node and a first passive node according to the first device and the first method extracted from the information in the link node, includes: If it is determined that the first device in the link node does not have an input module, and the corresponding first method is to automatically extract by executing a program, then the corresponding link node is used as the first active node; If it is determined that the first device in the link node has an input module, and the corresponding first method is to extract after corresponding triggering, then the corresponding link node is used as the first passive node.

[0010] Optionally, in a possible implementation of the first aspect, extracting the service monitoring scenario corresponding to the service, and screening the first active node and the first passive node based on the scenario attribute of the service monitoring scenario to obtain a second active node and a second passive node, includes: Determining the entity path point, entity personnel, and entity device in the service monitoring scenario, and generating the corresponding path point label, personnel label, and device label; Comparing the path point label, the personnel label, and the device label with the first active node and the first passive node, determining the remaining second active node and second passive node, and generating a node statistical table after classifying the nodes.

[0011] Optionally, in a possible implementation of the first aspect, determining the remaining second active node and second passive node, and generating a node statistical table after classifying the nodes, includes: Retaining the first active node and the first passive node corresponding to the path point label, the personnel label, and the device label as the second active node and the second passive node; Regarding the deleted first active node and first passive node as the third active node and the third passive node; After the secondary verification of the second active node and the second passive node, count all the nodes and fill them into the corresponding areas in the statistical table.

[0012] Optionally, in a possible implementation manner of the first aspect, after the secondary verification of the second active node and the second passive node, counting all the nodes and filling them into the corresponding areas in the statistical table includes: Count the entity path points, entity personnel, and entity devices corresponding to the second active node and the second passive node in the service monitoring scenario to obtain a second label set; Compare the first label set with the second label set to determine the labels that exist in the first label set but do not exist in the second label set to obtain a set of different labels; Count all the nodes and the set of different labels and fill them into the statistical table.

[0013] Optionally, in a possible implementation manner of the first aspect, combining the second active node and the second passive node in sequence to obtain a total link for monitoring includes: Determine the timing sequence of the entity path points, entity personnel, and entity devices in the service monitoring scenario; Extract the earliest timing sequence of the labels corresponding to the second active node and the second passive node as the combined timing sequence; Based on the combined timing sequence, combine all the second active nodes and the second passive nodes to obtain a total link for monitoring.

[0014] Optionally, in a possible implementation manner of the first aspect, combining all the second active nodes and the second passive nodes based on the combined timing sequence to obtain a total link for monitoring includes: If it is determined that the difference value of the timing sequence of any second active node and / or second passive node is less than or equal to a preset value, then the second active node and / or second passive node are used as a parallel group; After the parallel groups are set in parallel, connect them to the second active nodes and / or second passive nodes before and after respectively to obtain a total link in a mixed connection state.

[0015] Optionally, in a possible implementation manner of the first aspect, generating a node statistical table after classifying the nodes includes: Determine the number of the third active nodes and the third passive nodes in the statistical table to obtain the number of missing nodes; Determine the number of path point labels, personnel labels, and device labels in each of the third active nodes and the third passive nodes in the statistical table to obtain the number of missing first labels; Determine the number of the set of different labels in the statistical table to obtain the number of missing second labels; The coefficient of the total link to be filled is calculated based on the number of missing nodes, the number of missing first labels, and the number of missing second labels and is filled into the node statistics table.

[0016] Optionally, in a possible implementation of the first aspect, obtaining the to-be-filled coefficient of the total link based on the comprehensive calculation of the number of missing nodes, the number of missing first labels, and the number of missing second labels includes: The number of missing nodes, the number of missing first labels, and the number of missing second labels are compared with a preset constant value and then added to obtain the coefficient to be filled.

[0017] A second aspect of the present invention provides a full-link service monitoring device, comprising: A judgment module, configured to extract a first business attribute corresponding to a corresponding business after judging that a demand side sends a business monitoring demand; A traversal module, configured to traverse the corresponding first link in the database based on the first service attribute, and classify and count all link nodes in the first link to obtain a first active node and a first passive node; An extraction module is used to extract a business monitoring scenario corresponding to the business, and screen the first active node and the first passive node based on the scenario attributes of the business monitoring scenario to obtain a second active node and a second passive node; The combining module is used to combine the second active node and the second passive node in sequence to obtain a total link for monitoring.

[0018] According to a third aspect of the present invention, a storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the method of the first aspect of the present invention and various possible designs of the first aspect.

[0019] The beneficial effects of the present invention are as follows: 1. The present invention can realize full-link monitoring of business according to actual business scenarios. First of all, the present invention can realize dynamic generation of monitoring links and improve adaptability through link traversal and scene label screening driven by business attributes. Among them, the database is traversed according to the business attributes of the demand side, and the historical link template is extracted. The scene label is generated based on the entity elements of the current business monitoring scene. By comparing the label set of the historical link node with the scene label, irrelevant nodes are eliminated and matching nodes are retained. Finally, a total link that fits the actual business is generated. The irrelevant nodes in the historical link can be automatically filtered, and only the active nodes and passive nodes related to the business are retained, so that the monitoring range accurately covers the current business path, improves the efficiency of link construction, and avoids monitoring redundancy or omissions caused by traditional static templates.

[0020] 2. The present invention can classify nodes to improve monitoring accuracy. Specifically, the present invention can classify link nodes into active nodes and passive nodes based on device characteristics and data collection methods, achieving differentiated management of monitoring strategies. At the same time, by counting indicators such as the number of missing nodes and the number of missing labels, a coefficient to be filled is generated to quantify link integrity, avoiding abnormal missed detections due to incomplete data collection, thereby improving the accuracy of full-link monitoring.

[0021] 3. The present invention can realize dynamic sorting and parallel processing of node combinations according to the timing logic of the business scenario, ensuring that the monitoring link conforms to the actual execution order. Specifically, the present invention can obtain the combined timing by extracting the earliest timing of the node label, sequentially connect each node according to the combined timing, and calculate the timing difference value corresponding to each node. When the timing difference value is less than the preset value, it is set as a parallel group to indicate synchronous execution for monitoring. At the same time, it is easy to solve the problem of fault location lag caused by timing confusion. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flowchart of a full-link business monitoring method provided by the present invention; Figure 2 A schematic diagram of a parallel group link connection provided by the present invention; Figure 3 This is a structural diagram of a full-link business monitoring device provided by the present invention. DETAILED DESCRIPTION

[0023] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0024] like Figure 1 The present invention provides a flow chart of a method for monitoring a full service link, the method comprising: S1, extracting a first service attribute corresponding to a corresponding service after determining that a service monitoring demand is sent by a demand side.

[0025] It should be noted that the marketing business in the power grid has corresponding starting and ending locations. Therefore, the corresponding business link can be determined according to business needs so that the business link can be fully monitored subsequently. For example, when a transformer in a certain place has an abnormality, it may need to be replaced or repaired. Therefore, it is necessary to select a transformer of the corresponding model and transport it to the location. Among them, due to the different transmission locations and temporary storage points during transportation of different businesses, the attributes of the corresponding nodes are inevitably inconsistent. Therefore, the nodes can be adjusted according to the actual link to improve the accuracy of link detection.

[0026] It can be understood that the demand side is the information terminal of the management personnel for business execution, the business monitoring requirement is the requirement information for comprehensively monitoring the business process, and the first business attribute is the type corresponding to the business, such as a maintenance work order or a replacement work order, etc. That is, when the corresponding business is maintenance, the corresponding first business attribute, the maintenance work order, can be extracted; when the corresponding business is replacement, the corresponding first business attribute is the replacement work order, so as to perform link monitoring according to the first business attribute subsequently.

[0027] In some embodiments, the specific implementation manner in step S1 (extracting the first business attribute corresponding to the corresponding business after determining that the demand side sends a business monitoring requirement) includes: S11, after determining that the demand side sends a business monitoring requirement to the server, extracting the target business within the business monitoring requirement.

[0028] It can be understood that when it is determined that the server receives the business monitoring requirement from the demand side, the information of the target business pair included in the business monitoring requirement can be extracted. For example, when a transformer needs to be transported, business information such as the corresponding transportation location, the specification model and quantity of the transported transformer can be extracted.

[0029] It is not difficult to understand that through the extracted target business, it is convenient to initially judge the business complexity. For example, cross-province transportation requires multi-node and full-link monitoring.

[0030] S12, determining the first business attribute corresponding to the target business. Each business has a preset business attribute, and the business attribute has no relevance to the entity's business monitoring scenario.

[0031] It can be understood that the corresponding first business attribute can be determined according to the extracted target business. Since the business attribute is set according to the historical data of the same business, for example, when transporting item 1 from place A to place B, intermediate relevant temporary storage node information, transportation method and other information are involved. Therefore, the preset business attribute may have a certain difference from the current business monitoring scenario, that is, it has no relevance to the entity's business monitoring scenario. Subsequently, corresponding adjustments may be required, but it can provide an initial monitoring method and direction to determine the monitoring link and achieve full-link monitoring of the business subsequently.

[0032] S2, traversing the corresponding first link in the database based on the first business attribute, and classifying and counting all link nodes in the first link to obtain the first active node and the first passive node.

[0033] It should be noted that the first link is obtained by traversing the database according to the first business attribute. For example, when the current business is to repair transformers, the links of historical transformer repair in the database can be traversed to determine the node attributes of the link corresponding to the current business, so as to facilitate subsequent link monitoring. In addition, since some business links require people to passively obtain business information, some related equipment directly sends it to the server actively. For example, in the process of transporting equipment, there is a positioning device on the transport vehicle, and the positioning device can actively send the corresponding positioning information in real time. Then, the corresponding business nodes can be divided by attributes for subsequent classification monitoring.

[0034] It can be understood that by retrieving historical link templates through business attributes, link nodes are classified as active / passive based on device characteristics and data collection methods, so as to facilitate subsequent scenario screening and analysis and improve the accuracy of link monitoring.

[0035] Among them, the first link is the business link corresponding to the first business attribute, the link node is the structural connection node in the first link, the first active node is the node that actively sends information to the server, and the first passive node is the link node that passively obtains and sends.

[0036] In some embodiments, a specific implementation of step S2 (traversing the corresponding first link in the database based on the first service attribute and classifying and counting all link nodes in the first link to obtain the first active node and the first passive node) includes: S21: Traverse all links corresponding to the first service attribute in the database to obtain a first link.

[0037] It is understandable that all links corresponding to different business attributes are pre-stored in the database. For example, for the transformer replacement business, the database stores links for transporting the transformer to various locations, and there can be multiple modes of transportation, such as air transportation, land transportation, and sea transportation, so that the first link can be traversed.

[0038] Through the above implementation, the present invention can avoid repeated link planning, so that the verified service path can be used to improve monitoring efficiency.

[0039] S22 , traverse each link node in the first link in sequence, and divide the link nodes into first active nodes and first passive nodes according to the first device and the first method for extracting information from the link nodes.

[0040] It can be understood that the first device is the device corresponding to the first service attribute, including vehicles such as cars and ships for transportation, GPS of positioning devices, etc., and the first method is the execution method corresponding to the service information, such as the method of the device actively transmitting information or the method of manually actively scanning to obtain information.

[0041] Through the above implementation manners, the present invention can distinguish corresponding link nodes, so as to perform targeted monitoring according to node attributes subsequently, and improve the accuracy of link monitoring.

[0042] In some embodiments, the specific implementation manner in step S22 (dividing the link nodes into first active nodes and first passive nodes according to the first device and the first method extracted from the information in the link nodes) includes: S221, if it is determined that the first device in the link node does not have an input module, and the corresponding first method is automatic extraction by an execution program, then the corresponding link node is taken as the first active node.

[0043] It can be understood that when the devices of the link node (such as in-vehicle GPS, environmental sensors) do not have a manual input interface (such as a keyboard, touch screen), and the data is automatically collected regularly through a preset program (such as uploading location coordinates every 5 minutes), it indicates that the node can continuously generate data without manual intervention, and then the corresponding link node can be taken as the first active node.

[0044] Among them, the input module is a module for information interaction between the device and people.

[0045] S222, if it is determined that the first device in the link node has an input module, and the corresponding first method is extraction after corresponding triggering, then the corresponding link node is taken as the first passive node.

[0046] It can be understood that when the device has an input module and the data collection depends on manual operation triggering (such as scanning to confirm arrival of goods, manually entering quality inspection results), then the node belongs to the passive node.

[0047] S23, count the union of the path point labels, personnel labels, and device labels corresponding to each node in the first link to obtain the first label set.

[0048] It can be understood that the path point label is the corresponding label of the positioning point of the device in the corresponding service, that is, the address label, the personnel label is the label information of the types of personnel involved in the business process, such as labels of maintenance personnel, installation personnel, etc., the device label is the corresponding label of the detection device that may be encountered in the business, such as the detection device label, including detectors, etc., and the first label set is a set of multiple labels corresponding to the node.

[0049] S3. Extract the business monitoring scenarios corresponding to the services, and filter the first active node and the first passive node based on the scenario attributes of the business monitoring scenarios to obtain a second active node and a second passive node.

[0050] It can be understood that different services have corresponding business monitoring scenarios. For example, some services include multiple complex processes such as warehousing, verification, and outbound, while some services only involve transportation. Therefore, the corresponding monitoring scenarios are also different. Furthermore, the first active node and the first passive node can be filtered based on the scenario attributes corresponding to the business monitoring scenarios to obtain link nodes that conform to the current business monitoring scenario.

[0051] Among them, the scenario attribute is the attribute information that conforms to the business monitoring scenario. The second active node is the node obtained by filtering the first active node to meet the business monitoring scenario, and the second passive node is the node obtained by filtering the first passive node to meet the current business monitoring scenario.

[0052] In some embodiments, the specific implementation manner in step S3 (extracting the business monitoring scenarios corresponding to the services, filtering the first active node and the first passive node based on the scenario attributes of the business monitoring scenarios to obtain a second active node and a second passive node) includes: S31. Determine the entity path points, entity personnel, and entity devices in the business monitoring scenario, and generate corresponding path point labels, personnel labels, and device labels.

[0053] It can be understood that the entity path point is the path point in the actual business monitoring scenario, the entity personnel are the business personnel in the actual business monitoring scenario, such as truck drivers, installers, etc., and the entity devices are the devices required in the actual business monitoring scenario, such as transport trucks, etc.

[0054] It is not difficult to understand that by extracting the labels of these entities, such as "Location A", "Truck Driver", "Truck", etc., the link nodes related to the current scenario can be accurately located, and the inapplicable elements in the historical link can be excluded, such as the sea freight node is invalid for the land transportation scenario, so as to generate a targeted monitoring link subsequently.

[0055] S32. Compare the path point labels, personnel labels, and device labels with the first active node and the first passive node, determine the retained second active node and second passive node, and generate a node statistical table after classifying the nodes.

[0056] It can be understood that by comparing the labels to filter the historical link nodes, retaining the nodes related to the scenario and generating a statistical report, so as to allocate monitoring resources subsequently and optimize the link monitoring plan, that is, the nodes that match the labels can be retained as the second active node or the second passive node, and the unmatched nodes can be deleted.

[0057] The node statistics table is a table that performs comprehensive statistics on the determined nodes.

[0058] It should be noted that the first active node and the first passive node are designed with corresponding equipment and information acquisition methods. Therefore, the waypoint label, personnel label and equipment label can be compared with the corresponding node to complete the screening. For example, when the address in the waypoint label is connected to the land, there is no need to use sea transportation, and the nodes related to sea transportation can be deleted.

[0059] It is not difficult to understand that the statistical table clearly presents the monitoring range and node distribution, eliminates interference from irrelevant nodes, and improves link monitoring efficiency.

[0060] In some embodiments, a specific implementation of step S32 (determining the retained second active nodes and second passive nodes, and generating a node statistics table after classifying the nodes) includes: S321 , retaining the first active node and the first passive node corresponding to the waypoint tag, the personnel tag, and the device tag as the second active node and the second passive node.

[0061] It can be understood that historical link nodes are filtered based on scene labels, and monitoring nodes that are strongly related to the current business are retained. Path point labels, personnel labels, and equipment labels directly define the scope and objects of current business monitoring. Through label matching, only nodes whose locations belong to the current business path points, whose node operation roles are within the scope of business personnel, and whose equipment meets the current business needs are retained.

[0062] Through the above implementation, the present invention can eliminate redundant nodes in the historical link, concentrate monitoring resources on the current business key links, ensure that all retained nodes match the actual business process, and avoid disconnection between monitoring logic and execution.

[0063] S322: Use the deleted first active node and first passive node as the third active node and third passive node.

[0064] It can be understood that the third active node is the deleted first active node that is irrelevant to the current business monitoring scenario, and the third passive node is the deleted first passive node that is irrelevant to the current business monitoring scenario.

[0065] It should be noted that the first active node and the first passive node to be deleted can be information nodes that are not required in the current business monitoring scenario, or information nodes that do not meet the standards in the current business monitoring scenario. For example, for some businesses, temperature and humidity detection devices are required in transport vehicles or storage spaces, but the corresponding test devices are not configured in the actual devices, then this node can be deleted. Or, some warehouses have camera devices while some do not, so the corresponding image information cannot be extracted, and thus the corresponding scenario nodes will also be deleted.

[0066] S323. After the secondary verification of the second active node and the second passive node, count all the nodes and fill them into the corresponding areas in the statistical table.

[0067] It can be understood that by secondary verification, the validity of the remaining nodes is ensured, and then the node information is visualized in the form of a statistical table to improve the reliability of the monitoring plan, that is, all relevant nodes are counted in the statistical table.

[0068] In some embodiments, the specific implementation manner in step S323 (after the secondary verification of the second active node and the second passive node, count all the nodes and fill them into the corresponding areas in the statistical table) includes: S3231. Count the entity path points, entity personnel, and entity equipment corresponding to the business monitoring scenarios of the second active node and the second passive node to obtain the second label set.

[0069] It can be understood that the information actually involved in this business is counted to obtain the second label set for subsequent information comparison with the first label set.

[0070] Among them, the second label set is an information label set corresponding to the entity path points, entity personnel, and entity equipment actually involved in the business.

[0071] S3232. Compare the first label set and the second label set, and determine the labels that exist in the first label set but do not exist in the second label set to obtain the difference label set.

[0072] It can be understood that when the information required in the standard business requirements is not available in the actual business link, that is, relevant business conditions are missing in reality. For example, when transporting equipment needs to be monitored during business execution, that is, a real-time camera device is required in the transport vehicle, but there is no label corresponding to the camera device in the transport vehicle in the second label set, indicating that the corresponding camera device is missing in the actual business execution. Furthermore, the information that is required in the business requirements but missing in the actual execution can be counted to obtain the difference label set, such as a set including in-vehicle camera devices and temperature and humidity test devices, for subsequent statistics to prompt the equipment to be supplemented to achieve full-link monitoring.

[0073] It is not difficult to understand that the set of difference tags is the set of conditional tags missing in the second tag set relative to the first tag set.

[0074] S3233. Statistically count all nodes and the set of difference tags and fill them into the statistical table.

[0075] It can be understood that integrating node information and tag differences into the statistical table forms a comprehensive report including the current situation and potential problems. Through integration, personnel can intuitively understand the integrity and optimization direction of the monitoring link.

[0076] In some embodiments, the specific implementation manner in step S32 (generating a node statistical table after classifying the nodes) includes: S324. Determine the number of the third active nodes and the third passive nodes in the statistical table to obtain the node missing quantity.

[0077] It can be understood that the node missing quantity is the number of the third active nodes and the third passive nodes in the statistical table, representing the number of missing conditions in the actual business. For example, when the on-vehicle camera device and the temperature and humidity detection device are missing in this transport vehicle, the corresponding node quantities can be accumulated and statistically counted, so as to calculate the corresponding coefficient to be supplemented subsequently, facilitating the supplementary prompt for the business and improving the monitoring efficiency.

[0078] S325. Determine the number of path point tags, personnel tags, and device tags in each of the third active nodes and the third passive nodes in the statistical table to obtain the first tag missing quantity.

[0079] It can be understood that each third node contains specific tags. Statistically count the number of these tags. For example, if one personnel tag is missing, the specific missing business elements can be located. Traverse the tag fields of the third nodes and group and count according to the tag type (path point / personnel / device).

[0080] Among them, the first tag missing quantity is the number of missing information corresponding to each node.

[0081] S326. Determine the number of the set of difference tags in the statistical table to obtain the second tag missing quantity.

[0082] It can be understood that the second tag missing quantity is the number of the set of difference tags, reflecting the mismatch degree between historical experience and the current scenario.

[0083] S327. Based on the node missing quantity, the first tag missing quantity, and the second tag missing quantity, comprehensively calculate the coefficient to be supplemented for the total link and fill it into the node statistical table.

[0084] It can be understood that by weighted calculation, three types of missing indicators are integrated to generate the coefficient to be supplemented for the total link, so as to optimize the link subsequently.

[0085] Among them, the coefficient to be supplemented is the coefficient value reflecting the link missing condition.

[0086] In some embodiments, the specific implementation manner in step S327 (the coefficient to be supplemented for the total link obtained by comprehensively calculating based on the number of missing nodes, the number of missing first tags, and the number of missing second tags) includes: S3271, divide the number of missing nodes, the number of missing first tags, and the number of missing second tags by a preset constant value respectively and then add them up to obtain the coefficient to be supplemented.

[0087] It can be understood that the coefficient to be supplemented is the value obtained by calculating the ratios of the number of missing nodes, the number of missing first tags, and the number of missing second tags to a preset constant value respectively and then adding them up.

[0088] For example, when the preset constant value is 1, where the number of missing nodes is 2, the number of missing first tags is 3, and the number of missing second tags is 1, then the coefficient to be supplemented can be obtained as 6.

[0089] S4, combine the second active node and the second passive node in sequence to obtain the total link for monitoring.

[0090] It can be understood that during the business execution process, each step has a corresponding sequence of time before and after. Therefore, according to the timing constraints of the business scenario, the screened active and passive nodes can be connected in series in the correct order to construct a monitoring link that conforms to the business execution logic, ensuring full-process visibility.

[0091] In some embodiments, the specific implementation manner in step S4 (the combination of the second active node and the second passive node in sequence to obtain the total link for monitoring) includes: S41, determine the timing sequence of the entity path points, entity personnel, and entity devices in the business monitoring scenario.

[0092] It can be understood that according to the business execution process, the timing sequence of the entity path points, entity personnel, and entity devices in the business monitoring scenario is determined. For example, the starting point - transfer point - destination point has a certain sequence of time before and after, and the personnel and devices involved therein all have corresponding times, thereby obtaining the timing sequence, which is convenient for subsequent combination and arrangement of the corresponding nodes to obtain the total link for corresponding monitoring.

[0093] Among them, the timing sequence is the sequence arranged based on time.

[0094] S42, extract the earliest timing sequence of the tags corresponding to the second active node and the second passive node as the combination timing sequence.

[0095] It is understandable that each node tag has a first effective time in the business process. For example, the GPS positioning data of the active node first takes effect when loading is completed, and the code scanning confirmation of the passive node is triggered before departure. Extracting the earliest time sequence of these tags can ensure that the monitoring link is started in the order in which the business actually occurs.

[0096] The combined time sequence is the earliest time sequence of the tags corresponding to the second active node and the second passive node.

[0097] Through the above implementation, the earliest appearance time of the node label is used as a benchmark to determine the combination timing, thereby preventing the monitoring link from lagging behind the service execution.

[0098] S43: Combine all the second active nodes and the second passive nodes based on the combined timing to obtain a total link for monitoring.

[0099] It can be understood that the active / passive nodes are connected into a complete link based on the combined timing to achieve full-process monitoring of the business.

[0100] In some embodiments, a specific implementation of step S43 (combining all second active nodes and second passive nodes based on the combined timing to obtain a total link for monitoring) includes: S431: If it is determined that the timing phase difference value of any second active node and / or second passive node is less than or equal to a preset value, the second active node and / or the second passive node are grouped as a parallel group.

[0101] It should be noted that in a business process, although some nodes belong to different entity elements (such as personnel and equipment), they can operate in parallel within the same time period.

[0102] For example: When a transport truck arrives at the transfer station (active node timing T1), the warehouse manager simultaneously scans the code for confirmation (passive node timing T2). If |T1-T2| ≤ the preset value (such as 10 minutes), the two can be regarded as parallel operations. By setting the timing difference threshold (such as ≤15 minutes), the active or passive nodes that meet the conditions are divided into parallel groups (such as {truck positioning node, warehouse manager scanning node}) to avoid monitoring delays caused by sequential execution.

[0103] The timing phase difference value is the interval difference between the times corresponding to different nodes, the preset value is a pre-set time interval, such as 15 minutes, and the parallel group is a parallel combination of nodes that meet the time interval.

[0104] S432: After the parallel groups are set in parallel, they are respectively connected to the second active nodes and / or second passive nodes before and after them to obtain a total link in a mixed connection state.

[0105] It is understandable that when a parallel group appears, e.g.Figure 2 As shown, the parallel groups can be connected in series with the front and rear nodes to form a "hybrid connection" link, fully restoring the timing logic and parallel characteristics of the service process, so as to accurately reflect the complex "serial and parallel" logic in the service, avoid the disconnection between the monitoring model and the actual situation, and achieve full-link monitoring.

[0106] As Figure 3 shown, it is a schematic structural diagram of a service full-link monitoring device provided by the present invention. The service full-link monitoring device includes: A judgment module, configured to extract the first service attribute corresponding to the corresponding service after judging that the demand side sends a service monitoring demand.

[0107] A traversal module, configured to traverse the corresponding first link in the database based on the first service attribute, and classify and count all link nodes in the first link to obtain a first active node and a first passive node.

[0108] An extraction module, configured to extract the service monitoring scenario corresponding to the service, and screen the first active node and the first passive node based on the scenario attribute of the service monitoring scenario to obtain a second active node and a second passive node.

[0109] A combination module, configured to sequentially combine the second active node and the second passive node to obtain a total link for monitoring.

[0110] The present invention also provides a storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided by the above various embodiments.

[0111] Among them, the storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the storage medium is coupled to the processor, so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the storage medium can also exist as discrete components in a communication device. The storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0112] The present invention also provides a program product, which includes execution instructions stored in a storage medium. At least one processor of a device can read the execution instructions from the storage medium, and at least one processor executes the execution instructions so that the device implements the methods provided in the various embodiments described above.

[0113] In the above-mentioned terminal or server embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. Business full-link monitoring method, characterized in that Including: After determining that the demand side sends a service monitoring demand, extracting the first service attribute corresponding to the corresponding service; Based on the first service attribute, traversing the corresponding first link in the database, and classifying and counting all link nodes in the first link to obtain a first active node and a first passive node; Extracting the service monitoring scenario corresponding to the service, and filtering the first active node and the first passive node based on the scenario attributes of the service monitoring scenario to obtain a second active node and a second passive node; Combining the second active node and the second passive node in sequence to obtain a total link for monitoring.

2. The method according to claim 1, wherein: The extracting the first service attribute corresponding to the corresponding service after determining that the demand side sends a service monitoring demand includes: After determining that the demand side sends a service monitoring demand to the server, extracting the target service in the service monitoring demand; Determining the first service attribute corresponding to the target service, each service having a preset service attribute, and the service attribute having no relevance to the entity's service monitoring scenario.

3. The method according to claim 1, wherein: The traversing the corresponding first link in the database based on the first service attribute, and classifying and counting all link nodes in the first link to obtain a first active node and a first passive node includes: Traversing all links corresponding to the first service attribute in the database to obtain a first link; Sequentially traversing each link node in the first link, and dividing the link nodes into a first active node and a first passive node according to the first device and the first method extracted from the information in the link node; Counting the union of the path point labels, personnel labels, and device labels corresponding to each node in the first link to obtain a first label set.

4. The method according to claim 3, wherein: The dividing the link nodes into a first active node and a first passive node according to the first device and the first method extracted from the information in the link node includes: If it is determined that the first device in the link node does not have an input module, and the corresponding first method is to automatically extract by executing a program, then the corresponding link node is used as the first active node; If it is determined that the first device in the link node has an input module, and the corresponding first method is to extract after corresponding triggering, then the corresponding link node is used as the first passive node.

5. The method according to claim 1, wherein: The extracting the service monitoring scenario corresponding to the service, and filtering the first active node and the first passive node based on the scenario attributes of the service monitoring scenario to obtain a second active node and a second passive node includes: Determining the entity path points, entity personnel, and entity devices in the service monitoring scenario, and generating corresponding path point labels, personnel labels, and device labels; Comparing the path point labels, personnel labels, and device labels with the first active node and the first passive node to determine the remaining second active node and second passive node, and generating a node statistical table after classifying the nodes.

6. The method according to claim 5, wherein: The determining the remaining second active node and second passive node, and generating a node statistical table after classifying the nodes includes: Retain the first active node and the first passive node corresponding to the path point label, personnel label, and device label as the second active node and the second passive node; Take the deleted first active node and the first passive node as the third active node and the third passive node; After double-checking the second active node and the second passive node, count all the nodes and fill them into the corresponding area in the statistical table.

7. The method according to claim 6, wherein After the double-checking of the second active node and the second passive node, counting all the nodes and filling them into the corresponding area in the statistical table includes: Count the entity path points, entity personnel, and entity devices of the service monitoring scenario corresponding to the second active node and the second passive node to obtain a second label set; Compare the first label set with the second label set to determine the labels that exist in the first label set but do not exist in the second label set to obtain a difference label set; Count and fill all the nodes and the difference label set into the statistical table.

8. The method according to claim 5, wherein The combining the second active node and the second passive node in sequence to obtain a total link for monitoring includes: Determine the time sequence order of the entity path points, entity personnel, and entity devices in the service monitoring scenario; Extract the earliest time sequence order of the labels corresponding to the second active node and the second passive node as the combined time sequence; Based on the combined time sequence, combine all the second active nodes and the second passive nodes to obtain a total link for monitoring.

9. The method according to claim 8, wherein The combining all the second active nodes and the second passive nodes based on the combined time sequence to obtain a total link for monitoring includes: If it is judged that the time sequence difference value of any second active node and / or second passive node is less than or equal to a preset value, then take the second active node and / or second passive node as a parallel group; After the parallel groups are set in parallel, connect them to the second active nodes and / or second passive nodes before and after respectively to obtain a total link in a mixed connection state.

10. The method according to claim 6, wherein The generating a node statistical table after classifying the nodes includes: Determine the number of the third active node and the third passive node in the statistical table to obtain the number of missing nodes; Determine the number of the path point label, personnel label, and device label in each of the third active node and the third passive node in the statistical table to obtain the number of missing first labels; Determine the number of the difference label set in the statistical table to obtain the number of missing second labels; Based on the number of missing nodes, the number of missing first labels, and the number of missing second labels, comprehensively calculate the coefficient to be supplemented for the total link and fill it into the node statistical table.

11. The method according to claim 10, wherein The comprehensively calculating the coefficient to be supplemented for the total link based on the number of missing nodes, the number of missing first labels, and the number of missing second labels includes: Divide the number of missing nodes, the number of missing first labels, and the number of missing second labels by a preset constant value respectively and then add them up to obtain the coefficient to be supplemented.

12. Business full-link monitoring device, characterized in that, Includes: A judgment module, configured to extract a first service attribute corresponding to a corresponding service after a service monitoring requirement is sent by a demand side; A traversal module, configured to traverse a corresponding first link in a database based on the first service attribute, and classify and count all link nodes in the first link to obtain a first active node and a first passive node; An extraction module, configured to extract a service monitoring scenario corresponding to a service, and screen the first active node and the first passive node based on scenario attributes of the service monitoring scenario to obtain a second active node and a second passive node; A combination module, configured to sequentially combine the second active node and the second passive node to obtain a total link for monitoring.

13. A medium, characterized in that, The medium stores a computer program, and when the computer program is executed by a processor, it is used to implement the method according to any one of claims 1 to 11.

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