CN114926042A - Network logistics monitoring method, device, equipment and storage medium - Google Patents
Network logistics monitoring method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of logistics, and discloses a method, a device, equipment and a storage medium for monitoring network logistics. The method comprises the following steps: acquiring logistics information of a target network point, and calculating a first index value corresponding to the logistics information based on a preset timeliness index; determining a second index value of the assessment dimensionality corresponding to the target network point, and performing abnormity judgment on the first index value based on the second index value; acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information; and matching a corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point. The method and the device improve timeliness of monitoring the information of the related logistics network points.
Description
Technical Field
The invention relates to the technical field of logistics, in particular to a method, a device, equipment and a storage medium for monitoring network logistics.
Background
With the explosion of the caller in recent years, the high-speed development of the logistics industry and the continuous expansion of related services are driven. When the number of logistics businesses is increasing, express order processing and service requirements in the logistics industry are also improved, and especially for express items which cannot be transferred and delivered in time, if relevant information cannot be updated and relevant processing of the express items cannot be performed in time, service capacity of relevant network points or transfer station customers is reduced, customer complaint rate is increased, and accordingly the processes of monitoring receipts of the express items in time and the like become a trend of logistics enterprises.
In the conventional monitoring of the logistics express, all transportation operation data is uploaded to a remote server in a unified manner, the remote server performs related monitoring judgment through a real-time calculation engine or an offline calculation engine, and processed monitoring information is sent to related websites or personnel. However, as the volume of the service data increases rapidly, the data divisor and the processing capacity are large, and the service processing is required to be performed in combination with the indexes of the related distribution points, which affects the timeliness of the monitoring of the distribution points, that is, the timeliness of the existing information monitoring of the distribution points is low.
Disclosure of Invention
The invention mainly aims to solve the problem that the timeliness of the conventional information monitoring of logistics nodes is low.
The invention provides a network logistics monitoring method in a first aspect, which comprises the following steps: acquiring logistics information of a target network point, and calculating a first index value corresponding to the logistics information based on a preset timeliness index; determining a second index value of the assessment dimension corresponding to the target mesh point, and performing abnormity judgment on the first index value based on the second index value; acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information; and matching a corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point.
Optionally, in a first implementation manner of the first aspect of the present invention, the calculating the first index value corresponding to the logistics information based on a preset aging index includes: analyzing different level indexes in the preset aging indexes to obtain a first level index and a second level index; calculating a first level numerical value of the logistics information by using the first level index; and calculating a second-level numerical value of the logistics information based on the first-level numerical value and the second-level index.
Optionally, in a second implementation manner of the first aspect of the present invention, the determining a second index value of the assessment dimension corresponding to the target site includes: determining a mesh point grade corresponding to the target mesh point, and matching a basic dimension corresponding to the mesh point grade; and matching a plurality of second index values corresponding to the basic dimensionality and taking the second index values as second index values of the dimensionality corresponding to the target mesh point.
Optionally, in a third implementation manner of the first aspect of the present invention, the performing an abnormality determination on the first index value based on the second index value includes: comparing the second index value with the corresponding first index value; if the first index value is larger than the second index value, judging the first index value as an abnormal index value; and if the first index value is not greater than the second index value, continuing to monitor the assessment index of the target site.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the abnormal state information includes first abnormal state information and second abnormal state information, and the performing logistics state calculation on the abnormal logistics information to obtain the abnormal state information includes: calculating the prediction state information corresponding to the abnormal logistics information, and judging whether the prediction state information is matched with the abnormal logistics information; if the predicted state information is not matched with the abnormal logistics information, generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information; if the predicted state information is matched with the abnormal logistics information, calculating predicted time information corresponding to the abnormal logistics information, and generating second abnormal state information according to the predicted time information and the abnormal logistics information.
Optionally, in a fifth implementation manner of the first aspect of the present invention, if the predicted state information does not match the abnormal logistics information, generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information includes: if the predicted state information is not matched with the abnormal logistics information, comparing the predicted state information with the abnormal logistics information to obtain comparison information; and matching the corresponding abnormal state type according to the comparison information, and generating corresponding first abnormal state information based on the abnormal state type and the predicted state information.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the exception handling scheme includes a first exception scheme and a second exception scheme, and the matching, according to the exception state information, a corresponding exception handling scheme by using a preset exception handling policy includes: if the abnormal state information is first abnormal state information, matching a corresponding first abnormal scheme for state exception handling according to the website state information in the first abnormal state information; and if the abnormal state information is second abnormal state information, comparing the time state information in the second abnormal state information with preset delay time, and matching a corresponding second abnormal scheme for time abnormality processing according to the comparison result.
The second aspect of the present invention provides a network logistics monitoring apparatus, including: the index calculation module is used for acquiring logistics information of a target network point and calculating a first index value corresponding to the logistics information based on a preset timeliness index; the anomaly determination module is used for determining a second index value of the assessment dimension corresponding to the target mesh point and performing anomaly determination on the first index value based on the second index value; the state calculation module is used for acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and performing logistics state calculation on the abnormal logistics information to obtain abnormal state information; and the scheme matching module is used for matching a corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information and sending the exception scheme to the target network point.
Optionally, in a first implementation manner of the second aspect of the present invention, the index calculation module includes: the index analyzing unit is used for analyzing different level indexes in the preset aging indexes to obtain a first level index and a second level index; a first index calculation unit configured to calculate a first level value of the logistics information using the first level index; and the second index calculating unit is used for calculating a second level numerical value of the logistics information based on the first level numerical value and the second level index.
Optionally, in a second implementation manner of the second aspect of the present invention, the abnormality determining module includes: the dimension matching unit is used for determining a mesh point grade corresponding to the target mesh point and matching a basic dimension corresponding to the mesh point grade; and the examination matching unit is used for matching a plurality of second index values corresponding to the basic dimensionality and taking the second index values as second index values of the dimensionality corresponding to the target mesh point.
Optionally, in a third implementation manner of the second aspect of the present invention, the abnormality determining module further includes: a value comparison unit, configured to perform a value comparison between the second index value and the corresponding first index value; a first determination unit configured to determine the first index value as an abnormal index value if the first index value is greater than the second index value; and the second judgment unit is used for continuing monitoring the assessment indexes of the target mesh point if the first index value is not greater than the second index value.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the state calculating module includes: the state matching unit is used for calculating the prediction state information corresponding to the abnormal logistics information and judging whether the prediction state information is matched with the abnormal logistics information or not; the first abnormal unit is used for generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information if the predicted state information is not matched with the abnormal logistics information; and the second abnormal unit is used for calculating the predicted time information corresponding to the abnormal logistics information if the predicted state information is matched with the abnormal logistics information, and generating second abnormal state information according to the predicted time information and the abnormal logistics information.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the first exception unit includes: if the predicted state information is not matched with the abnormal logistics information, comparing the predicted state information with the abnormal logistics information to obtain comparison information; and matching the corresponding abnormal state type according to the comparison information, and generating corresponding first abnormal state information based on the abnormal state type and the predicted state information.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the scheme matching module includes: a first scheme unit, configured to, if the abnormal state information is first abnormal state information, match a first abnormal scheme of corresponding state exception handling according to mesh point state information in the first abnormal state information; and the second scheme unit is used for comparing the time state information in the second abnormal state information with the preset delay time if the abnormal state information is the second abnormal state information, and matching a corresponding second abnormal scheme of time abnormality processing according to the comparison result.
A third aspect of the present invention provides a network logistics monitoring apparatus, including: a memory and at least one processor, the memory having instructions stored therein; the at least one processor calls the instructions in the memory to enable the website logistics monitoring equipment to execute the steps of the website logistics monitoring method.
A fourth aspect of the present invention provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to perform the steps of the above-mentioned network-point logistics monitoring method.
According to the technical scheme provided by the invention, logistics information of a target network point is obtained, and a first index value corresponding to the logistics information is calculated based on a preset timeliness index; determining a second index value of the assessment dimension corresponding to the target mesh point, and performing anomaly judgment on the first index value based on the second index value; acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information; and matching the corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point. Compared with the prior art, the method and the device have the advantages that the first index value corresponding to the target network point is calculated, the second index value corresponding to the dimensionality of the network point is obtained, the abnormity judgment is carried out based on the first index value and the second index value, the logistics state abnormity judgment is carried out according to the judgment result, and therefore the abnormal state judgment result is matched with the corresponding abnormity scheme and the scheme feedback. The abnormity judgment of the evaluation indexes of the logistics information of different network points is realized, and corresponding schemes are generated in time according to the abnormal state conditions and sent to the target network points for processing, so that the timeliness of monitoring the related logistics network point information is improved.
Drawings
FIG. 1 is a schematic diagram of a first embodiment of a network point logistics monitoring method in an embodiment of the invention;
FIG. 2 is a schematic diagram of a second embodiment of a network logistics monitoring method in an embodiment of the invention;
FIG. 3 is a schematic diagram of a third embodiment of a network point logistics monitoring method in an embodiment of the invention;
FIG. 4 is a schematic diagram of an embodiment of a network logistics monitoring apparatus in an embodiment of the invention;
FIG. 5 is a schematic diagram of another embodiment of a network logistics monitoring apparatus in an embodiment of the invention;
fig. 6 is a schematic diagram of an embodiment of a network logistics monitoring apparatus in an embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for monitoring logistics of a network, wherein the method comprises the following steps: acquiring logistics information of a target network point, and calculating a first index value corresponding to the logistics information based on a preset timeliness index; determining a second index value of the assessment dimension corresponding to the target mesh point, and performing abnormity judgment on the first index value based on the second index value; acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information; and matching a corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point. The method and the device improve timeliness of monitoring the information of the related logistics network points.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Moreover, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For the sake of understanding, the following describes a specific flow of an embodiment of the present invention, and referring to fig. 1, a first embodiment of a method for monitoring logistics at a site according to an embodiment of the present invention includes:
101. acquiring logistics information of a target network point, and calculating a first index value corresponding to the logistics information based on a preset timeliness index;
it is to be understood that the execution subject of the present invention may be a network logistics monitoring apparatus, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
In this embodiment, the target network point refers to an express transfer station where a logistics enterprise delivers relevant express from a sender to an addressee, and the intermediate transfer station passes through the intermediate transfer of the addressee, and includes express network points such as distribution centers and terminal delivery stations; the logistics information refers to express items and the like which need to be processed by corresponding network points; the preset time efficiency index refers to a time efficiency assessment index of express delivery transportation set by a corresponding logistics enterprise, and by carrying out relevant processing on the set time efficiency index, the whole logistics situation and the logistics situation of each logistics network can be subjected to statistical analysis, the logistics problem can be found, and the time efficiency of logistics transfer and monitoring can be improved.
In practical application, logistics information of a target network point corresponding to current logistics monitoring is obtained, and then various timeliness first index numerical values are calculated for the obtained logistics information based on timeliness index information preset by a logistics enterprise, a first level index and a second level index are obtained by analyzing different level indexes in the preset timeliness indexes, a first level numerical value of the logistics information is calculated by utilizing the first level index, and a second level numerical value of the logistics information is calculated based on the first level numerical value and the second level index, wherein the first index numerical value comprises the first level numerical value and the second level numerical value.
102. Determining a second index value of the assessment dimension corresponding to the target mesh point, and performing anomaly judgment on the first index value based on the second index value;
in this embodiment, the second index value refers to a second index value corresponding to logistics monitoring of different dimensionalities, that is, corresponding levels of network points, and assessment indexes and numerical requirements corresponding to network points of different dimensionalities are different; the abnormal judgment refers to whether each first index value calculated by the current network point is matched with a required second index value or not, and if part of the examination values in the current target network point is not matched with the corresponding second index value, the abnormal logistics condition of the target network point can be judged.
In practical application, determining a mesh point grade corresponding to a target mesh point according to the acquired target mesh point information, and matching a basic dimension corresponding to the mesh point grade; matching a plurality of second index values corresponding to the basic dimensionality and taking the second index values as second index values of the dimensionality corresponding to the target mesh points; further, according to the first index value obtained by the calculation, the second index value is compared with the corresponding first index value in a numerical comparison mode; if the first index value is larger than the second index value, judging the first index value as an abnormal index value; and if the first index value is not greater than the second index value, continuing to monitor the assessment index of the target site.
103. Acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information;
in this embodiment, the abnormal logistics information refers to that physical information corresponding to an item, of which a corresponding first index value does not conform to a second index value, is used as the abnormal logistics information, and the logistics state calculation refers to calling a logistics distribution simulation algorithm to perform simulation calculation on a logistics change state required by a corresponding express from a sender to a receiver, and performing logistics state calculation on the express with the abnormal logistics state information, so that a logistics state which should exist in a current express can be simulated, each express with abnormality can be better monitored, and the abnormal express can be better fed back and processed.
In practical application, acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, further calculating prediction state information corresponding to the abnormal logistics information, and judging whether the prediction state information is matched with the abnormal logistics information; if the predicted state information is not matched with the abnormal logistics information, generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information, namely comparing the predicted state information with the abnormal logistics information to obtain comparison information if the predicted state information is not matched with the abnormal logistics information, further matching a corresponding abnormal state type according to the comparison information, and generating corresponding first abnormal state information based on the abnormal state type and the predicted state information; if the predicted state information is matched with the abnormal logistics information, calculating predicted time information corresponding to the abnormal logistics information, and generating second abnormal state information according to the predicted time information and the abnormal logistics information.
104. And matching the corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point.
In this embodiment, the preset exception handling policy matching refers to matching, for different exception type express mails, a corresponding type of handling policy to better handle the exception express mails. Corresponding schemes are matched on the express mails with abnormal state information through news, the abnormal express mails existing in the monitoring process and the corresponding schemes are fed back to the target network points, and the monitoring timeliness of the related logistics network point information is improved.
In practical application, according to the abnormal state information obtained by the processing, if the abnormal state information is first abnormal state information, matching a corresponding first abnormal scheme of the state abnormality processing according to the website state information in the first abnormal state information; if the abnormal state information is second abnormal state information, comparing the time state information in the second abnormal state information with preset delay time, and matching a corresponding second abnormal scheme for time exception processing according to the comparison result; and then sending the abnormal scheme obtained by matching to a target network point for express exception handling.
In the embodiment of the invention, logistics information of a target network point is obtained, and a first index value corresponding to the logistics information is calculated based on a preset timeliness index; determining a second index value of the assessment dimension corresponding to the target mesh point, and performing anomaly judgment on the first index value based on the second index value; acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information; and matching the corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point. Compared with the prior art, the method and the device have the advantages that the first index value corresponding to the target network point is calculated, the second index value corresponding to the dimensionality of the network point is obtained, the abnormity judgment is carried out based on the first index value and the second index value, the logistics state abnormity judgment is carried out according to the judgment result, and therefore the abnormal state judgment result is matched with the corresponding abnormity scheme and the scheme feedback. The abnormity judgment of the evaluation indexes of the logistics information of different network points is realized, and corresponding schemes are generated in time according to the abnormal state conditions and sent to the target network points for processing, so that the timeliness of monitoring the related logistics network point information is improved.
Referring to fig. 2, a second embodiment of the method for monitoring logistics at different points in the embodiment of the present invention includes:
201. analyzing different level indexes in the preset aging indexes to obtain a first level index and a second level index;
in the embodiment, the level indexes refer to indexes of different levels set by the logistics enterprises for the logistics examination, and the method sets two layers of assessment indexes as monitoring level indexes and can set multiple layers or even nested sub-layer indexes according to actual conditions, for example, the two layers of assessment indexes can be week assessment indexes, day assessment indexes and the like.
In practical application, logistics information of a target network point is obtained, and then indexes of different levels in the timeliness indexes are analyzed based on preset timeliness indexes, for example, classification is carried out according to two layers of weekly assessment indexes and daily assessment indexes, and a first-level index corresponding to weekly assessment and a second-level index corresponding to daily assessment are obtained.
202. Calculating a first level numerical value of the logistics information by using the first level index;
in this embodiment, because different hierarchical indexes have corresponding index calculation formulas or strategies, according to the analyzed first hierarchical index, that is, a calculation statistical manner corresponding to a smaller range of daily hierarchical indexes, for example, by statistically calculating each index (for example, daily turn rate, daily speed number, daily group number, daily complaint rate, etc.) to be assessed every day, a first hierarchical value corresponding to a plurality of sets is obtained.
203. Calculating a second level numerical value of the logistics information based on the first level numerical value and the second level index;
in this embodiment, based on the first-level numerical value and the second-level index obtained by the above processing, since the first-level index is a small-range index, and the second-level index is a calculation identifier (for example, a first-level numerical value) in a larger range for the first-level index, the first-level numerical value, the second-level index and a related calculation strategy are used for performing calculation, for example, each index (for example, a turnover rate in the week, a number of weekdays, a number of parcels in the week, a complaint rate, and the like) required to be assessed per week is statistically calculated, so as to obtain the second-level numerical values corresponding to the plurality of sets. Wherein the first index value and the second level value are collectively referred to as a first level value.
204. Determining a mesh point grade corresponding to a target mesh point, and matching a basic dimension corresponding to the mesh point grade;
in this embodiment, the network level here refers to the network level division of different functional entities by the logistics company, such as provincial and branch centers, city transit centers, distribution stations, and the like; the basic dimension here refers to an index dimension corresponding to the processing level.
In practical application, according to the acquired logistics information of the target network point, the network point grade corresponding to the target network point is determined, and then the processing dimensionality corresponding to the basic index corresponding to the network point grade is matched.
205. Matching a plurality of second index values corresponding to the basic dimensionality and taking the second index values as second index values of the dimensionality corresponding to the target mesh points;
in this embodiment, according to the basic dimension corresponding to the matched target mesh point, a plurality of second index values corresponding to the basic dimension are matched, and the plurality of matched second index values are used as second index values of the dimension corresponding to the target mesh point.
206. Comparing the second index value with the corresponding first index value;
in this embodiment, according to the second index value obtained by the processing and the first index value obtained by the target node calculation, the first level value and the second level value in the second index value and the corresponding first index value are compared, and whether the first index value of the corresponding item meets the value of the assessment index requirement interval is compared.
207. If the first index value is larger than the second index value, judging the first index value as an abnormal index value;
in this embodiment, according to the comparison result, if the first level value and the second level value of the first index value are greater than the second index value, the value greater than the first index value is determined as the abnormal first index value.
208. If the first index value is not greater than the second index value, continuing monitoring the assessment index of the target site;
in this embodiment, according to the comparison result, if the first level value and the second level value in the first index value are not greater than the second index value, the qualified index of the target website is continuously monitored.
209. Acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information;
210. and matching the corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point.
In the embodiment of the invention, different level indexes in preset aging indexes are analyzed to obtain a first level index and a second level index; calculating a first level numerical value of the logistics information by using the first level index; calculating a second level numerical value of the logistics information based on the first level numerical value and the second level index; determining a mesh point grade corresponding to a target mesh point, and matching a basic dimension corresponding to the mesh point grade; matching a plurality of second index values corresponding to the basic dimensionality and taking the second index values as second index values of the dimensionality corresponding to the target net points; comparing the second index value with the corresponding first index value; if the first index value is larger than the second index value, judging the first index value as an abnormal index value; and if the first index value is not greater than the second index value, continuing to monitor the assessment index of the target network point. Compared with the prior art, the method and the device have the advantages that the first index numerical calculation is carried out on the logistics information of the target network points, and the second index numerical values of the corresponding dimensionalities and the numerical values of the calculation results are matched for abnormal judgment, so that whether the current target network points have abnormal examination points or not is monitored, the monitoring processing of the examination indexes corresponding to different network points is realized, and the abnormal monitoring and the timely processing of the abnormal judgment are better carried out on different network points.
Referring to fig. 3, a third embodiment of the method for monitoring logistics at different points in the embodiment of the present invention includes:
301. acquiring logistics information of a target network point, and calculating a first index value corresponding to the logistics information based on a preset timeliness index;
302. determining a second index value of the assessment dimensionality corresponding to the target network point, and performing anomaly judgment on the first index value based on the second index value;
303. calculating the prediction state information corresponding to the abnormal logistics information, and judging whether the prediction state information is matched with the abnormal logistics information;
in this embodiment, the prediction state information refers to that the logistics state simulation prediction calculation of the express is performed by using a state simulation calculation algorithm of an internal logistics company to obtain the logistics transportation state information of the express, such as a transfer state, a transportation state, a delivery state, and the like of the express.
In practical application, the abnormal logistics information is subjected to state calculation by using a built-in state simulation calculation algorithm to obtain corresponding predicted state information, and whether the predicted state information is matched with the abnormal logistics information under a preset deviation requirement is further judged.
304. If the predicted state information is not matched with the abnormal logistics information, comparing the predicted state information with the abnormal logistics information to obtain comparison information;
in this embodiment, if the predicted status information and the abnormal logistics information are not matched within the corresponding matching error range, the predicted status information and the abnormal logistics information are compared, and the information of the unmatched part of the predicted status information and the abnormal logistics information is compared, so as to obtain the comparison information,
305. matching the corresponding abnormal state type according to the comparison information, and generating corresponding first abnormal state information based on the abnormal state type and the predicted state information;
in this embodiment, the exception status type herein refers to an exception type corresponding to a logistics status, such as a transit status exception, a delivery status exception, a mail address status exception, and the like.
In practical application, according to the comparison information, matching the abnormal state type corresponding to the abnormal index, and further analyzing the current first abnormal state information corresponding to the generation based on the abnormal state type and the predicted state information, if the current abnormal state type is the delivery state type and the predicted state information is the delivery completion state, generating the first abnormal state information by using the delivery state type and the completion state according to the template of the corresponding state type.
306. If the predicted state information is matched with the abnormal logistics information, calculating predicted time information corresponding to the abnormal logistics information, and generating second abnormal state information according to the predicted time information and the abnormal logistics information;
in this embodiment, if the predicted state information is matched with the abnormal logistics information, time calculation is performed on the abnormal logistics information by using a built-in time simulation calculation algorithm to obtain corresponding predicted time information, where the predicted time information may be delivery time, transit time, receiving time, and the like, and then according to the predicted time information and the abnormal logistics information, according to a template of a corresponding time type, second abnormal state information is generated by using the predicted time information and the abnormal logistics information; the abnormal state information comprises first abnormal state information and second abnormal state information.
307. If the abnormal state information is first abnormal state information, matching a corresponding first abnormal scheme for state exception handling according to the website state information in the first abnormal state information;
in this embodiment, according to the result of the processing, if the abnormal state information is the first abnormal state information, the processing scheme corresponding to the abnormal state is matched according to the dot state information in the first abnormal state information, and if there is an abnormal delivery state, the delivery processing scheme of the corresponding dot region is matched, so as to obtain the first abnormal scheme.
308. If the abnormal state information is second abnormal state information, comparing the time state information in the second abnormal state information with preset delay time, and matching a corresponding second abnormal scheme for time abnormality processing according to the comparison result.
In this embodiment, according to the processing result, if the abnormal status information is the second abnormal status information, and because the abnormal indicator does not have the status abnormality problem, comparing whether the time status information in the second abnormal status information and the preset delay time are within the allowable range, and further according to the comparison result, searching the current abnormal status duration for the second abnormal status information that does not meet the preset delay time requirement, wherein the abnormal status duration includes a period from the abnormal start time to the abnormal end time of the selected abnormal node and a period from the abnormal start time to the abnormal end time, and the "abnormal start time" refers to a period from the time when an abnormal status occurs in a certain express node to the time when the abnormal node is determined during the continuous monitoring process for the express node, or a certain express node actively reports the abnormal status and determines the abnormal status as the abnormal node, considering that a monitoring system has certain delay in the process of judging the abnormal mesh points, namely the abnormal starting time is later than the actual abnormal starting time, a certain preset time needs to be pushed forward to enable the time period between the abnormal starting time and the abnormal ending time to comprehensively cover the actual abnormal state duration of the abnormal mesh points; and matching a corresponding time exception handling scheme according to the duration of the exception state and the comparison result, if the transfer time is overtime and is overtime for two minutes, generating a handling scheme between two transfer stations and between transport vehicles to obtain a second exception scheme, wherein the exception schemes comprise a first exception scheme and a second exception scheme.
In the embodiment of the invention, the prediction state information corresponding to the abnormal logistics information is calculated, and whether the prediction state information is matched with the abnormal logistics information is judged; if the predicted state information is not matched with the abnormal logistics information, generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information; if the predicted state information is matched with the abnormal logistics information, calculating predicted time information corresponding to the abnormal logistics information, and generating second abnormal state information according to the predicted time information and the abnormal logistics information; if the abnormal state information is first abnormal state information, matching a corresponding first abnormal scheme for state exception processing according to the website state information in the first abnormal state information; and if the abnormal state information is second abnormal state information, comparing the time state information in the second abnormal state information with preset delay time, and matching a corresponding second abnormal scheme for time abnormality processing according to the comparison result. Compared with the prior art, the method and the device have the advantages that the abnormal state judgment and the time abnormality judgment are carried out on the logistics information with the abnormal first index value, and then the corresponding abnormal handling scheme is generated according to the judged result type and is sent to corresponding personnel, so that the real-time monitoring on the logistics information of the network points is realized, meanwhile, the corresponding scheme is generated according to the abnormal condition obtained through monitoring, the related personnel can timely feed back and process the logistics information with the abnormal state, and the transportation timeliness of logistics and the logistics satisfaction of customers are improved.
In the above description of the method for monitoring logistics at a site in the embodiment of the present invention, referring to fig. 4, a device for monitoring logistics at a site in the embodiment of the present invention is described below, where one embodiment of the device for monitoring logistics at a site in the embodiment of the present invention includes:
the index calculation module 401 is configured to acquire logistics information of a target site, and calculate a first index value corresponding to the logistics information based on a preset timeliness index;
an anomaly determination module 402, configured to determine a second index value of the evaluation dimension corresponding to the target mesh point, and perform anomaly determination on the first index value based on the second index value;
a state calculation module 403, configured to obtain corresponding abnormal logistics information based on a result of the abnormal determination, and perform logistics state calculation on the abnormal logistics information to obtain abnormal state information;
and the scheme matching module 404 is configured to match a corresponding exception handling scheme by using a preset exception handling policy according to the exception state information, and send the exception handling scheme to the target network point.
In the embodiment of the invention, logistics information of a target network point is obtained, and a first index value corresponding to the logistics information is calculated based on a preset timeliness index; determining a second index value of the assessment dimension corresponding to the target mesh point, and performing anomaly judgment on the first index value based on the second index value; acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information; and matching the corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point. Compared with the prior art, the method and the device have the advantages that the first index value corresponding to the target network point is calculated, the second index value corresponding to the network point dimension is obtained, the abnormality judgment is carried out based on the first index value and the second index value, the logistics state abnormality judgment is carried out according to the judgment result, and therefore the result of the state abnormality judgment is matched with the corresponding abnormality scheme and the scheme feedback. The abnormity judgment of the evaluation indexes of the logistics information of different network points is realized, and corresponding schemes are generated in time according to the abnormal state conditions and sent to the target network points for processing, so that the timeliness of monitoring the related logistics network point information is improved.
Referring to fig. 5, another embodiment of the network logistics monitoring apparatus in the embodiment of the invention includes:
the index calculation module 401 is configured to obtain logistics information of a target site, and calculate a first index value corresponding to the logistics information based on a preset timeliness index;
an anomaly determination module 402, configured to determine a second index value of the evaluation dimension corresponding to the target mesh point, and perform anomaly determination on the first index value based on the second index value;
a state calculation module 403, configured to obtain corresponding abnormal logistics information based on a result of the abnormal determination, and perform logistics state calculation on the abnormal logistics information to obtain abnormal state information;
and the scheme matching module 404 is configured to match a corresponding exception handling scheme by using a preset exception handling policy according to the exception state information, and send the exception handling scheme to the target network point.
Further, the index calculation module 401 includes:
the index analyzing unit 4011 is configured to analyze different levels of indexes in the preset aging indexes to obtain a first level index and a second level index; a first index calculation unit 4012, configured to calculate a first index value of the logistics information by using the first level index; a second index calculation unit 4013, configured to calculate a second index value of the logistics information based on the first index value and the second-tier index.
Further, the abnormality determination module 402 includes:
a dimension matching unit 4021, configured to determine a mesh point rank corresponding to the target mesh point, and match a basic dimension corresponding to the mesh point rank; and the assessment matching unit 4022 is configured to match the plurality of second index values corresponding to the basic dimensionality and serve as the second index values of the dimensionality corresponding to the target website.
Further, the abnormality determining module 402 further includes:
a numerical comparison unit 4023, configured to perform numerical comparison between the second index value and the corresponding first index value; a first determination unit 4024, configured to determine the first index value as an abnormal index value if the first index value is greater than the second index value; a second determining unit 4025, configured to continue to monitor the assessment index of the target website if the first index value is not greater than the second index value.
Further, the state calculation module 403 includes:
a state matching unit 4031, configured to calculate predicted state information corresponding to the abnormal logistics information, and determine whether the predicted state information matches the abnormal logistics information; a first abnormal unit 4032, configured to generate corresponding first abnormal state information according to the abnormal logistics information and the predicted state information if the predicted state information does not match the abnormal logistics information; a second abnormal unit 4033, configured to calculate, if the predicted state information matches the abnormal logistics information, predicted time information corresponding to the abnormal logistics information, and generate second abnormal state information according to the predicted time information and the abnormal logistics information.
Further, the first abnormality unit 4032 includes:
if the predicted state information is not matched with the abnormal logistics information, comparing the predicted state information with the abnormal logistics information to obtain comparison information; and matching the corresponding abnormal state type according to the comparison information, and generating corresponding first abnormal state information based on the abnormal state type and the predicted state information.
Further, the scheme matching module 404 includes:
a first scheme unit 4041, configured to, if the abnormal state information is first abnormal state information, match a corresponding first abnormal scheme for state exception handling according to node state information in the first abnormal state information; a second scheme unit 4042, configured to, if the abnormal state information is second abnormal state information, compare time state information in the second abnormal state information with a preset delay time, and match a corresponding second abnormal scheme of time exception handling according to a comparison result.
In the embodiment of the invention, the corresponding assessment index abnormity judgment is carried out according to the corresponding aging index of the target network point, the corresponding abnormity type is matched according to the abnormity index, and the corresponding processing scheme is matched according to the abnormity type. The system and the method realize the monitoring of indexes of corresponding distribution points, are convenient for relevant personnel to inquire and detect index data, realize the real-time and effective monitoring of different logistics distribution points, shorten the discovery time of logistics abnormity, and improve the processing speed of logistics and the satisfaction degree of customers.
Fig. 4 and 5 describe the network logistics monitoring apparatus in the embodiment of the invention in detail from the perspective of the modular functional entity, and the network logistics monitoring apparatus in the embodiment of the invention is described in detail from the perspective of hardware processing.
Fig. 6 is a schematic structural diagram of a logistics monitoring apparatus at a website according to an embodiment of the present invention, where the logistics monitoring apparatus 600 may generate relatively large differences due to different configurations or performances, and may include one or more processors (CPUs) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing applications 633 or data 632. Memory 620 and storage medium 630 may be, among other things, transient or persistent storage. The program stored in the storage medium 630 may include one or more modules (not shown), each of which may include a series of instruction operations for the network logistics monitoring apparatus 600. Further, the processor 610 may be configured to communicate with the storage medium 630, and execute a series of instruction operations in the storage medium 630 on the network logistics monitoring apparatus 600.
The site logistics monitor apparatus 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input-output interfaces 660, and/or one or more operating systems 631, such as Windows service, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the configuration of the dot logistics monitoring apparatus shown in FIG. 6 does not constitute a limitation of the dot logistics monitoring apparatus, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The invention further provides a network point logistics monitoring device, which includes a memory and a processor, where the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the processor executes the steps of the network point logistics monitoring method in the foregoing embodiments.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, having stored therein instructions, which, when executed on a computer, cause the computer to perform the steps of the network point logistics monitoring method.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is substantially or partly contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a portable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A network logistics monitoring method is characterized by comprising the following steps:
acquiring logistics information of a target network point, and calculating a first index value corresponding to the logistics information based on a preset timeliness index;
determining a second index value of the assessment dimension corresponding to the target mesh point, and performing abnormity judgment on the first index value based on the second index value;
acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and carrying out logistics state calculation on the abnormal logistics information to obtain abnormal state information;
and matching a corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information, and sending the exception scheme to the target network point.
2. The network logistics monitoring method of claim 1, wherein the first index value comprises a first level value and a second level value, and the calculating the first index value corresponding to the logistics information based on the preset timeliness index comprises:
analyzing different level indexes in the preset aging indexes to obtain a first level index and a second level index;
calculating a first level numerical value of the logistics information by using the first level index;
and calculating a second-level numerical value of the logistics information based on the first-level numerical value and the second-level index.
3. The website logistics monitoring method of claim 1, wherein the determining of the second index value of the assessment dimension corresponding to the target website comprises:
determining a mesh point grade corresponding to the target mesh point, and matching a basic dimension corresponding to the mesh point grade;
and matching a plurality of second index values corresponding to the basic dimensionality and taking the second index values as second index values of the dimensionality corresponding to the target mesh point.
4. The network logistics monitoring method of claim 1, wherein the determining the abnormality of the first index value based on the second index value comprises:
comparing the second index value with the corresponding first index value;
if the first index value is larger than the second index value, judging the first index value as an abnormal index value;
and if the first index value is not greater than the second index value, continuing to monitor the assessment index of the target site.
5. The network logistics monitoring method of claim 1, wherein the abnormal state information comprises a first abnormal state information and a second abnormal state information, and the performing the logistics state calculation on the abnormal logistics information to obtain the abnormal state information comprises:
calculating the prediction state information corresponding to the abnormal logistics information, and judging whether the prediction state information is matched with the abnormal logistics information;
if the predicted state information is not matched with the abnormal logistics information, generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information;
if the predicted state information is matched with the abnormal logistics information, calculating predicted time information corresponding to the abnormal logistics information, and generating second abnormal state information according to the predicted time information and the abnormal logistics information.
6. The network logistics monitoring method of claim 5, wherein if the predicted state information does not match the abnormal logistics information, generating corresponding first abnormal state information according to the abnormal logistics information and the predicted state information comprises:
if the predicted state information is not matched with the abnormal logistics information, comparing the predicted state information with the abnormal logistics information to obtain comparison information;
and matching the corresponding abnormal state type according to the comparison information, and generating corresponding first abnormal state information based on the abnormal state type and the predicted state information.
7. The website logistics monitoring method according to claim 6, wherein the exception scheme comprises a first exception scheme and a second exception scheme, and the matching of the corresponding exception handling scheme by using a preset exception handling policy according to the exception state information comprises:
if the abnormal state information is first abnormal state information, matching a corresponding first abnormal scheme for state exception handling according to the website state information in the first abnormal state information;
if the abnormal state information is second abnormal state information, comparing the time state information in the second abnormal state information with preset delay time, and matching a corresponding second abnormal scheme for time abnormality processing according to the comparison result.
8. A network logistics monitoring device, characterized in that, the network logistics monitoring device includes:
the index calculation module is used for acquiring logistics information of a target network point and calculating a first index value corresponding to the logistics information based on a preset timeliness index;
the anomaly determination module is used for determining a second index value of the assessment dimension corresponding to the target mesh point and performing anomaly determination on the first index value based on the second index value;
the state calculation module is used for acquiring corresponding abnormal logistics information based on the result of the abnormal judgment, and performing logistics state calculation on the abnormal logistics information to obtain abnormal state information;
and the scheme matching module is used for matching a corresponding exception handling scheme by using a preset exception handling strategy according to the exception state information and sending the exception scheme to the target network point.
9. A network-point logistics monitoring device, characterized in that the network-point logistics monitoring device comprises: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invokes the instructions in the memory to cause the site logistics monitoring apparatus to perform the steps of the site logistics monitoring method of any one of claims 1-7.
10. A computer-readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement the steps of the network point logistics monitoring method according to any one of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115795335A (en) * | 2023-02-02 | 2023-03-14 | 国家邮政局邮政业安全中心 | Logistics network anomaly identification method and device and electronic equipment |
| CN116485301A (en) * | 2023-05-30 | 2023-07-25 | 佛山众陶联供应链服务有限公司 | Service authenticity judging method and system based on service information and logistics information |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115795335A (en) * | 2023-02-02 | 2023-03-14 | 国家邮政局邮政业安全中心 | Logistics network anomaly identification method and device and electronic equipment |
| CN116485301A (en) * | 2023-05-30 | 2023-07-25 | 佛山众陶联供应链服务有限公司 | Service authenticity judging method and system based on service information and logistics information |
| CN116485301B (en) * | 2023-05-30 | 2023-12-05 | 佛山众陶联供应链服务有限公司 | Service authenticity judging method and system based on service information and logistics information |
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