Logistics ultra-long order time monitoring method, device, equipment and storage medium

Abstract

The present invention relates to the field of logistics technology, and in particular to a method, device, equipment and storage medium for monitoring the timeliness of logistics overlong orders. The method collects the sources of logistics orders from various business provinces at a preset time to obtain order source data, and the reference configuration time data needs to be calculated according to the routing information of each logistics order in the logistics order source and the flow time of each logistics stage; the warning time is configured according to the preset to-be-configured rules and the reference configuration time data to make the warning time data more accurate; and then unique order warning data is obtained according to the combination of the logistics order and the warning time data. During monitoring, the real-time time data of each logistics stage is monitored through the order warning data, and a warning is issued if a timeout is about to occur, so as to improve the timeliness achievement rate of the overall link of the logistics order, and effectively reduce the proportion of overlong orders in the evaluation indicators of the shopping platform for logistics companies.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to a logistics ultra-long single time monitoring method, device, equipment and storage medium. Background Art

[0002] In the circulation process of logistics orders, logistics orders that take too long are logistics orders that take too long. The logistics timeliness is calculated from the time the order is placed until the goods are received. The logistics timeliness represents the logistics speed, such as some services that are delivered on the same day, the next day, the next day, and no longer than 4 days. The shorter the life cycle of the logistics, the faster the logistics timeliness. The logistics timeliness determines the service quality of the logistics company. In the existing technology, the timeliness monitoring of logistics generally only records the logistics information of the package, and the reasons for the formation of logistics overlong orders are relatively complicated (such as improper first distribution operation resulting in delivery display timeout, transportation road conditions resulting in in-transit time overtime, etc.), and the impact of human and environmental factors is relatively large, so it is difficult to accurately monitor each overlong order and it is difficult to ensure that each overlong order can be delivered on time.

[0003] It can be seen that the existing technology still needs to be improved and enhanced. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method, device, equipment and storage medium for monitoring the timeliness of logistics overlong orders, which automatically configures reasonable early warning timeliness configuration information according to the historical order data of the merchant platform, improves the monitoring accuracy of the logistics status of logistics pieces at various stages, and effectively reduces the proportion of overlong orders in the merchant platform's assessment indicators for logistics providers, thereby improving the achievement rate of the overall link timeliness of logistics providers.

[0005] The first aspect of the present invention provides a method for monitoring the timeliness of logistics overlong orders, including: obtaining order source data according to a preset time; extracting the duration data of each logistics stage according to the order source data, and generating reference configuration duration data; performing time configuration according to preset to-be-configured rules and the reference configuration duration data to generate warning duration data; obtaining a logistics order, and calculating the time configuration of the logistics order according to the warning duration data to obtain order warning data; obtaining real-time duration data of each logistics stage of the logistics order, and performing timeout monitoring on the real-time duration data according to the order warning data.

[0006] Optionally, in a first implementation method of the first aspect of the present invention, the duration data of each logistics stage is extracted according to the order source data, and reference configuration duration data is generated, including: the order source data includes the shopping platform type, business province address information and historical order data; the historical order data is classified according to the shopping platform type and the business province address information to classify the historical order data of the same shopping platform type and the same business province address information to obtain at least one reference order source data; the duration data of each logistics stage is extracted according to the reference order source data, and reference configuration duration data is generated.

[0007] Optionally, in a second implementation of the first aspect of the present invention, the extracting the duration data of each logistics stage according to the reference order source data and generating the reference configuration duration data includes: extracting the logistics routing information of each order according to the reference order source data; extracting the delivery duration data, the first distribution operation duration data, the in-transit transportation duration data, the last distribution operation duration data, the last distribution in-transit time data and the delivery time data according to the logistics routing information; extracting the delivery duration data, the first distribution operation duration data, the in-transit transportation duration data and the delivery duration data according to the logistics routing information; The average delivery time data, the average first distribution operation time data, the average in-transit transportation time data, the average last distribution operation time data, the average in-transit transportation time data and the delivery time data are calculated to obtain the average delivery time data, the average first distribution operation time data, the average in-transit transportation time data, the average last distribution operation time data, the average in-transit transportation time data and the delivery time data; the reference configuration time data is generated according to the average delivery time data, the average first distribution operation time data, the average in-transit transportation time data, the average last distribution operation time data, the average in-transit distribution time data and the delivery time data.

[0008] Optionally, in a third implementation method of the first aspect of the present invention, time configuration is performed according to preset rules to be configured and reference configuration time data to generate warning time data, including: obtaining a fuzzy value of the warning time for each logistics stage according to the preset rules to be configured; extracting an average time value for each logistics stage according to the reference configuration time data; calculating a warning time range value for the corresponding logistics stage according to the average time value and the fuzzy value of the warning time; and generating warning time data according to each warning time range value.

[0009] Optionally, in a fourth implementation method of the first aspect of the present invention, the obtaining of a logistics order and calculating the time configuration of the logistics order based on the warning duration data to obtain order warning data includes: obtaining a logistics order and obtaining the logistics order time based on the logistics order; estimating and calculating the warning duration range value for each logistics stage of the logistics order based on the logistics order time and the warning duration data; obtaining routing planning data based on the logistics order; and adding the warning duration range value for each logistics stage to the routing planning data to obtain order warning data.

[0010] Optionally, in a fifth implementation method of the first aspect of the present invention, the real-time duration data of each logistics stage of the logistics order is obtained, and the real-time duration data is monitored for timeout according to the order warning data, including: obtaining the current logistics status according to the logistics order; obtaining the real-time duration data of the corresponding logistics stage according to the current logistics status; obtaining the warning duration range value of the corresponding logistics stage in the order warning data according to the current logistics status; monitoring the real-time duration data for timeout according to the warning duration range value; if the real-time duration data enters the interval of the warning duration range value, generating a warning feedback; if the real-time duration data has not entered or has exceeded the interval of the warning duration range value, it is prohibited to generate a warning feedback.

[0011] Optionally, in a sixth implementation method of the first aspect of the present invention, if the real-time duration data has not entered or has exceeded the interval of the warning duration range value, then the generation of warning feedback is prohibited, including: if the real-time duration data has not entered the interval of the warning duration range value, then the generation of warning feedback is prohibited; if the real-time duration data exceeds the interval of the warning duration range value, then a reset instruction is generated, and the generation of warning feedback is prohibited; according to the reset instruction, the real-time scanning time of the next logistics stage is obtained, and the warning duration range value of the subsequent logistics stage of the logistics order is re-estimated based on the real-time scanning time and the warning duration data to obtain an updated warning duration range value; and the order warning data is updated according to the updated warning duration range value.

[0012] The second aspect of the present invention provides a logistics over-long order time monitoring device, including: an acquisition module, used to obtain order source data according to a preset time; an extraction module, used to extract the duration data of each logistics stage according to the order source data, and generate reference configuration duration data; a configuration module, used to perform time configuration according to a preset to-be-configured rule and the reference configuration duration data to generate warning duration data; a calculation module, used to obtain a logistics order, and calculate the time configuration of the logistics order according to the warning duration data to obtain order warning data; a monitoring module, used to obtain real-time duration data of each logistics stage of the logistics order, and perform timeout monitoring on the real-time duration data according to the order warning data.

[0013] Optionally, in a first implementation method of the second aspect of the present invention, the extraction module includes: a classification unit, used to classify the historical order data according to the shopping platform type and the business province address information, so as to classify the historical order data of the same shopping platform type and the same business province address information to obtain at least one reference order source data; an extraction unit, used to extract the duration data of each logistics stage according to the reference order source data, and generate reference configuration duration data.

[0014] Optionally, in a second implementation of the second aspect of the present invention, the extraction unit includes: a first extraction unit, which is used to extract logistics routing information of each order according to the reference order source data; a second extraction unit, which is used to extract delivery time data, first distribution operation time data, in-transit transportation time data, last distribution operation time data, last distribution in-transit time data and delivery time data according to the logistics routing information; a calculation unit, which is used to calculate the delivery time data, first distribution operation time data, in-transit transportation time data, last distribution in-transit time data and delivery time data according to the logistics routing information. The operation time data, the in-transit time data of the last distribution and the delivery time data are calculated to obtain the average delivery time data, the first distribution operation average time data, the in-transit transportation average time data, the last distribution operation average time data, the last distribution in-transit average time data and the delivery average time data; the generating unit is used to generate the reference configuration time data according to the average delivery time data, the first distribution operation average time data, the in-transit transportation average time data, the last distribution operation average time data, the last distribution in-transit average time data and the delivery average time data.

[0015] Optionally, in a third implementation method of the second aspect of the present invention, the configuration module includes: a preset unit, used to obtain a fuzzy value of the warning duration of each logistics stage according to a preset rule to be configured; a value obtaining unit, used to extract the average duration value of each logistics stage according to the reference configuration duration data; a range calculation unit, used to calculate the warning duration range value of the corresponding logistics stage according to the average duration value and the fuzzy value of the warning duration; and a generation unit, used to generate warning duration data according to each warning duration range value.

[0016] Optionally, in a fourth implementation method of the second aspect of the present invention, the calculation module includes: a first acquisition unit, used to acquire a logistics order, and acquire a logistics order time based on the logistics order; an estimation unit, used to estimate and calculate the warning time range value of each logistics stage of the logistics order based on the logistics order time and the warning time data; a second acquisition unit, used to acquire routing planning data based on the logistics order; an adding unit, used to add the warning time range value of each logistics stage to the routing planning data to obtain order warning data.

[0017] Optionally, in a fifth implementation of the second aspect of the present invention, the monitoring module includes: a third acquisition unit, used to acquire the current logistics status based on the logistics order; a fourth acquisition unit, used to acquire the real-time duration data of the corresponding logistics stage based on the current logistics status; a fifth acquisition unit, used to acquire the warning duration range value of the corresponding logistics stage in the order warning data based on the current logistics status; a feedback unit, used to perform timeout monitoring on the real-time duration data according to the warning duration range value; if the real-time duration data enters the interval of the warning duration range value, generating a warning feedback; a prohibition unit, used to prohibit the generation of warning feedback if the real-time duration data has not entered or has exceeded the interval of the warning duration range value.

[0018] Optionally, in a sixth implementation method of the second aspect of the present invention, the prohibition unit includes: a first prohibition unit, used to prohibit the generation of warning feedback if the real-time duration data does not enter the interval of the warning duration range value; a second prohibition unit, used to generate a reset instruction and prohibit the generation of warning feedback if the real-time duration data exceeds the interval of the warning duration range value; a reset unit, used to obtain the real-time scanning time of the next logistics stage according to the reset instruction, and re-estimate the warning duration range value of the subsequent logistics stage of the logistics order according to the real-time scanning time and the warning duration data to obtain an updated warning duration range value; an update unit, used to update the order warning data according to the updated warning duration range value.

[0019] The third aspect of the present invention provides a logistics over-long single time limit monitoring device, and the logistics over-long single time limit monitoring device comprises: a memory and at least one processor, and the memory stores instructions; at least one of the processors calls the instructions in the memory to enable the logistics over-long single time limit monitoring device to perform each step of the logistics over-long single time limit monitoring method described in any one of the above items.

[0020] A fourth aspect of the present invention provides a computer-readable storage medium having instructions stored thereon, and when the instructions are executed by a processor, the various steps of any of the above-mentioned methods for monitoring the over-long single time limit of logistics are implemented.

[0021] In the technical solution of the present invention, the sources of logistics orders from various business provinces are collected regularly by presetting a time to obtain order source data, and the reference configuration time data needs to be calculated based on the routing information of each logistics order in the logistics order source and the flow time of each logistics stage. The reference configuration time data is dynamic data with a certain timeliness and can change with market changes, thereby improving the accuracy of timeliness monitoring of each stage of logistics orders; the warning time is reasonably configured according to the preset rules to be configured and the dynamic reference configuration time data, so that the warning time data is more accurate and close to reality. international market situation; then, the actual logistics orders are combined with the warning time data to obtain the unique order warning data. The order warning data is determined according to the different logistics order situations. During monitoring, the real-time duration data of each logistics stage of the logistics order is monitored through the order warning data. If the real-time duration data enters the warning range set by the order warning data, the overtime warning is immediately fed back to the relevant distribution or related outlets or related personnel to improve the timeliness achievement rate of the overall logistics order link, effectively reducing the proportion of overlong orders in the shopping platform's assessment indicators for logistics companies, so as to improve the competitiveness of logistics companies in the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A first flow chart of a logistics ultra-long single time monitoring method provided by an embodiment of the present invention;

[0023] Figure 2 A second flow chart of the logistics ultra-long single time monitoring method provided by an embodiment of the present invention;

[0024] Figure 3 A third flow chart of the logistics ultra-long single time monitoring method provided by an embodiment of the present invention;

[0025] Figure 4 A fourth flow chart of the logistics ultra-long single time monitoring method provided by an embodiment of the present invention;

[0026] Figure 5 A fifth flow chart of the logistics ultra-long single time monitoring method provided by the embodiment of the present invention;

[0027] Figure 6 A sixth flow chart of the logistics ultra-long single time monitoring method provided by an embodiment of the present invention;

[0028] Figure 7 A schematic diagram of the structure of a logistics ultra-long single-time monitoring device provided by an embodiment of the present invention;

[0029] Figure 8 Another structural schematic diagram of the logistics ultra-long single-time monitoring device provided by an embodiment of the present invention;

[0030] Fig. 9 A schematic diagram of the structure of a logistics ultra-long single-time monitoring device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The present invention provides a method, device, equipment and storage medium for monitoring the timeliness of logistics overlong orders. The present invention collects the source of logistics orders from various business provinces regularly by presetting a time to obtain order source data, and the reference configuration time data needs to be calculated based on the routing information of each logistics order in the logistics order source and the flow time of each logistics stage. The reference configuration time data is dynamic data with a certain timeliness and can change with market changes, thereby improving the accuracy of timeliness monitoring of each stage of logistics orders; according to the preset rules to be configured and the dynamic reference configuration time data, the warning time is reasonably configured to make the warning time Long data is more accurate and closer to the actual market situation; then the actual logistics orders are combined with the warning time data to obtain unique order warning data. The order warning data is determined according to the different logistics order situations. During monitoring, the real-time duration data of each logistics stage of the logistics order is monitored through the order warning data. If the real-time duration data enters the warning range set by the order warning data, the timeout warning will be immediately fed back to the relevant distribution or relevant outlets or relevant personnel to improve the timeliness achievement rate of the overall logistics order link, effectively reducing the proportion of super-long orders in the shopping platform's assessment indicators for logistics providers, so as to improve the competitiveness of logistics companies in the market.

[0032] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the logistics ultra-long single time monitoring method in the embodiment of the present invention includes:

[0034] 101. Obtain order source data according to preset time;

[0035] In this embodiment, the logistics order sources from various business provinces are regularly collected at a preset time to obtain order source data, and the order source data collected each time will automatically overwrite the original repeated data to ensure the freshness of the order source data, making the order source data dynamic data, and making the reference configuration duration data have a certain timeliness, which can change with market changes, thereby improving the accuracy of timeliness monitoring of each stage of logistics orders.

[0036] It should be noted that the preset time can be any time period, such as 24 hours, 48 ​​hours, 72 hours, etc., and the specific time is not limited here.

[0037] 102. Extract the duration data of each logistics stage according to the order source data, and generate reference configuration duration data;

[0038] In this embodiment, the order source data contains complete routing information of historical logistics orders and the circulation time of each logistics stage. Multiple historical logistics orders are obtained through the order source data, and the average circulation time of each logistics stage is calculated according to the routing information of each logistics order and the circulation time of each logistics stage to obtain reference configuration time data. The reference configuration time data provides a more accurate time reference standard for each logistics stage to improve the monitoring effect of each logistics stage and improve the timeliness achievement rate of the overall logistics link.

[0039] It should be noted that the various logistics stages include the first distribution stage, the in-transit transportation stage, the final distribution stage, the final distribution in-transit transportation stage and the delivery stage.

[0040] 103. Perform time configuration according to the preset to-be-configured rule and the reference configuration duration data to generate warning duration data;

[0041] In this embodiment, the preset rules to be configured are the warning time ranges of each logistics stage, and the timeout time of each logistics stage is defined, such as the definition of delivery timeout: orders that have not been submitted to the distribution after more than X hours after collection; the definition of first distribution operation timeout: orders that have not been transferred out after more than X hours after arriving at the first distribution; the definition of transportation timeout: orders that have not arrived at the last distribution after more than X hours after the first distribution is issued; the definition of last distribution operation timeout: orders that have not been sent to the last outlet after more than x hours after arriving at the last distribution; the definition of last distribution to outlet timeout: orders that have not arrived at the last outlet after more than x hours after the last distribution is issued; Definition of about to time out: orders that have not been signed for at the outlets for more than x hours; the value of x needs to be configured according to the reference configuration time data. The warning time is reasonably configured through the dynamic reference configuration time data to make the warning time data more accurate and closer to the actual market situation; the warning is issued within the configured time range, and no warning is issued if the set time is exceeded. For ease of understanding, the following example is used to illustrate, such as: the pickup time is 1:00, the delivery time warning range is 2-4 hours, and the warning time is 3:00-5:00. If the arrival time of the first distribution exceeds 5:00, no warning is issued.

[0042] 104. Obtain the logistics order, and calculate the time configuration of the logistics order according to the warning duration data to obtain the order warning data;

[0043] In this embodiment, the corresponding warning time of the logistics order is configured according to the actual order time of the logistics order and combined with the warning duration data to obtain order warning data that is compatible with the logistics order. The situation of each logistics order is different, so the corresponding order warning data needs to be set separately according to different logistics orders to improve the effectiveness of timeliness monitoring.

[0044] 105. Obtain the real-time duration data of each logistics stage of the logistics order, and perform timeout monitoring on the real-time duration data based on the order warning data.

[0045] In this embodiment, the real-time duration data of each logistics stage is obtained according to the real-time routing situation of the logistics order, and the real-time duration data is monitored according to the order warning data to determine whether the real-time duration data is about to time out. If it enters the warning range set by the order warning data, a timeout warning is immediately fed back to the relevant distribution or related outlets or related personnel to improve the timeliness achievement rate of the overall logistics order link, effectively reduce the proportion of overlong orders in the shopping platform's assessment indicators for logistics providers, and improve the competitiveness of logistics companies in the market.

[0046] In the embodiment of the present invention, the sources of logistics orders from various business provinces are collected regularly by presetting a time to obtain order source data, and the reference configuration time data needs to be calculated based on the routing information of each logistics order in the logistics order source and the flow time of each logistics stage. The reference configuration time data is dynamic data with a certain timeliness, which can change with the changes in the market, so as to improve the accuracy of the timeliness monitoring of each stage of the logistics order; the warning time is reasonably configured according to the preset rules to be configured and the dynamic reference configuration time data, so that the warning time data is more accurate and close to the actual situation. Market conditions; and then the actual logistics orders are combined with the warning duration data to obtain unique order warning data. The order warning data is determined according to the different logistics order conditions. During monitoring, the real-time duration data of each logistics stage of the logistics order is monitored through the order warning data. If the real-time duration data enters the warning range set by the order warning data, a timeout warning will be immediately fed back to the relevant distribution or related outlets or related personnel to improve the timeliness achievement rate of the overall logistics order link, effectively reducing the proportion of overlong orders in the shopping platform's assessment indicators for logistics providers, so as to improve the competitiveness of logistics companies in the market.

[0047] See also Figure 2 , the second embodiment of the logistics ultra-long single time monitoring method in the embodiment of the present invention includes:

[0048] 201. The order source data includes a shopping platform type, a business province address information, and historical order data; the historical order data is classified according to the shopping platform type and the business province address information, so as to classify the historical order data of the same shopping platform type and the same business province address information, and obtain at least one reference order source data;

[0049] 202. Extract the duration data of each logistics stage according to the reference order source data, and generate reference configuration duration data;

[0050] In this embodiment, when the order source data is collected, the historical order data therein needs to be parsed, and the historical order data is classified according to the shopping platform type and business province address information to obtain reference order source data. By classifying the historical order data, the reference order source data is made more targeted and can be used separately for parameter settings of a certain business province and the corresponding shopping platform, thereby improving the adaptability of early warning parameters in the corresponding business province and the corresponding shopping platform, and effectively reducing the proportion of overlong orders in the shopping platform's assessment indicators for logistics providers, so as to improve the competitiveness of logistics companies in the market; finally, the reference order source data is further parsed to obtain the duration data of each logistics stage in the historical order data, and generate reference configuration duration data.

[0051] See also Figure 3The third embodiment of the logistics super-long single time monitoring method in the embodiment of the present invention includes:

[0052] 301. Extracting logistics routing information of each order based on the reference order source data;

[0053] In this embodiment, the reference order source data is composed of a plurality of historical order data, and the logistics routing information of each order is extracted to obtain the entire flow path of the logistics parts and the time required for each stage.

[0054] 302. Extract the delivery time data, the first distribution operation time data, the in-transit transportation time data, the last distribution operation time data, the last distribution in-transit time data and the delivery time data according to the logistics routing information;

[0055] 303. Calculate the average delivery time data, the average first distribution operation time data, the average in-transit transportation time data, the average last distribution operation time data, the average last distribution in-transit time data and the delivery time data of each logistics routing information to obtain the average delivery time data, the average first distribution operation time data, the average in-transit transportation time data, the average last distribution operation time data, the average last distribution in-transit time data and the average delivery time data;

[0056] 304. Generate reference configuration duration data based on the average delivery duration data, the average first distribution operation duration data, the average in-transit transportation duration data, the average final distribution operation duration data, the average final distribution in-transit duration data, and the average delivery duration data;

[0057] In this embodiment, the logistics routing information is parsed to divide it into five stages, namely, the delivery operation stage, the first distribution operation stage, the in-transit transportation stage, the final distribution operation stage, the final distribution in-transit stage and the delivery stage, and the average is calculated based on the duration data of each stage to obtain the average duration data of each logistics stage, namely, the average delivery duration data, the average duration data of the first distribution operation, the average duration data of in-transit transportation, the average duration data of the final distribution operation, the average duration data of the final distribution in-transit stage and the average duration data of delivery, and finally, the reference configuration duration data is generated based on the average duration data of each logistics stage.

[0058] See also Figure 4 The third embodiment of the logistics super-long single time monitoring method in the embodiment of the present invention includes:

[0059] 401. Obtain the fuzzy value of the warning duration of each logistics stage according to the preset rules to be configured;

[0060] 402. Extract the average duration value of each logistics stage according to the reference configuration duration data;

[0061] 403. Calculate the warning duration range value of the corresponding logistics stage according to the average duration value and the warning duration fuzzy value;

[0062] 404. Generate warning duration data according to each warning duration range value;

[0063] In this embodiment, a fuzzy value of the warning duration is obtained according to a preset rule to be configured, and the fuzzy value of the warning duration is the duration range value of the configuration parameter x, such as one hour before and after x, two hours before and after x, etc.; the average duration value in the reference configuration duration data is obtained as the parameter x, and combined with the fuzzy value of the warning duration to obtain the warning duration range value. Assuming that the average duration value is 24 hours and the fuzzy value of the warning duration is two hours before and after, the warning duration range value is 22 hours-26 hours.

[0064] See also Figure 5 The fourth embodiment of the logistics super-long single time monitoring method in the embodiment of the present invention includes:

[0065] 501. Obtain the logistics order, and obtain the logistics order time according to the logistics order;

[0066] 502. Estimate and calculate the warning duration range value of each logistics stage of the logistics order according to the logistics order placement time and the warning duration data;

[0067] 503. Obtain routing planning data according to the logistics order;

[0068] 504. Add the warning duration range value of each logistics stage to the route planning data to obtain order warning data.

[0069] In this embodiment, the warning time range value of each logistics stage of the logistics order is estimated according to the logistics order time of the logistics order and combined with the warning time data, the warning time data is converted with the specific time to obtain the warning time range value, and then the warning time range value is combined with the route planning data to obtain the order warning data. The order warning data can display the specific route status while displaying the warning time.

[0070] 505. Obtain the current logistics status according to the logistics order;

[0071] 506. Obtain the real-time duration data of the corresponding logistics stage according to the current logistics status;

[0072] 507. Obtain the warning duration range value of the corresponding logistics stage in the order warning data according to the current logistics status;

[0073] 508. Perform timeout monitoring on the real-time duration data according to the warning duration range value; if the real-time duration data enters the interval of the warning duration range value, generate a warning feedback;

[0074] 509. If the real-time duration data does not enter or exceeds the warning duration range, it is prohibited to generate warning feedback.

[0075] In this embodiment, an early warning is issued based on the current logistics status of the logistics order and the corresponding real-time duration data. The real-time duration data is monitored through the order early warning data to see if it enters the interval. If it enters the early warning interval, an early warning feedback is immediately sent to the relevant distribution or relevant outlets or relevant personnel to prompt the feedback party to expedite the current express delivery to avoid the logistics order flow from entering the overdue order volume.

[0076] See also Figure 6 The fourth embodiment of the logistics super-long single time monitoring method in the embodiment of the present invention includes:

[0077] 601. If the real-time duration data does not enter the warning duration range, it is prohibited to generate warning feedback;

[0078] In this embodiment, if the real-time duration data does not enter the interval, there is no need to issue an early warning to the relevant distribution or relevant outlets or relevant personnel, so the early warning feedback needs to be disabled.

[0079] 602. If the real-time duration data exceeds the interval of the warning duration range value, a reset instruction is generated and generation of warning feedback is prohibited;

[0080] 603. According to the reset instruction, the real-time scanning time of the next logistics stage is obtained, and the warning time range value of the subsequent logistics stage of the logistics order is re-estimated and calculated according to the real-time scanning time and the warning time data to obtain an updated warning time range value;

[0081] 605. Update the order warning data according to the update warning time range value;

[0082] In this embodiment, if a timeout occurs in any logistics stage of a logistics order during the monitoring process, the order warning data of the logistics order needs to be reset to avoid affecting the timeliness monitoring of subsequent logistics stages.

[0083] The above describes the logistics overlong order time monitoring method in the embodiment of the present invention. The following describes the logistics overlong order time monitoring device in the embodiment of the present invention. Figure 7 In one embodiment of the present invention, an embodiment of a logistics overlong single time monitoring device includes:

[0084] The acquisition module 701 is used to acquire order source data according to a preset time;

[0085] Extraction module 702, used to extract duration data of each logistics stage according to order source data, and generate reference configuration duration data;

[0086] Configuration module 703, used for performing time configuration according to preset rules to be configured and reference configuration duration data to generate warning duration data;

[0087] The calculation module 704 is used to obtain the logistics order and calculate the time configuration of the logistics order according to the warning duration data to obtain the order warning data;

[0088] The monitoring module 705 is used to obtain the real-time duration data of each logistics stage of the logistics order, and perform timeout monitoring on the real-time duration data according to the order warning data.

[0089] In this embodiment, a time is preset by the acquisition module 701 and the extraction module 702 to regularly collect the logistics order sources from each business province to obtain the order source data, and the reference configuration time data needs to be calculated based on the routing information of each logistics order in the logistics order source and the flow time of each logistics stage. The reference configuration time data is dynamic data with a certain timeliness and can change with the changes in the market, so as to improve the accuracy of the timeliness monitoring of each stage of the logistics order; the configuration module 703 is used to reasonably configure the warning time according to the preset rules to be configured and the dynamic reference configuration time data, so that the warning time data is more accurate and close to the actual situation. Actual market conditions; and then the calculation module 704 and the monitoring module 705 are used to combine the actual logistics orders with the warning duration data to obtain unique order warning data. The order warning data is determined according to the different logistics order conditions. During monitoring, the real-time duration data of each logistics stage of the logistics order is monitored through the order warning data. If the real-time duration data enters the warning range set by the order warning data, a timeout warning is immediately fed back to the relevant distribution or relevant outlets or relevant personnel to improve the timeliness achievement rate of the overall logistics order link, effectively reducing the proportion of super-long orders in the shopping platform's assessment indicators for logistics providers, so as to improve the competitiveness of logistics companies in the market.

[0090] See also Figure 8 Another embodiment of the logistics super-long single-time monitoring device in the embodiment of the present invention includes:

[0091] The acquisition module 701 is used to acquire order source data according to a preset time;

[0092] Extraction module 702, used to extract duration data of each logistics stage according to order source data, and generate reference configuration duration data;

[0093] Configuration module 703, used for performing time configuration according to preset rules to be configured and reference configuration duration data to generate warning duration data;

[0094] The calculation module 704 is used to obtain the logistics order and calculate the time configuration of the logistics order according to the warning duration data to obtain the order warning data;

[0095] Monitoring module 705, used to obtain real-time duration data of each logistics stage of the logistics order, and perform overtime monitoring on the real-time duration data according to the order warning data;

[0096] In this embodiment, the extraction module 702 includes: a classification unit 7021, which is used to classify the historical order data according to the shopping platform type and the business province address information, so as to classify the historical order data of the same shopping platform type and the same business province address information to obtain at least one reference order source data; an extraction unit 7022, which is used to extract the duration data of each logistics stage according to the reference order source data, and generate reference configuration duration data.

[0097] In this embodiment, the extraction unit 7022 includes: a first extraction unit 70221, which is used to extract the logistics routing information of each order according to the reference order source data; a second extraction unit 70222, which is used to extract the delivery time data, the first distribution operation time data, the in-transit transportation time data, the last distribution operation time data, the last distribution in-transit time data and the delivery time data according to the logistics routing information; a calculation unit 70223, which is used to extract the delivery time data, the first distribution operation time data, the in-transit transportation time data, the last distribution operation time data and the delivery time data according to the logistics routing information. The generation unit 70224 is used to generate reference configuration time data according to the average delivery time data, the average first distribution operation time data, the average in-transit transportation time data, the average last distribution operation time data, the average in-transit transportation time data and the average delivery time data.

[0098] In this embodiment, the configuration module 703 includes: a preset unit 7031, which is used to obtain the fuzzy value of the warning duration of each logistics stage according to the preset rules to be configured; a value obtaining unit 7032, which is used to extract the average duration value of each logistics stage according to the reference configuration duration data; a range calculation unit 7033, which is used to calculate the warning duration range value of the corresponding logistics stage according to the average duration value and the fuzzy value of the warning duration; and a generation unit 7034, which is used to generate warning duration data according to each warning duration range value.

[0099] In this embodiment, the calculation module 704 includes: a first acquisition unit 7041, used to acquire a logistics order and acquire a logistics order time according to the logistics order; an estimation unit 7042, used to estimate and calculate the warning time range value of each logistics stage of the logistics order according to the logistics order time and the warning time data; a second acquisition unit 7043, used to acquire routing planning data according to the logistics order; an adding unit 7044, used to add the warning time range value of each logistics stage to the routing planning data to obtain order warning data.

[0100] In this embodiment, the monitoring module 705 includes: a third acquisition unit 7051, which is used to obtain the current logistics status according to the logistics order; a fourth acquisition unit 7052, which is used to obtain the real-time duration data of the corresponding logistics stage according to the current logistics status; a fifth acquisition unit 7053, which is used to obtain the warning duration range value of the corresponding logistics stage in the order warning data according to the current logistics status; a feedback unit 7054, which is used to perform timeout monitoring on the real-time duration data according to the warning duration range value; if the real-time duration data enters the interval of the warning duration range value, a warning feedback is generated; a prohibition unit 7055, which is used to prohibit the generation of warning feedback if the real-time duration data has not entered or has exceeded the interval of the warning duration range value.

[0101] In this embodiment, the prohibition unit 7055 includes: a first prohibition unit 70551, which is used to prohibit the generation of warning feedback if the real-time duration data does not enter the interval of the warning duration range value; a second prohibition unit 70552, which is used to generate a reset instruction and prohibit the generation of warning feedback if the real-time duration data exceeds the interval of the warning duration range value; a reset unit 70553, which is used to obtain the real-time scanning time of the next logistics stage according to the reset instruction, and re-estimate the warning duration range value of the subsequent logistics stage of the logistics order according to the real-time scanning time and the warning duration data to obtain an updated warning duration range value; an update unit 70554, which is used to update the order warning data according to the updated warning duration range value.

[0102] above Figure 7 and Figure 8 The logistics over-long single-time monitoring device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The logistics over-long single-time monitoring device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0103] Fig. 91 is a schematic diagram of the structure of a logistics super-long single time-limit monitoring device provided by an embodiment of the present invention. The logistics super-long single time-limit monitoring device 800 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 810 (for example, one or more processors) and a memory 820, and one or more storage media 830 (for example, one or more mass storage devices) storing application programs 833 or data 832. Among them, the memory 820 and the storage medium 830 can be short-term storage or persistent storage. The program stored in the storage medium 830 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the logistics super-long single time-limit monitoring device 800. Furthermore, the processor 810 can be configured to communicate with the storage medium 830, and execute a series of instruction operations in the storage medium 830 on the logistics super-long single time-limit monitoring device 800 to implement the steps of the logistics super-long single time-limit monitoring method provided by the above-mentioned method embodiments.

[0104] The logistics overlong single time monitoring device 800 may also include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input and output interfaces 860, and / or one or more operating systems 831, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will appreciate that Fig. 9 The structure of the logistics over-long single-time monitoring equipment shown does not constitute a limitation on the logistics over-long single-time monitoring equipment, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0105] 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. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the logistics over-long single time monitoring method.

[0106] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0108] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A logistics ultra-long single-time monitoring method, characterized in that: include: Get order source data according to preset time; Extract the duration data of each logistics stage according to the order source data, and generate reference configuration duration data; Perform time configuration according to the preset rules to be configured and the reference configuration duration data to generate warning duration data; Obtain logistics orders and calculate the time configuration of logistics orders based on the warning duration data to obtain order warning data; Obtain the real-time duration data of each logistics stage of the logistics order, and perform overtime monitoring of the real-time duration data based on the order warning data; The extracting of the duration data of each logistics stage according to the order source data and generating reference configuration duration data includes: The order source data includes shopping platform type, business province address information and historical order data; Classify the historical order data according to the shopping platform type and the business province address information, so as to classify the historical order data of the same shopping platform type and the same business province address information, and obtain at least one reference order source data; Extract the duration data of each logistics stage based on the reference order source data, and generate reference configuration duration data; The extracting of the duration data of each logistics stage according to the reference order source data and generating the reference configuration duration data includes: Extract logistics routing information for each order based on reference order source data; Extract the delivery time data, first distribution operation time data, in-transit transportation time data, last distribution operation time data, last distribution in-transit time data and delivery time data according to the logistics routing information; According to the delivery time data, first distribution operation time data, in-transit transportation time data, last distribution operation time data, last distribution in-transit time data and delivery time data of each logistics routing information, the average delivery time data, first distribution operation average time data, in-transit transportation average time data, last distribution operation average time data, last distribution in-transit time data and delivery average time data are calculated; Generate reference configuration duration data based on average delivery time data, average first distribution operation time data, average in-transit transportation time data, average final distribution operation time data, average final distribution in-transit time data, and average delivery time data; The time configuration is performed according to the preset to-be-configured rule and the reference configuration duration data to generate the warning duration data, including: Obtain the fuzzy value of the warning duration for each logistics stage according to the preset rules to be configured; Extract the average duration value of each logistics stage based on the reference configuration duration data; Calculate the warning duration range value of the corresponding logistics stage according to the average duration value and the warning duration fuzzy value; Generate warning duration data according to each warning duration range value; The obtaining of the logistics order and calculating the time configuration of the logistics order according to the warning duration data to obtain the order warning data include: Obtain the logistics order, and obtain the logistics order time based on the logistics order; Estimate the warning duration range for each logistics stage of the logistics order based on the logistics order placement time and warning duration data; Obtain routing planning data based on logistics orders; The warning duration range values ​​of each logistics stage are added to the route planning data to obtain order warning data.

2. The logistics ultra-long single time monitoring method according to claim 1 is characterized in that: The real-time duration data of each logistics stage of the logistics order is obtained, and the real-time duration data is monitored overtime according to the order warning data, including: Get the current logistics status based on the logistics order; Obtain real-time duration data of the corresponding logistics stage based on the current logistics status; Obtain the warning duration range value of the corresponding logistics stage in the order warning data according to the current logistics status; Perform timeout monitoring on real-time duration data according to the warning duration range value; if the real-time duration data enters the warning duration range value interval, generate warning feedback; If the real-time duration data does not enter or exceeds the warning duration range, it is prohibited to generate warning feedback.

3. The logistics ultra-long single time monitoring method according to claim 2 is characterized in that: If the real-time duration data does not enter or exceeds the warning duration range, then the generation of warning feedback is prohibited, including: If the real-time duration data does not enter the warning duration range, it is prohibited to generate warning feedback; If the real-time duration data exceeds the warning duration range, a reset instruction is generated and the generation of warning feedback is prohibited; According to the reset instruction, the real-time scanning time of the next logistics stage is obtained, and the warning time range value of the subsequent logistics stage of the logistics order is re-estimated and calculated according to the real-time scanning time and the warning time data to obtain the updated warning time range value; The order warning data is updated according to the updated warning time range value.

4. A logistics ultra-long single-time monitoring device, characterized in that: include: The acquisition module is used to obtain order source data according to a preset time; An extraction module is used to extract the duration data of each logistics stage according to the order source data, and generate reference configuration duration data; the extraction of the duration data of each logistics stage according to the order source data, and the generation of reference configuration duration data, including: the order source data includes the shopping platform type, business provincial address information and historical order data; the historical order data is classified according to the shopping platform type and the business provincial address information to classify the historical order data of the same shopping platform type and the same business provincial address information to obtain at least one reference order source data; the duration data of each logistics stage is extracted according to the reference order source data, and the reference configuration duration data is generated; the extraction of the duration data of each logistics stage according to the reference order source data, and the generation of reference configuration duration data, including: extracting the logistics route of each order according to the reference order source data Information; extract the delivery time data, the first distribution operation time data, the in-transit transportation time data, the last distribution operation time data, the last distribution distribution in-transit time data and the delivery time data according to the logistics routing information; calculate the average delivery time data, the first distribution operation time data, the in-transit transportation time data, the last distribution operation time data, the last distribution distribution in-transit time data and the delivery time data of each logistics routing information; generate the reference configuration time data according to the average delivery time data, the first distribution operation time data, the in-transit transportation time data, the last distribution operation time data, the last distribution distribution in-transit time data and the delivery time data; A configuration module, used for performing time configuration according to preset rules to be configured and reference configuration time data to generate warning time data; said performing time configuration according to preset rules to be configured and reference configuration time data to generate warning time data, including: obtaining warning time fuzzy values ​​of each logistics stage according to preset rules to be configured; extracting average time values ​​of each logistics stage according to reference configuration time data; calculating warning time range values ​​of corresponding logistics stages according to average time value and warning time fuzzy value; generating warning time data according to each warning time range value; A calculation module is used to obtain a logistics order, and calculate the time configuration of the logistics order according to the warning duration data to obtain order warning data; the obtaining of the logistics order, and calculating the time configuration of the logistics order according to the warning duration data to obtain the order warning data, includes: obtaining the logistics order, and obtaining the logistics order time according to the logistics order; estimating and calculating the warning duration range value of each logistics stage of the logistics order according to the logistics order time and the warning duration data; obtaining the route planning data according to the logistics order; adding the warning duration range value of each logistics stage to the route planning data to obtain the order warning data; The monitoring module is used to obtain the real-time duration data of each logistics stage of the logistics order, and perform timeout monitoring on the real-time duration data based on the order warning data.

5. A logistics ultra-long single-time monitoring device, characterized in that: The logistics overlong single time monitoring device comprises: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors calls the instructions in the memory to enable the logistics over-long single time limit monitoring device to execute each step of the logistics over-long single time limit monitoring method as described in any one of claims 1-3.

6. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the logistics ultra-long single time monitoring method as described in any one of claims 1-3 are implemented.

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