Method and system for monitoring quality of service based on multi-source data

Abstract

The application discloses a service quality monitoring method and system based on multi-source data, and aims at the scene of taking out in rural and remote areas. Through interaction between the service monitoring end and the pointing station, the logistics data is monitored in real time. Based on the natural law of the trend and predictability shown by the time sequence, the warehousing time relationship of the orders represented by each node in the time sequence is used to screen out the orders that need to be focused on, that is, the second target order, so that the specified station can improve the attention degree of the second target order, reduce the risk of package loss and package not found as time goes on, supervise the quality of package delivery service, reduce the management risk of the specified station, and improve the service experience of the person taking out.

Description

Technical Field

[0001] This application relates to the field of electronic digital data processing technology, and in particular to a method for digital computing or data processing specifically applicable to a particular application, specifically a service quality monitoring method and system based on multi-source data. Background Technology

[0002] With goods readily available, and as the boundaries and depth of the consumer market continue to expand, express delivery companies have been driving the express delivery development capability index to rise steadily in recent years by continuously improving the level of intelligence at the last mile, continuously enhancing air transport support capabilities, and steadily expanding the international delivery market.

[0003] However, especially in rural areas, where transportation is limited, delivering parcels to recipients is quite difficult. In most cases, recipients will write the address as the nearest delivery station (station) in the county or town, and then pick up the parcel after it arrives at the station. Again, due to transportation limitations, recipients may not pick up their parcels for an extended period, or they may wait until a certain number of parcels have been stored before picking them up all at once. This results in a large number of parcels remaining at the station for a long time. This increases the management difficulty of the station and also poses a risk of lost parcels, making it difficult for recipients to retrieve their packages.

[0004] It is evident that how to effectively monitor the quality of delivery services in response to the issues of long package dwell times and large package backlogs has become an urgent problem to be solved.

[0005] For example, patent publication number CN211015222U, titled "A Construction Engineering Quality Supervision Service Device" (main classification number: G06F1 / 16), achieves construction engineering quality supervision services through differentiated device structure design. On the one hand, this demonstrates the significant potential of electronic digital data processing technology in quality supervision and analysis technologies; on the other hand, it also illustrates the broad prospects for technological expansion in this field. Summary of the Invention

[0006] This application provides a service quality monitoring method and system based on multi-source data to at least partially solve the above-mentioned technical problems.

[0007] The embodiments of this application adopt the following technical solutions:

[0008] In a first aspect, embodiments of this application provide a service quality monitoring method based on multi-source data, the method comprising:

[0009] The service monitoring system acquires logistics data for each order.

[0010] Based on the logistics data, a first target order is determined; the first target order is the order among the orders that needs to be delivered to a designated station; the designated station is a station with obvious delayed pickup phenomenon;

[0011] The system acquires the inbound data from the designated site. When the inbound data indicates that the first target order has been inbound, a time-series sequence is constructed for the first target order based on the inbound data before the first target order was inbound, the inbound data of the first target order, and the inbound data after the first target order was inbound. The time-series sequence contains several nodes arranged in chronological order, and each node corresponds to an order inbound at the designated site. The monitoring terminal communicates with the designated site via SSL / TLS protocol.

[0012] Obtain the outbound data of the designated site. When it is detected that a first specified number of orders other than the first target order have been outbound from the orders corresponding to the time sequence indicated by the outbound data, the first target order is taken as the second target order.

[0013] A notification message is sent to the designated site to inform it and increase its attention to the second target order.

[0014] In an optional embodiment of this specification, the method further includes:

[0015] In addition to being an order that needs to be delivered to the designated site, the first target order must also meet one of the following conditions:

[0016] The first target order corresponds to fresh produce;

[0017] The volume of the item corresponding to the first target order is less than a preset volume threshold;

[0018] The recipient of the first target order has experienced a lost package issue within a historical time period of a preset first specified time interval from the current time.

[0019] In an optional embodiment of this specification, the method further includes:

[0020] The service monitoring terminal communicates with the site, and when it detects a service registration request from the site, it registers the site as the designated site.

[0021] In an optional embodiment of this specification, the method further includes:

[0022] The service monitoring terminal continues to acquire the inbound data of the designated site. When it detects that the first target order currently inbound has a historical order with the same recipient that has not yet been shipped, it determines both the first target order currently inbound and the historical order as the second target order.

[0023] In an optional embodiment of this specification, the method further includes:

[0024] When the first target order is identified as the second target order, a unique identifier is assigned to the second target order, so that the unique identifier is different for different recipients.

[0025] In an optional embodiment of this specification, the method further includes:

[0026] The first specified quantity is less than the first specified quantity when the difference between the volume of the item corresponding to the first target order and the volume of the item corresponding to other orders in the corresponding time sequence is greater than a preset difference threshold.

[0027] In an optional embodiment of this specification, the method further includes:

[0028] The service monitoring terminal continues to acquire the inbound data of the designated site. When it detects that the number of first target orders that have stayed at the designated site for a longer than a preset second specified time exceeds a preset second specified number, it reconstructs the corresponding time sequence for the third target order to increase the number of nodes contained therein. The third target order is the third specified number of first target orders that have stayed at the designated site for a longer than the second specified time, which has the longest stay.

[0029] The second target order is determined from the third target order.

[0030] In an optional embodiment of this specification, the method further includes:

[0031] In the time sequence, the number of nodes following the node corresponding to the first target order is greater than the number of nodes preceding it.

[0032] In an optional embodiment of this specification, the method further includes:

[0033] When constructing the time series sequence, if the number of second target orders corresponding to nodes in the time series sequence of the first target order is greater than a preset quantity threshold, then the inbound data after the first target order is inbound is added when constructing the time series sequence.

[0034] Secondly, embodiments of this application also provide a service quality monitoring system based on multi-source data, the system comprising:

[0035] The service monitoring terminal is configured to acquire logistics data for each order.

[0036] Based on the logistics data, a first target order is determined; the first target order is the order among the orders that needs to be delivered to a designated station; the designated station is a station with obvious delayed pickup phenomenon;

[0037] The system acquires the inbound data from the designated site. When the inbound data indicates that the first target order has been inbound, a time-series sequence is constructed for the first target order based on the inbound data before the first target order was inbound, the inbound data of the first target order, and the inbound data after the first target order was inbound. The time-series sequence contains several nodes arranged in chronological order, and each node corresponds to an order inbound at the designated site. The monitoring terminal communicates with the designated site via SSL / TLS protocol.

[0038] Obtain the outbound data of the designated site. When it is detected that a first specified number of orders other than the first target order have been outbound from the orders corresponding to the time sequence indicated by the outbound data, the first target order is taken as the second target order.

[0039] A notification message is sent to the designated site to inform it and increase its attention to the second target order.

[0040] Thirdly, embodiments of this application also provide an electronic device, including:

[0041] Processor; and

[0042] A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the method described in the first aspect.

[0043] Fourthly, embodiments of this application also provide a computer-readable storage medium storing one or more programs that, when executed by an electronic device including multiple applications, cause the electronic device to perform the steps of the method described in the first aspect.

[0044] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects:

[0045] The method in this application targets parcel pickup scenarios in rural and remote areas. The service monitoring terminal, through interaction with designated stations, monitors logistics data in real time. Based on the trend and predictive natural laws exhibited by the time series, and by analyzing the inbound time relationships of orders represented by each node in the time series, it continuously monitors and filters out orders requiring special attention—the second target orders. This allows designated stations to increase their focus on these second target orders, reducing the risk of lost or missing packages over time. This not only supervises the quality of parcel delivery services but also reduces management risks at designated stations and improves the service experience for pickup recipients. It also realizes the application of a service quality monitoring method and system based on multi-source data in the fields of quality supervision and analysis. Attached Figure Description

[0046] Figure 1 This is a schematic diagram illustrating the process of the service quality monitoring method based on multi-source data provided in the embodiments of this specification.

[0047] Figure 2 This is a schematic diagram of the structure of an electronic device in an embodiment of this specification. Detailed Implementation

[0048] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. Similar elements in different embodiments are referred to by related similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of the present application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to the present application are not shown or described in the specification. This is to avoid obscuring the core parts of the present application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0049] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0050] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0051] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0052] like Figure 1 As shown, the service quality monitoring method based on multi-source data in this specification includes the following steps:

[0053] S100: The service monitoring terminal obtains logistics data for each order.

[0054] The service monitoring terminal in this specification has the attributes of a server, which can be a server cluster, used to monitor service quality, and is also the subject of execution of the method in this application.

[0055] All technical means that enable the collection and acquisition of logistics data are applicable to this specification, provided that conditions permit.

[0056] It is understood that, in addition to the monitoring methods described in this specification, other monitoring methods exist in related technologies, and these can be combined with the methods described in this specification when conditions permit. For example, real-time location data of freight trucks can also be acquired to monitor the smoothness of logistics.

[0057] The logistics data in this manual can contain multiple information dimensions. In this step, we will focus on obtaining the information of the shipment address dimension in the logistics data.

[0058] In the method described in this specification, the main decisions are all executed by the service monitoring terminal, which can reduce the data processing pressure on the terminal equipment of the site.

[0059] S102: Based on the logistics data, determine the first target order.

[0060] In this technology, packages undergo multi-level sorting based on their delivery address. Typically, packages destined for a city are consolidated and delivered to a central sorting station within that city. For example, city A includes the urban area and its subordinate counties B and C. Regardless of whether the delivery address is in city A, county B, or county C, the package will first be sent to city A, then sorted at city A's sorting station before being delivered to county B or county C. Packages with delivery addresses in the urban area will be delivered directly within the urban area.

[0061] County B is relatively developed with a high degree of industrialization, and parcels from County B can be delivered directly. However, County C is a rural county, mainly inhabited by farmers. It is sparsely populated and its delivery is more difficult due to limited transportation conditions. In this case, parcels can be left at a designated station (referred to as the "designated station" in this instruction manual) for the recipient to pick up themselves.

[0062] The first target order in this specification refers to the order that needs to be delivered to a designated station. This designated station is one where delayed pickup is a significant issue; in the aforementioned example, it is the station in county C. Therefore, the first target order in this specification is an order that is anticipated (although the package corresponding to this order may not yet have been picked up by the logistics company, and the sender has only filled in the delivery address) and is likely to be lost or delayed. In other words, the method in this specification can predict the future delivery status and pickup situation of packages based on the delivery address, demonstrating its predictive and timely beneficial effects.

[0063] In some cases, certain delivery stations are relatively convenient (e.g., stations in the urban area of ​​City A). To improve service quality and reduce their own management burden, station administrators can register these stations as designated stations in this specification, even if occasional delays in package pickup occur, to utilize the service quality monitoring methods described herein. In an optional embodiment, the service monitoring terminal communicates with the station and, upon detecting a service registration request from the station, registers the station as a designated station.

[0064] The service monitoring terminal described in this manual can communicate with multiple designated sites. This manual will only use one of these designated sites as an example for explanation.

[0065] S104: Obtain the inbound data of the designated site. When the inbound data indicates that the first target order has been inbound, construct a time sequence for the first target order based on the inbound data before the first target order is inbound, the inbound data of the first target order, and the inbound data after the first target order is inbound.

[0066] The warehousing operation described in this manual is performed by a designated site. This site may be equipped with terminal devices, which interact with the service monitoring terminal via a network to transmit data. The interaction between the terminal devices and the service monitoring terminal may use the SSL / TLS protocol. Any related technologies that enable this interaction are applicable to this manual, where conditions permit. For example, the data collected when the site administrator scans the package for warehousing is the warehousing data, indicating that the package has arrived at the site and the time of arrival.

[0067] SSL / TLS (Secure Sockets Layer / Transport Layer Security) is widely used in HTTPS, email protocols, and other protocols to ensure data security during transmission. It operates at the application layer, establishing an encrypted connection through a handshake process between the client and server. It is primarily used for secure communication between web browsers and servers, ensuring the confidentiality, integrity, and authentication of data transmission. For example, HTTPS is used for secure web page transmission, and the secure versions of IMAP and POP3, IMAPS and POP3S, are used for email services.

[0068] Both SSL / TLS and SSH use Public Key Infrastructure (PKI) for key management and authentication, ensuring the authenticity and reliability of the identities of both communicating parties. SSL / TLS is typically used in public network environments, while SSH is more often used in local networks or environments requiring high security.

[0069] The time sequence described in this specification can be used to some extent to characterize the timing of package pickup under ideal conditions, without pickup or delivery obstacles. In other words, ideally, packages within the same time sequence should all have been picked up within a certain period (e.g., 3 days). However, in reality, especially at designated stations, this ideal state is difficult to achieve. The technical means described in this specification are designed to address this "non-ideal" situation.

[0070] The time sequence in this specification contains several nodes arranged chronologically, each node corresponding to an order received at a designated site. For example, if a designated site receives six packages for a first target order, then a separate time sequence needs to be constructed for each of these six first target orders. Typically, when a site receives packages, it follows a chronological order without further sorting; that is, the time sequence reflects the concentration of the ideal pickup order for the packages.

[0071] The natural patterns exhibited by time series mainly include trends, seasonality, periodicity, and randomness. These patterns collectively constitute the core framework of time series analysis. Trends: Data shows a long-term, gradually increasing or decreasing directional change, reflecting potential development trends. For example, economic indicators grow steadily over time. Seasonality: Data exhibits recurring, regular fluctuations within fixed periods (such as years, months, and weeks). For example, annual temperature variations or peak sales of down jackets in winter. Periodicity: Fluctuations in data caused by non-fixed-period factors (such as economic cycles), lasting for a long time and exhibiting weak regularity. For example, the business cycle of a market economy. Randomness: Noise that cannot be explained by trends, seasonality, or periodicity, caused by accidental factors. For example, the impact of sudden events on stock prices.

[0072] Time series analysis is widely used in economic, business, and social research, primarily for indicator forecasting and dynamic characteristic analysis. For example: economic indicator forecasting: predicting future economic growth trends by analyzing historical economic data; business sales forecasting: predicting future sales of a product based on historical sales data; social problem research: analyzing the dynamic characteristics of social phenomena such as population changes and disease transmission.

[0073] In some cases, a designated site may have fewer packages arriving on a given day. In such cases, the time series constructed for packages arriving that day may include packages arriving from the previous day or several days prior. Ideally, the pickup times of these previously recorded packages should differ from the pickup times of packages arriving on the current day, leading to a deviation in the regularity representation of the time series. To address this issue, in an optional embodiment of this specification, when constructing the time series, the number of nodes following the node corresponding to the first target order should be greater than the number of nodes preceding it. This improves the time series' ability to represent temporal order and reduces the negative impact of historical backlogged orders. However, there are special cases. For example, the time series constructed for the last order arriving on a given day may contain nodes at the end of the time series. In such cases, these orders can be tagged, and the time series constructed for them marked as incomplete. The time series can then be supplemented when orders arrive on the next day.

[0074] Furthermore, in a further optional embodiment, when constructing the time series sequence, if the number of second target orders corresponding to nodes in the time series sequence of the first target order (in some cases, some first target orders can be identified as second target orders even without a time series sequence, these cases will be explained later) is greater than a preset quantity threshold (which can be an empirical value, such as half. It is usually related to the order processing capacity of the specified site; the higher the order processing capacity of the specified site, the higher the quantity threshold), then the data entered into the warehouse after the first target order is entered into the warehouse when constructing the time series sequence is increased to increase the number of subsequent nodes, thereby improving the ability of the time series sequence to represent the temporal sequence.

[0075] The number of nodes in the time series can be adjusted based on experience, and administrators of designated sites can also set it through interaction between terminal devices and the service monitoring terminal. More nodes result in lower sensitivity, while fewer nodes result in higher sensitivity.

[0076] S106: Obtain the outbound data of the designated site. When it is detected that, among the orders corresponding to the time sequence indicated by the outbound data, a first specified number of orders other than the first target order have been outbound, the first target order is taken as the second target order.

[0077] The outbound data in this specification is used to at least identify which packages have been shipped. Although all orders dispatched at designated stations are referred to as "first target orders" in this specification, in this step, "first target order" refers to one specific first target order. According to the logic of constructing time series sequences, orders corresponding to the same time series should have similar inbound times; ideally, their outbound events should also be similar. However, if other orders in this time series have been shipped out successively, but the first target order has not, based on the aforementioned natural laws of time series sequences, it is clear that this first target order has a higher risk of being delayed. The second target order in this specification represents this type of order with higher risk.

[0078] The negative impacts of delayed packages are numerous. For example, they may become difficult to find because they are covered by other packages and left unattended; or they may be damaged by other packages due to prolonged neglect, resulting in losses; and in severe cases, they may be lost altogether. These phenomena will all affect service quality to varying degrees.

[0079] In an optional embodiment of this specification, the first specified quantity can be an empirical value. A larger value for the first specified quantity indicates less sensitivity; a smaller value indicates greater sensitivity. Optionally, the first specified quantity used when the difference between the volume of the item corresponding to the first target order and the volume of the items corresponding to other orders in its corresponding time series is greater than a preset difference threshold (empirical value) is less than the first specified quantity used when the difference between the volume of the item corresponding to the first target order and the volume of the items corresponding to other orders in its corresponding time series is not greater than the difference threshold. A larger volume difference indicates that the smaller item is more easily covered by other packages, thus requiring increased sensitivity to improve attention to small-volume packages.

[0080] In some cases, there may be an overconcentration of backlogged packages, which can overwhelm the temporal characteristics represented by the time-series sequence, causing some orders that should be monitored to go unnoticed. To address this issue, in an optional embodiment of this specification, the service monitoring terminal continues to acquire the inbound data of the designated site. When it detects that the number of first target orders whose dwell time at the designated site exceeds a preset second specified time (which can be an empirical value) exceeds a preset second specified number (which can be an empirical value, indicating that the designated site is experiencing a severe backlog of orders that cannot be shipped), the time-series sequence corresponding to the third target order is reconstructed to increase the number of nodes included. The added nodes correspond to orders that entered the warehouse after the inbound time of the third target order. The third target order is the third specified number (which can be an empirical value) of first target orders whose dwell time at the designated site exceeds the preset second specified time. From the third target orders, the second target order is determined. For historical orders with long backlogs, if there is a clustering of inbound times, the orders used when updating the time series are determined according to their chronological order, regardless of whether the orders corresponding to the added nodes have been shipped. This allows nodes corresponding to some orders that have already been shipped to be added to the time series, which helps improve sensitivity. It should be noted that the technical means of determining the second target order in this embodiment does not conflict with the aforementioned technical means of determining the second target order; the two are parallel.

[0081] S108: Send a prompt message to the designated site to inform the designated site to increase its attention to the second target order.

[0082] After identifying the second target order, the service monitoring terminal can add relevant identification information to the notification message and send it to the terminal device. The terminal device will then display the notification message to the administrator of the designated site. In an optional embodiment, the notification message may also include processing suggestions for the second target order, such as placing the second target order in a specific location at the designated site to avoid loss or damage.

[0083] The method in this application targets parcel pickup scenarios in rural and remote areas. The service monitoring terminal, through interaction with designated stations, monitors logistics data in real time. Based on the trend and predictive natural laws exhibited by the time series, and by analyzing the inbound time relationships of orders represented by each node in the time series, it continuously monitors and filters out orders requiring special attention—the second target orders. This allows designated stations to increase their focus on these second target orders, reducing the risk of lost or missing packages over time. This not only supervises the quality of parcel delivery services but also reduces management risks at designated stations and improves the service experience for pickup recipients. It also realizes the application of a service quality monitoring method and system based on multi-source data in the fields of quality supervision and analysis.

[0084] In the order delivery scenario described in this manual, the recipients are relatively dispersed, which may result in a large backlog of orders at designated stations. Monitoring all orders at designated stations could put significant pressure on the data processing of the service monitoring system or on the workload of the administrators at those stations.

[0085] In order to reduce the burden on both ends of the interaction while ensuring the effectiveness of service quality supervision, in an optional embodiment of this specification, the first target order, in addition to being an order that needs to be delivered to the designated station, must also meet one of the following conditions:

[0086] Condition 1: The item corresponding to the first target order is fresh produce. Fresh produce has a short shelf life, and its spoilage may contaminate other packages; therefore, this should be taken into consideration.

[0087] Condition 2: The volume of the item corresponding to the first target order is less than the volume threshold (empirical value). Data for determining the package volume can be obtained from logistics data. When a logistics company receives a package, it undergoes weighing and other processing, and relevant logistics regulations in my country require senders to clearly identify the items inside the package. Even if there is no image information of the package in the logistics data, the volume can be roughly estimated using the aforementioned package information. Related technologies capable of estimating package volume are applicable to this specification when conditions permit. Smaller packages are more prone to loss and should be given special attention.

[0088] Condition 3: The recipient of the first target order has experienced a lost package issue within a historical time period of a preset first specified time (experience value) from the current time. The user experience of the recipient is also one of the aspects that this application needs to consider. If a lost package issue has occurred in a more recent historical time, then the recipient may still be in a relatively sensitive state, and their emotions should be taken into account, with special attention paid to their package.

[0089] Since the recipients of packages picked up at designated stations are mostly those who have difficulty picking up their packages, the problem of long package backlog times cannot be ignored. If multiple packages for the same recipient are backlogged and their locations at the designated station are too scattered, it will affect the efficiency of subsequent pickups and thus the service quality. Therefore, in an optional embodiment of this specification, the service monitoring terminal continues to acquire the inbound data of the designated station. When it detects that the currently inbound first target order has a historical order with the same recipient that has not yet been shipped (the historically inbound first target order), both the currently inbound first target order and the historical order are identified as the second target order, so as to prompt the management personnel of the designated station to place the packages of the same recipient in one place. To facilitate pickup by the recipient, when the first target order is identified as the second target order, a unique identifier is assigned to the second target order; different recipients correspond to different unique identifiers. It should be noted that the technical means of determining the second target order in this embodiment does not conflict with the aforementioned technical means of determining the second target order; the two are parallel.

[0090] Furthermore, this specification also provides a service quality monitoring system based on multi-source data, the system comprising:

[0091] The service monitoring terminal is configured to acquire logistics data for each order.

[0092] Based on the logistics data, a first target order is determined; the first target order is the order among the orders that needs to be delivered to a designated station; the designated station is a station with obvious delayed pickup phenomenon;

[0093] The system acquires the inbound data from the designated site. When the inbound data indicates that the first target order has been inbound, a time-series sequence is constructed for the first target order based on the inbound data before the first target order was inbound, the inbound data of the first target order, and the inbound data after the first target order was inbound. The time-series sequence contains several nodes arranged in chronological order, and each node corresponds to an order inbound at the designated site. The monitoring terminal communicates with the designated site via SSL / TLS protocol.

[0094] Obtain the outbound data of the designated site. When it is detected that a first specified number of orders other than the first target order have been outbound from the orders corresponding to the time sequence indicated by the outbound data, the first target order is taken as the second target order.

[0095] A notification message is sent to the designated site to inform it and increase its attention to the second target order.

[0096] The system can execute the methods in any of the foregoing embodiments and achieve the same or similar technical effects, which will not be elaborated here.

[0097] Figure 2 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Please refer to it. Figure 2 At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for other business operations.

[0098] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 2 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0099] Memory is used to store programs. Specifically, programs may include program code, which includes computer operation instructions. Memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0100] The processor reads the corresponding computer program from non-volatile memory into main memory and then runs it, forming a service quality monitoring system based on multi-source data at the logical level. The processor executes the program stored in memory and specifically performs any of the aforementioned service quality monitoring methods based on multi-source data.

[0101] The above is as stated in this application. Figure 1The service quality monitoring method based on multi-source data disclosed in the illustrated embodiments can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0102] The electronic device can also perform Figure 1 A service quality monitoring method based on multi-source data was developed and implemented. Figure 1 The functions of the embodiments shown are not described in detail here.

[0103] This application also proposes a computer-readable storage medium that stores one or more programs, the programs including instructions that, when executed by an electronic device including multiple applications, perform any of the aforementioned service quality monitoring methods based on multi-source data.

[0104] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0106] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0107] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0108] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0109] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0110] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0111] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0112] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0113] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A service quality monitoring method based on multi-source data, characterized in that, The method includes: The service monitoring system acquires logistics data for each order. Based on the logistics data, a first target order is determined; the first target order is the order among the orders that needs to be delivered to a designated station; the designated station is a station with obvious delayed pickup phenomenon; The system acquires the inbound data from the designated site. When the inbound data indicates that the first target order has been inbound, a time-series sequence is constructed for the first target order based on the inbound data before the first target order was inbound, the inbound data of the first target order, and the inbound data after the first target order was inbound. The time-series sequence contains several nodes arranged in chronological order, and each node corresponds to an order inbound at the designated site. The monitoring terminal communicates with the designated site via SSL / TLS protocol. Obtain the outbound data of the designated site. When it is detected that a first specified number of orders other than the first target order have been outbound from the orders corresponding to the time sequence indicated by the outbound data, the first target order is taken as the second target order. A notification message is sent to the designated site to inform it and increase its attention to the second target order; The service monitoring terminal continues to acquire the inbound data of the designated site. When it detects that the number of first target orders that have stayed at the designated site for a longer than a preset second specified time exceeds a preset second specified number, it reconstructs the corresponding time sequence for the third target order to increase the number of nodes contained therein. The third target order is the third specified number of first target orders that have stayed at the designated site for a longer than the second specified time, which has the longest stay. The second target order is determined from the third target order.

2. The method as described in claim 1, characterized in that, The method further includes: In addition to being an order that needs to be delivered to the designated site, the first target order must also meet one of the following conditions: The first target order corresponds to fresh produce; The volume of the item corresponding to the first target order is less than a preset volume threshold; The recipient of the first target order has experienced a lost package issue within a historical time period of a preset first specified time interval from the current time.

3. The method as described in claim 1, characterized in that, The method further includes: The service monitoring terminal communicates with the site, and when it detects a service registration request from the site, it registers the site as the designated site.

4. The method as described in claim 1, characterized in that, The method further includes: The service monitoring terminal continues to acquire the inbound data of the designated site. When it detects that the first target order currently inbound has a historical order with the same recipient that has not yet been shipped, it determines both the first target order currently inbound and the historical order as the second target order.

5. The method as described in claim 4, characterized in that, The method further includes: When the first target order is identified as the second target order, a unique identifier is assigned to the second target order, so that the unique identifier is different for different recipients.

6. The method as described in claim 1, characterized in that, The method further includes: The first specified quantity is less than the first specified quantity when the difference between the volume of the item corresponding to the first target order and the volume of the item corresponding to other orders in the corresponding time sequence is greater than a preset difference threshold.

7. The method as described in claim 1, characterized in that, The method further includes: In the time sequence, the number of nodes following the node corresponding to the first target order is greater than the number of nodes preceding it.

8. The method as described in claim 4, characterized in that, The method further includes: When constructing the time series sequence, if the number of second target orders corresponding to nodes in the time series sequence of the first target order is greater than a preset quantity threshold, then the inbound data after the first target order is inbound is added when constructing the time series sequence.

9. A service quality monitoring system based on multi-source data, characterized in that, The system includes: The service monitoring terminal is configured to acquire logistics data for each order. Based on the logistics data, a first target order is determined; the first target order is the order among the orders that needs to be delivered to a designated station; the designated station is a station with obvious delayed pickup phenomenon; The system acquires the inbound data from the designated site. When the inbound data indicates that the first target order has been inbound, a time-series sequence is constructed for the first target order based on the inbound data before the first target order was inbound, the inbound data of the first target order, and the inbound data after the first target order was inbound. The time-series sequence contains several nodes arranged in chronological order, and each node corresponds to an order inbound at the designated site. The monitoring terminal communicates with the designated site via SSL / TLS protocol. Obtain the outbound data of the designated site. When it is detected that a first specified number of orders other than the first target order have been outbound from the orders corresponding to the time sequence indicated by the outbound data, the first target order is taken as the second target order. A notification message is sent to the designated site to inform it and increase its attention to the second target order; The service monitoring terminal continues to acquire the inbound data of the designated site. When it detects that the number of first target orders that have stayed at the designated site for a longer than a preset second specified time exceeds a preset second specified number, it reconstructs the corresponding time sequence for the third target order to increase the number of nodes contained therein. The third target order is the third specified number of first target orders that have stayed at the designated site for a longer than the second specified time, which has the longest stay. The second target order is determined from the third target order.

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