Data processing method and device

Abstract

An embodiment of the present application provides a data processing method and device, the method comprising: determining at least one data batch based on the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location. Determine a first time range for the data batch to reach the first target geographical location based on the starting geographical location and the first target geographical location. Push the data in the data batch that belongs to the first target geographical location to the target terminal, so that the target terminal reaches the first target geographical location within the first time range to obtain the data. By dividing the data to be processed into batches, then determining the first time range for the data batch to reach the first target geographical location, and then pushing the data corresponding to the first target geographical location to the target terminal, it is ensured that both the target terminal and the data batch reach the first target geographical location within the first time range, thereby effectively improving the efficiency of data processing.

Description

Technical Field

[0001] The embodiments of the present application relate to computer technology, and more particularly to a data processing method and device. Background Art

[0002] With the development of driverless technology, driverless cars are playing an increasingly important role in data processing scenarios.

[0003] At present, in the process of data processing, usually the unmanned vehicle can first deliver the goods corresponding to the data from the store to the docking point, and then the staff will go to the nearby docking point to pick up the goods corresponding to the data and deliver them to the user. However, because the working efficiency of the unmanned vehicle cannot be guaranteed to match the working efficiency of the staff, there may be a situation where the car waits for people, or people wait for the car.

[0004] Therefore, in the implementation method of the prior art, there is a problem of low efficiency of data processing due to mismatch in work efficiency. Summary of the invention

[0005] The embodiments of the present application provide a data processing method and device to overcome the problem of low efficiency of data processing.

[0006] In a first aspect, an embodiment of the present application provides a data processing method, including:

[0007] Determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location;

[0008] Determining, according to the starting geographical location and a first target geographical location among the target geographical locations, a first time range for the data batch to arrive at the first target geographical location;

[0009] The data belonging to the first target geographical location in the data batch is pushed to the target terminal, so that the target terminal reaches the first target geographical location within the first time range to obtain the data.

[0010] In a second aspect, an embodiment of the present application provides a data processing device, including:

[0011] A determination module, configured to determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location;

[0012] The determination module is further configured to determine a first time range for the data batch to arrive at a first target geographical location according to the starting geographical location and a first target geographical location among the target geographical locations;

[0013] The processing module is used to push the data belonging to the first target geographical location in the data batch to the target terminal, so that the target terminal reaches the first target geographical location within the first time range to obtain the data.

[0014] In a third aspect, an embodiment of the present application provides a data processing device, including:

[0015] Memory, used to store programs;

[0016] A processor is used to execute the program stored in the memory. When the program is executed, the processor is used to execute the method described in the first aspect above.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enables the computer to execute the method described in the first aspect above.

[0018] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method described in the first aspect above.

[0019] An embodiment of the present application provides a data processing method and device, the method comprising: determining at least one data batch based on the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location. Determine a first time range for the data batch to reach the first target geographical location based on the starting geographical location and the first target geographical location among the target geographical locations. Push the data belonging to the first target geographical location in the data batch to the target terminal, so that the target terminal reaches the first target geographical location within the first time range to obtain the data. By dividing the data to be processed into batches, a data batch is the data included in the processing process at one time, and then the first time range for the data batch to reach its corresponding first target geographical location can be determined for each data batch, and then the data corresponding to the first target geographical location can be pushed to the target terminal to ensure that both the target terminal and the data batch can reach the first target geographical location within the first time range, thereby effectively improving the speed and efficiency of data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0021] Figure 1A schematic diagram of a data processing scenario provided in an embodiment of the present application;

[0022] Figure 2 A flowchart of a data processing method provided in an embodiment of the present application;

[0023] Figure 3 The process of the data processing method provided in the embodiment of the present application Figure 2 ;

[0024] Figure 4 A schematic diagram of a driving route provided in an embodiment of the present application;

[0025] Figure 5 A schematic diagram of an implementation of determining a first estimated arrival time provided in an embodiment of the present application;

[0026] Figure 6 A schematic diagram of an implementation of determining a first time range provided in an embodiment of the present application;

[0027] Figure 7 A schematic diagram of an implementation of determining a terminal within a preset range provided in an embodiment of the present application;

[0028] Figure 8 The process of the data processing method provided in the embodiment of the present application Figure 3 ;

[0029] Fig. 9 A schematic diagram of implementing the division of sub-distribution ranges provided in an embodiment of the present application;

[0030] Fig.10 A schematic diagram of the implementation of the processing scope provided in the embodiment of the present application;

[0031] Fig.11 A schematic diagram of an implementation of determining data batches provided in an embodiment of the present application;

[0032] Fig.12 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application;

[0033] Fig.13 A schematic diagram of the hardware structure of a data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] In order to better understand the technical solution of the present application, the relevant technologies involved in the present application are firstly introduced in further detail.

[0036] With the continuous development of driverless technology, current driverless cars play a big role in data processing scenarios. The data here can be orders, or other data. Currently, the technical background of this part is introduced based on the data being orders.

[0037] For example, you can combine Figure 1 Understand the scenarios in which unmanned vehicles process data. Figure 1 A schematic diagram of a data processing scenario provided in an embodiment of the present application.

[0038] like Figure 1 As shown in the figure, the ordered goods that need to be processed are usually placed in the store, and the unmanned vehicle carrying the goods can start from the store and transport the goods to the docking point first. The docking point can also be understood as a docking point, which is the place where the unmanned vehicle and the staff obtain and hand over the goods.

[0039] After that, for example, a staff member can go to the stop, pick up the goods from the unmanned vehicle, and then deliver the goods to the order address corresponding to the order, which can be a residential area, so as to realize the delivery of the goods. The implementation method of unmanned vehicles participating in the delivery can avoid the need for staff to frequently return to the store to pick up the goods, thereby improving the efficiency of order processing.

[0040] In the delivery scenario described above, a complete order processing process requires the cooperation of unmanned vehicles and staff. In the prior art, unmanned vehicles usually transport the ordered goods to a docking point near the order address according to the order address, and then the staff will go to the nearby docking point to pick up the ordered goods. However, because the working efficiency of the unmanned vehicle and the working efficiency of the staff cannot be guaranteed to match, there may be a situation where the car waits for people, or people wait for the car. Therefore, this mismatch in work efficiency in the prior art will lead to a decrease in the efficiency of goods delivery.

[0041] In response to the problems in the prior art, the present application proposes the following technical concept: by dividing the data into batches, and then for each data batch, the estimated arrival time period of the data batch at the stop point is estimated, and the surrounding terminals are promptly notified to obtain data at the designated stop point during the corresponding time period, thereby effectively realizing the coordinated scheduling of data and terminals, avoiding the situation of waiting for each other, and improving data processing efficiency.

[0042] The data processing method provided by the present application is introduced below in conjunction with specific embodiments. It should be noted first that the execution subject of each embodiment in the present application can be a server, processor, chip, and other devices with data processing functions. In the actual implementation process, the specific implementation of the execution subject can be selected according to actual needs. The present application does not impose any restrictions on this. Any device with data processing functions can be used as the execution subject of each embodiment in the present application.

[0043] Let's first combine Figure 2 Make an introduction, Figure 2 A flowchart of a data processing method provided in an embodiment of the present application.

[0044] like Figure 2 As shown, the method includes:

[0045] S201. Determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location.

[0046] In this embodiment, the data to be processed can be obtained first. The data to be processed here can be understood as the orders to be delivered introduced above. In a possible implementation method, the data to be processed can be, for example, data that needs to be processed within a target period, such as data to be processed from 0:00 to 24:00 today, such as data generated yesterday, which need to be processed today. These data to be processed can be in any order and only need to be processed today.

[0047] Alternatively, all data that has not yet been processed can be used as data to be processed. This embodiment does not limit the specific implementation of the data to be processed, and it can be implemented according to actual needs.

[0048] In this embodiment, the data to be processed can be divided into batches to determine at least one data batch. A data batch can be understood as a collection of orders that need to be transported in a delivery vehicle's trip. Each data batch includes at least one data to be processed, and each data batch in this embodiment corresponds to a starting geographical location and at least one target geographical location.

[0049] It is understandable that the processing of the data batch in this embodiment is actually to complete the delivery of the goods corresponding to the data batch, so the starting geographical location is the place where the goods corresponding to the data batch are first stored. The starting geographical location can be understood as a store, for example, a store can be processed as a unit, and for each store, the data to be processed of the current store is obtained, and then the data processing operation is performed for each store.

[0050] And, the target geographic location is the destination to which the delivery vehicle needs to transport the goods in the data batch. A data batch may include data corresponding to multiple target geographic locations, so each data batch corresponds to at least one target geographic location.

[0051] In a possible implementation, the target geographic location can be understood as a docking point, where the docking point is the location where the delivery vehicle and the staff complete the handover of the goods.

[0052] S202: Determine a first time range for a data batch to arrive at the first target geographical location according to the starting geographical location and a first target geographical location among the target geographical locations.

[0053] After determining at least one data batch, multiple data batches can be processed separately. The specific processing process can be understood as transporting the goods in the data batches to their respective corresponding target geographical locations.

[0054] In a possible implementation, for example, a delivery vehicle may carry the data batches to transport the data batches from the starting geographic location to each target geographic location, wherein for each target geographic location, a time range for the data batch to arrive at the target geographic location may be determined. The specific transportation method of the data batches may be selected according to actual needs, and this embodiment does not limit this.

[0055] Therefore, the first time range for the data batch to arrive at the first target geographical location can be determined according to the starting geographical location and the first target geographical location. In the actual implementation process, this process can be performed for each target geographical location respectively, so as to determine the time range corresponding to each first target geographical location.

[0056] S203: Push the data belonging to the first target geographical location in the data batch to the target terminal, so that the target terminal reaches the first target geographical location within a first time range to obtain the data.

[0057] A data batch may include multiple data, each of which belongs to its own target geographic location. The term "belonging" here means that the data needs to be transported to the target geographic location.

[0058] In this embodiment, data belonging to the first target geographical location may be determined in the data batch, and then this part of data may be pushed to the target terminal at the first target geographical location.

[0059] The data batch will arrive at the first target geographical location within a first time range. In order to ensure that the data is processed as quickly as possible, the target terminal is also required to arrive at the first target geographical location within the first time range to obtain the data.

[0060] In a possible implementation, after the target terminal obtains the data, subsequent processing of the data may be completed until the data processing is completed. For example, when the data to be processed is an order to be delivered, the subsequent processing here may be to deliver the goods from the docking point to the designated location corresponding to the order address.

[0061] The data processing method provided by the embodiment of the present application includes: determining at least one data batch based on the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location. Determine the first time range for the data batch to reach the first target geographical location based on the starting geographical location and the first target geographical location among the target geographical locations. Push the data belonging to the first target geographical location in the data batch to the target terminal, so that the target terminal reaches the first target geographical location within the first time range to obtain the data. By dividing the data to be processed into batches, a data batch includes the data in the processing process at one time, and then the first time range for the data batch to reach its corresponding first target geographical location can be determined for each data batch, and then the data corresponding to the first target geographical location can be pushed to the target terminal to ensure that both the target terminal and the data batch can reach the first target geographical location within the first time range, thereby effectively improving the speed and efficiency of data processing.

[0062] Based on the above introduction, the following Figures 3 to 7 The data processing method provided in this application is further introduced in detail. Figure 3 The process of the data processing method provided in the embodiment of the present application Figure 2 , Figure 4 A schematic diagram of a driving route provided in an embodiment of the present application, Figure 5 A schematic diagram of an implementation of determining a first estimated arrival time provided in an embodiment of the present application, Figure 6 A schematic diagram of an implementation of determining a first time range provided in an embodiment of the present application, Figure 7 A schematic diagram of an implementation of determining terminals within a preset range provided in an embodiment of the present application.

[0063] like Figure 3 As shown, the method includes:

[0064] S301. Determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location.

[0065] The implementation of S301 is similar to that of S201 and will not be described in detail here.

[0066] S302: Determine a first time range for a data batch to arrive at the first target geographical location according to the starting geographical location and a first target geographical location among the target geographical locations.

[0067] In this embodiment, determining the first time range for a data batch to arrive at a first target geographic location is further introduced in detail.

[0068] It is understandable that the data batch will be transported from the starting geographical location and pass through each target geographical location. At each target geographical location, the data belonging to the target geographical location will be handed over to the target terminal, and the processing of the data batch will be finally completed. Therefore, in a possible implementation, the route of the data batch starting from the starting geographical location and passing through each target geographical location can be determined.

[0069] For example, you can combine Figure 4 To understand, such as Figure 4 As shown, assuming that for a data batch, there is Figure 4 Target location 1, target location, target location 3, and Figure 4 The starting geographical location is also indicated in FIG. The route can be planned based on the starting geographical location, target geographical location 1, target geographical location 2, and target geographical location 3, thereby obtaining Figure 4 Driving route shown.

[0070] In one possible implementation, for example, data batches may be transported by delivery vehicles, wherein after passing through each target geographic location and transporting the data of each target geographic location to each target geographic location in turn, the delivery vehicle needs to return to the starting geographic location to continue transporting the data batches.

[0071] Therefore, in a possible implementation, the driving route here may be the driving route of the delivery vehicle, wherein the driving route may include an outbound route from the starting geographical location to each target geographical location, and may also include a return route from the last target geographical location back to the starting geographical location. The outbound route and the return route may be the same route, that is, the delivery vehicle may return to the starting geographical location along the original route. Alternatively, the outbound route and the return route may not be the same route, that is, the outbound route and the return route may be planned independently.

[0072] In the actual implementation process, for example, a vehicle routing problem (VRP) algorithm can be used to implement travel route planning, or an adaptive large neighborhood search algorithm (ALNS) can be used to implement driving route planning, wherein the specific implementation of driving route planning can be selected and set according to actual needs, and this embodiment does not impose any restrictions on this, as long as the route planning is performed based on the starting geographical location and each target geographical location.

[0073] After the driving route is determined, the driving route may be sent to a delivery vehicle, for example, so that the delivery vehicle transports the data batches according to the driving route.

[0074] It is also necessary to further explain here that each data batch in this embodiment is processed in sequence, and when the delivery vehicle starts to transport the data batch from the starting geographical location, the staff is required to place the goods of the next batch of data batches on the delivery vehicle. In a possible implementation, the data batches can be placed in the starting geographical location in batches, and then each time a delivery vehicle comes back, the staff will place the goods of the next batch of data batches in this delivery vehicle. For example, the delivery vehicle can scan the corresponding information to identify the information of the current data batch, and then the delivery vehicle transports the data batch according to the driving route corresponding to this data batch.

[0075] In one possible implementation, when the delivery vehicle returns, for example, an indication message may be sent to the staff's terminal device to indicate that the current delivery vehicle has returned, so as to notify the staff to be prepared and place the next batch of goods in the delivery vehicle in a timely manner.

[0076] After route planning is performed, the driving time from the starting geographical location to the first target geographical location among the target geographical locations in the current driving route may be determined, wherein the first target geographical location may be any target geographical location.

[0077] For example, you can combine Figure 4 For example, for the target geographic location 1, it can be determined that the delivery vehicle is along Figure 4 The driving route shown in Figure 1 shows the driving time from the starting location to the target location 1. Similarly, for the target location 2, it can be determined that the delivery vehicle takes Figure 4 The driving route shown is the driving time from the starting geographical location to the target geographical location 2. The same is true for the target geographical location 3.

[0078] In a possible implementation, for example, a driving duration model may be trained based on multiple driving data of historical periods, wherein the driving data may include, for example, driving tracks, driving duration, and driving events, and driving events may include, for example, abnormal situations such as traffic jams, road closures, and calls for manual intervention.

[0079] Then, when the driving time needs to be determined, for example, the starting geographic location and the first target geographic location can be input into the trained driving time model to obtain the driving time from the starting geographic location to the first target geographic location.

[0080] Or in another possible implementation, the average driving time from the starting geographical location to each target geographical location and the average driving time between each target geographical location may be pre-calculated based on the driving data of multiple delivery vehicles in the historical period. Then, for example, the driving time from the starting geographical location to the first target geographical location may be determined by adding the pre-calculated average values.

[0081] After determining the driving time from the starting geographic location to the first target geographic location, the time corresponding to the driving time after the departure time corresponding to the data batch can be determined as the first estimated arrival time corresponding to the first target geographic location. The departure time corresponding to the data batch is the time when it leaves the starting geographic location.

[0082] For example, you can refer to Figure 5 Understanding, such as Figure 5 As shown, for example, the departure time t1 corresponding to the data batch can be determined first, and then the time t2 corresponding to the driving time after the departure time t1 can be determined as the first estimated arrival time corresponding to the current first target geographic location.

[0083] Afterwards, a first time range corresponding to the first target geographic location may be determined according to the first estimated arrival time of the first target geographic location.

[0084] It is understandable that after determining the first preset arrival time, the target terminal can be notified to arrive at the corresponding target geographical location near the time of the first preset arrival time, but it is usually difficult to require the target terminal to arrive on time at the first preset time, because some calculation errors, short-term abnormal conditions, etc. need to be considered, so a waiting time can be reserved. Then in a possible implementation method, for example, the preset waiting time can be obtained first, and the preset waiting time here is the reserved buffer time. The specific implementation method of the preset waiting time can be selected and set according to actual needs. For example, the preset waiting time can be 3 minutes, 5 minutes, etc., and this embodiment does not limit this.

[0085] Afterwards, refer to Figure 6 , the moment corresponding to the preset waiting time before the first expected arrival time t2 can be determined as the starting time t3 of the first time range, and the moment corresponding to the preset waiting time after the first expected arrival time t2 can be determined as the ending time t4 of the first time range, and then the time period between the starting time t3 and the ending time t4 can be determined as the first time range.

[0086] Alternatively, in an optional implementation, the period between the start time t3 and the first estimated arrival time t2 may be determined as the first time range. Alternatively, the period between the first estimated arrival time t2 and the end time t4 may be determined as the first time range.

[0087] S303: Determine at least one terminal within a preset range from the first target geographic location.

[0088] The following is an introduction to the implementation of determining the target terminal device. It can be understood that, because the target terminal is required to reach the first target geographical location within the first time range, when selecting the target terminal, at least one terminal within a preset range from the first target geographical location is first determined. The terminal here can be, for example, a terminal held by a delivery person, or a terminal device for goods delivery, which is not limited in this embodiment.

[0089] For example, you can refer to Figure 7 To understand, such as Figure 7 As shown, assuming that the preset range corresponding to the current first target geographic location 1 is Figure 7 701 in the range, for example, at least one terminal within the preset range 701 can be determined, for example, Figure 7 The 6 terminals shown in .

[0090] S304: Determine a real-time geographic location of a first terminal among the at least one terminal.

[0091] After determining at least one terminal, the real-time geographic location of a first terminal among the at least one terminal may be determined, wherein the real-time geographic location is the current location of the first terminal, and the first terminal may be any one of the at least one terminal.

[0092] S305: Determine a second time range for the first terminal to arrive at the first target geographical location according to the distance between the real-time geographical location and the first target geographical location.

[0093] Because the target terminal needs to reach the first target geographic location from the current real-time geographic location to obtain data. Therefore, the second time range for the first terminal to reach the first target geographic location can be determined based on the distance between the real-time geographic location and the first target geographic location. The implementation method for determining the second time range here is similar to the implementation method for determining the first time range described above, and will not be repeated here.

[0094] S306: Determine the amount of data to be processed by the first terminal.

[0095] It is understandable that in this embodiment, the target terminal is required to reach the first target geographical location from the current real-time geographical location. An important prerequisite is that the target terminal needs to complete the processing of the current remaining data. Therefore, in this embodiment, the amount of data to be processed by the first terminal can also be determined.

[0096] S307: Determine the waiting time for processing of the first terminal according to the amount of data to be processed.

[0097] After determining the amount of data to be processed, the waiting time for the first terminal to process may be determined according to the amount of data to be processed, wherein the waiting time is the time required for the first terminal to complete the processing of the data.

[0098] In one possible implementation, for example, the average processing time of the first terminal can be obtained, where the average processing time refers to the average time required for the first terminal to process a data. For example, the average processing time corresponding to each terminal can be determined separately, or an average processing time can be determined for all terminals as a whole. This embodiment does not impose any restrictions on this.

[0099] This can be explained with reference to a specific example. For example, if the current number of data to be processed at the first terminal is 5 and the average processing time of the delivery object is 3 minutes, it can be determined that the processing time of the first terminal is 15 minutes.

[0100] Furthermore, it is possible that some terminals are idle, that is, the amount of data to be processed by the terminal may be 0. In this case, the waiting time of the first terminal is also 0.

[0101] S308: Adjust the second time range according to the duration to be processed.

[0102] After the waiting time for processing of the first terminal is determined, the second time range determined above can be adjusted according to the waiting time for processing.

[0103] For example, the second time range can be extended backward by the processing time to obtain an adjusted second time range, where the adjusted second time range refers to the time range for the first terminal to complete the processing of the remaining data to be processed and then reach the first target geographic location.

[0104] S309: If the second time range is within the first time range, determine the first terminal as a candidate terminal.

[0105] After determining the second time range of the first terminal, it can be determined first whether the second time range is within the first time range. If so, it can be determined that the current first terminal can reach the first target geographic location within the first time range, so the first terminal can be determined as an alternative terminal.

[0106] S310: Select a terminal that reaches the first target geographical location earliest from among the candidate terminals as the target terminal.

[0107] After determining the candidate terminal, there may be multiple candidate terminals, and then the terminal that reaches the first target geographical location earliest can be further selected as the target terminal from the candidate terminals. The terminal that reaches the first target geographical location earliest is selected as the target terminal, thereby effectively improving the efficiency of data processing.

[0108] It should be noted here that determining the terminals within the first time range in the second time range as candidate terminals and then selecting the target terminal from the candidate terminals actually excludes the terminals before the first time range from the selection range of the target terminal.

[0109] The terminals in the second time range before the first time range actually arrive earlier. The reason for excluding these terminals is that the data batch will arrive at the target geographical location within the first time range. If the terminal arrives too early, it will cause the terminal to wait for the data batch. Therefore, in this embodiment, the terminals in the second time range before the first time range will not be determined as candidate terminals. At the same time, this can ensure that these terminals are determined as candidate terminals within the appropriate first time range of the remaining target geographical locations, thereby ensuring the effective scheduling of the overall terminals and avoiding the mutual waiting of the terminals and the data batches.

[0110] It is also necessary to further explain that when determining the candidate terminals, it is possible that the second time range of each terminal is not within the first time range, that is, there is no candidate terminal. In this case, the earliest arriving first terminal can be directly determined as the target terminal.

[0111] After the target terminal is determined, for example, notification information may be sent to the target terminal to notify the target terminal to arrive at the first target geographical location within a first time range, thereby completing subsequent processing of the data.

[0112] S311: Push the data belonging to the first target geographical location in the data batch to the target terminal, so that the target terminal reaches the first target geographical location within a first time range to obtain the data.

[0113] The implementation of S311 is similar to that of S203 and will not be described in detail here.

[0114] The data processing method provided in the embodiment of the present application first determines the driving route according to the starting geographical location and each target geographical location in the data batch, and then determines the driving time from the starting geographical location to the first target geographical location according to the driving route, and then determines the time corresponding to the driving time after the departure time of the data batch as the first estimated arrival time of the data batch at the first target geographical location, so that the time when the data batch arrives at the first target geographical location can be effectively estimated. After determining the first estimated arrival time, the first time range of the first target geographical location is determined in combination with the preset waiting time, so that a certain buffer period can be reserved on the basis of the first estimated arrival time to reserve a tolerance time for calculation errors and abnormal situations, thereby improving the success rate of matching the target terminal. When determining the target terminal, the second time range for reaching the first target geographical location corresponding to each terminal can be determined first among at least one terminal within a preset range from the first target geographical location, and then the terminals within the first time range within the second time range can be determined as candidate terminals, so as to ensure that the terminals with a relatively close second time range and first time range are screened out to avoid the situation where one of the target terminal and the data is waiting for the other, and at the same time, it can ensure that the terminals other than the candidate terminals are free to wait for the scheduling of the remaining target geographical locations, so as to ensure that the effective scheduling of the terminals as a whole can be achieved. Then, the terminal that arrives at the first target geographical location earliest among the candidate terminals can be further selected as the target terminal, so as to allow the target terminal to arrive at the stop location as early as possible on the basis of a suitable arrival time, so as to complete the data processing as early as possible.

[0115] Based on the above introduction, the following Figures 8 to 11 In the data processing method provided in the present application, an implementation method of dividing a plurality of data to be processed into at least one data batch is introduced. Figure 8 The process of the data processing method provided in the embodiment of the present application Figure 3 , Fig. 9 A schematic diagram of implementing the division of sub-processing ranges provided in an embodiment of the present application, Fig.10A schematic diagram of the implementation of the processing scope provided in the embodiment of the present application, Fig.11 A schematic diagram of an implementation of determining data batches provided in an embodiment of the present application.

[0116] like Figure 8 As shown, the method includes:

[0117] S801. Obtain a data processing scope according to a starting geographical location.

[0118] The starting geographical location in this embodiment can be understood as a storage location. Usually, data is transported from the starting geographical location and then delivered to each target geographical location.

[0119] Taking the data as an example, a starting geographical location can be understood as a store. During the processing, it is usually processed as a unit of a store. The delivery scenario in this embodiment can be a same-city next-day delivery scenario. In this case, each store has its own delivery range. For addresses beyond the delivery range, the order processing cannot be completed, so as to ensure the timely delivery of orders.

[0120] Therefore, in this embodiment, the processing range of the data can be determined according to the starting geographical location, and the processing range means that the data will only be processed within this range. Therefore, in a possible implementation method, the processing range can be, for example, a circular range centered on the starting geographical location, or the processing range can also be a rectangular range, an irregular range, etc. This embodiment does not limit the specific implementation method of the processing range, and it can be selected and divided according to actual needs.

[0121] S802. Divide the processing range into multiple sub-processing ranges.

[0122] After determining the processing range, the processing range can be further divided into multiple sub-processing ranges. It is understandable that each data corresponds to its own data address. For example, if the data is an order, the data address is the delivery address of the order, where the delivery address can be a community, for example.

[0123] In this embodiment, for example, the sub-processing range can be divided according to the data address of each data in the data batch. For example, a data address can be first determined as a sub-processing range, and then it can be determined whether the amount of data in the same sub-processing range is lower than a preset value. If so, the data in the sub-processing range is divided into other sub-processing ranges until a final sub-processing range is obtained, in which the amount of data in each sub-processing range is greater than or equal to the preset value.

[0124] The implementation of determining the sub-processing range described above can be understood as a clustering process, where clustering is to cluster data with relatively close addresses and relatively small amounts of data, so that when processing data, these data addresses can be processed together in one trip, saving the cost of multiple allocations and round trips, thereby effectively improving the efficiency of data processing. Fig. 9 The implementation of determining the sub-processing scope described above is understood.

[0125] When clustering is performed, it is necessary to limit the amount of data in the sub-processing range after clustering. For example, the amount of data in the sub-processing range may be limited to be less than the maximum amount of data.

[0126] In one possible implementation, the maximum amount of data may be, for example, the maximum loading quantity of a delivery vehicle. For example, if a delivery vehicle transports data batches, then it must at least be ensured that the delivery vehicle can transport all the data within a sub-processing range at one time. If a delivery vehicle cannot transport all the data within the sub-processing range at one time, and requires at least two trips to transport all the data, then this means that the amount of data within the sub-processing range is relatively large, and there is no need to cluster the data within the sub-processing range.

[0127] This embodiment does not impose any restrictions on the specific implementation of the maximum data volume, as long as the maximum data volume can limit the amount of data within a sub-processing range.

[0128] For example, you can combine Fig. 9 To understand, such as Fig. 9 As shown, it is assumed that the data within the processing range 90 includes data 1 to data 45, and it is assumed that there are 6 data addresses in total among these data within the processing range 90, and it is also assumed that the maximum number of data within the sub-processing range is 30.

[0129] Reference Fig. 9 , where data address 1 corresponds to 3 data, namely data 1 to data 3; data address 2 corresponds to 3 data, namely data 4 to data 5; data address 3 corresponds to 4 data, namely data 6 to data 9.

[0130] Reference Fig. 9 It can be understood that the distances between data address 1, data address 2, and data address 3 are relatively close, and the number of data corresponding to these three data addresses is relatively small. Therefore, for example, data address 1, data address 2, and data address 3 can be clustered into a sub-processing range, and the obtained Fig. 9 The sub-processing range 901 shown includes data 1 to data 9. The amount of data in the sub-processing range 901 does not exceed the preset amount.

[0131] And, refer to Fig. 9 , data address 4 corresponds to 21 data, namely data 9 to data 29. It can be determined that the number of data corresponding to data address 4 is already relatively large. At this time, no matter which data address it is clustered with, it will exceed the preset number. Therefore, data address 4 can be directly determined as a sub-processing range, and the result is Fig. 9 The sub-processing range 902 shown includes data 9 to data 29. The amount of data in the sub-processing range 901 does not exceed the preset amount.

[0132] And, refer to Fig. 9 , data address 5 corresponds to 6 data, namely data 30 to data 35; data address 6 corresponds to 9 data, namely data 36 to data 45. Among them, the distance between data address 5 and data address 6 is relatively close, and the number of data corresponding to these two data addresses is also relatively small. Therefore, for example, data address 5 and data address 6 can be clustered into a sub-processing range, and the result is Fig. 9 The sub-processing range 903 shown includes data 30 to data 45. The amount of data in the sub-processing range 903 does not exceed the preset amount.

[0133] In the actual implementation process, the specific implementation process of clustering processing can be determined according to actual needs. For example, any possible clustering algorithm can be used for clustering processing as long as the sub-processing range obtained after clustering processing meets the distance and data quantity conditions introduced above.

[0134] And in an optional implementation, the processing range may include multiple small ranges. In a possible implementation, for example, referring to Fig.10 To understand, such as Fig.10 As shown, the processing range 100 includes four small ranges, namely A, B, C, and D. The specific division method of the small ranges can be selected according to actual needs.

[0135] It is understandable that the processing range is usually a relatively large range. If order delivery is carried out for the entire processing range as a whole, the terminal will need to shuttle and move continuously in the entire processing range, which will lead to a more dispersed distribution of terminals, which will in turn increase the difficulty of terminal scheduling and increase the distance the terminal travels from one location to another.

[0136] In this embodiment, the data processing range is set to include multiple small ranges, and then the data is processed separately for the multiple small ranges. That is to say, the data within a small range is processed first, and then the data within another small range is processed. This ensures that the terminal always moves in a smaller range, which effectively reduces the difficulty of terminal scheduling and also reduces the distance the terminal travels between various locations.

[0137] S803. Treat the data in the same sub-processing range as the same data batch.

[0138] After dividing into multiple sub-processing ranges, the data in the same sub-processing range can be regarded as the same data batch. Also, a data batch can include data in multiple sub-processing ranges. On this basis, the specific division method of the data batch can be selected and set according to time requirements.

[0139] S804: In the same data batch, determine the target data quantity of the data batch according to the processing time corresponding to each data.

[0140] Each data batch in this embodiment includes multiple data, where different data have different processing difficulties. In this embodiment, in order to ensure that the data time for data batches with different processing difficulties is relatively balanced, the number of data in the data batch can be further limited. The following is an introduction to possible implementation methods for determining the target data quantity.

[0141] It is understandable that the difficulty of data processing actually depends on the data address corresponding to the data. For example, taking order delivery as an example, if some communities are relatively large, then the average delivery time in this community is relatively long. Correspondingly, for smaller communities, the average delivery time will be shorter. Therefore, each data address in this embodiment corresponds to its own processing time. The processing time corresponding to the data here is actually the processing time corresponding to the data address of the data.

[0142] In the order delivery scenario, processing time can be understood as the average time required for the delivery personnel to complete the delivery of an order under the current data address.

[0143] Because the processing range is currently divided into multiple sub-processing ranges, each sub-processing range includes multiple data, and each data has a corresponding processing time. Therefore, for example, for the first sub-processing range among the multiple sub-processing ranges, the average processing time corresponding to each data in the first sub-processing range can be calculated to determine the average processing time corresponding to the first sub-processing range.

[0144] A data batch may include multiple sub-processing ranges, so further, the average value of the multiple sub-processing ranges in the data batch may be determined as the average processing time corresponding to the data batch.

[0145] It is understandable that in order to avoid the terminal being occupied for a long time, resulting in no available terminal when the terminal is needed to reach the target geographical location to obtain data in time, which in turn causes the problem of long waiting time for data batches, a maximum processing time can be set to ensure that the processing time for each data batch is relatively balanced.

[0146] The maximum processing time is used to limit the maximum processing time of a data batch. For example, if a data processing process does not exceed 30 minutes, 30 minutes here is the maximum processing time.

[0147] Therefore, in this embodiment, the target data quantity corresponding to the data batch can be determined according to the average processing time corresponding to the data batch and the maximum processing time described above. The target data quantity corresponding to the data batch here refers to the number of data that can be included in the data batch to ensure that the data processing is completed within the maximum processing time by processing the data according to the average processing time corresponding to the data batch described above.

[0148] For example, the ratio of the longest processing time to the average processing time corresponding to the data batch can be rounded to an integer to determine the target data quantity corresponding to the data batch.

[0149] S805: If the amount of data in the data batch is less than or equal to the target amount of data, the data batch is used as a candidate batch.

[0150] The actual amount of data in the data batch can then be compared with the target amount of data mentioned above. In one possible implementation, if the amount of data in the data batch is less than or equal to the target amount of data, it means that processing the current data batch can ensure that the overall processing time is controlled within the maximum processing time. Therefore, the current data batch can be directly determined as an alternative batch, waiting for subsequent batch operations.

[0151] S806: If the amount of data in the data batch is greater than the target amount of data, split the data batch into at least two candidate batches.

[0152] In another possible implementation, if the amount of data in a data batch is greater than the target amount of data, it means that if the current data batch is processed, it is impossible to ensure that the overall delivery time is controlled within the maximum processing time, so the current data batch needs to be split. The data batch can then be split into at least two alternative batches, and the amount of data in the alternative batch is less than or equal to the target amount of data, so that it can be ensured that for one alternative batch, the overall processing time can be controlled within the maximum processing time.

[0153] S807: Determine the maximum data volume of a data batch.

[0154] After determining that multiple candidate batches are obtained, data batches can be obtained based on the multiple candidate batches. In a possible implementation, the amount of data in a data batch needs to be controlled, so the maximum amount of data in a batch can be determined.

[0155] The maximum data volume may be, for example, the maximum carrying capacity of a delivery vehicle, or it may be selected and set according to actual needs.

[0156] S808. Treat one or more candidate batches whose sum does not exceed the maximum data amount as the same data batch.

[0157] Afterwards, one or more candidate batches whose sum does not exceed the maximum data amount can be taken as the same data batch, thereby obtaining the final divided data batches.

[0158] For example, you can combine Fig.11 To understand, such as Fig.11 As shown, assuming that there is currently Fig.11 The four candidate batches shown, each of which corresponds to its own target geographic location. On the basis of satisfying the requirement that the sum does not exceed the maximum data volume, for example, candidate batch 1 and candidate batch 2 can be determined as one data batch, wherein the distance between the target geographic locations of candidate batch 1 and candidate batch 2 can be, for example, a preset distance.

[0159] Furthermore, candidate batch 3 and candidate batch 4 may be determined as one data batch, wherein the distance between the target geographic locations of candidate batch 3 and candidate batch 4 may also be less than a preset distance.

[0160] Reference Fig.11 It is understandable that if alternative batch 1 and alternative batch 4 are determined as one order batch, the distance between the target geographical locations of these two alternative batches is relatively far. On this basis, it is necessary to transport the orders of alternative batch 2 and alternative batch 3 later. Fig.11The current method of dividing data batches undoubtedly increases the distance of data processing. Therefore, by limiting the distance of target geographic locations of candidate batches in data batches to be less than the preset cluster, the distance required for data processing can be effectively shortened, thereby effectively improving data processing efficiency.

[0161] In an optional implementation, if the target terminal cannot reach the first target geographical location within the first time range, a terminal that arrives the earliest is selected from among the candidate terminals as a new target terminal.

[0162] For example, for any data batch, if the fault information corresponding to the data batch is received, or if the abnormal information reported by the target terminal corresponding to the data batch is received, the batch information of the data batch can be updated, and the updated batch information can be used to re-determine the target terminal, and send notification information to the new target terminal. The batch information includes at least one of the following: the first time range corresponding to each target geographical location in the data batch, and the target terminal corresponding to the data batch.

[0163] The data processing method provided by the embodiment of the present application divides the processing range of the data corresponding to the starting geographical location into multiple sub-processing ranges, so that the data of several data addresses with relatively small data quantities can be clustered together and assigned to a target terminal to complete the distribution at one time, thereby realizing efficient operation of the target terminal. At the same time, when the data is processed in batches, the target data quantity of the data batch will be further determined according to the processing time corresponding to each data, so as to limit the data quantity of each data batch within a certain range, ensure that each data batch can achieve the balance in processing, and then ensure that the target terminal can complete the data outlet within a relatively balanced time, and then quickly enter the next data processing process, so as to realize flexible and efficient scheduling of the terminal. In addition, according to the limitation of the target data quantity, the existing multiple data batches are determined as multiple candidate batches, and then one or more candidate batches whose sum does not exceed the maximum data amount are taken as the same data batch, so as to ensure that data processing can be realized quickly and efficiently for a data batch.

[0164] In summary, the data processing method provided in the embodiment of the present application realizes fast, flexible and efficient scheduling of data and terminals, reduces the waiting time of data and terminals for each other, and thus can effectively improve the speed and efficiency of data processing.

[0165] Fig.12 This is a schematic diagram of the structure of the data processing device provided in the embodiment of the present application. Fig.12 As shown, the device 120 includes: a determination module 1201 and a processing module 1202.

[0166] A determination module 1201 is used to determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location;

[0167] The determining module 1201 is further configured to determine a first time range for the data batch to arrive at the first target geographical location according to the starting geographical location and a first target geographical location among the target geographical locations;

[0168] The processing module 1202 is used to push the data belonging to the first target geographical location in the data batch to the target terminal, so that the target terminal reaches the first target geographical location within the first time range to obtain the data.

[0169] In a possible design, the determining module 1201 is specifically used for:

[0170] Determine at least one terminal within a preset range from the first target geographical location;

[0171] Determining a real-time geographic location of a first terminal among the at least one terminal;

[0172] Determine a second time range for the first terminal to arrive at the first target geographical location according to the distance between the real-time geographical location and the first target geographical location;

[0173] If the second time range is within the first time range, determining the first terminal as a candidate terminal;

[0174] A terminal that reaches the first target geographical location earliest is selected from among the candidate terminals as the target terminal.

[0175] In one possible design, the processing module 1202 is further configured to:

[0176] Determining the amount of data to be processed by the first terminal;

[0177] Determining a waiting time for the first terminal to be processed according to the amount of data to be processed;

[0178] The second time range is adjusted according to the to-be-processed time length.

[0179] In a possible design, the determining module 1201 is specifically used for:

[0180] According to the starting geographical location, obtaining a data processing scope;

[0181] dividing the processing range into a plurality of sub-processing ranges;

[0182] Treat the data within the same sub-processing range as the same data batch.

[0183] In one possible design, the processing module 1202 is further configured to:

[0184] If the amount of data in the same sub-processing range is lower than the preset value, the data in the sub-processing range will be divided into other sub-processing ranges.

[0185] In one possible design, the processing module 1202 is further configured to:

[0186] In the same data batch, the target data quantity of the data batch is determined according to the processing time corresponding to each data;

[0187] If the amount of data in the data batch is less than or equal to the target amount of data, taking the data batch as a candidate batch;

[0188] If the amount of data in the data batch is greater than the target amount of data, splitting the data batch into at least two candidate batches;

[0189] A data batch is determined among a plurality of candidate batches.

[0190] In a possible design, the determining module 1201 is specifically used for:

[0191] Determine the maximum amount of data in a data batch;

[0192] One or more candidate batches whose sum does not exceed the maximum data amount are treated as the same data batch.

[0193] In one possible design, the processing module 1202 is further configured to:

[0194] If the target terminal cannot reach the first target geographical location within the first time range, a terminal that arrives the earliest is selected from among the candidate terminals as a new target terminal.

[0195] The device provided in this embodiment can be used to execute the technical solution of the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0196] Fig.13 A schematic diagram of the hardware structure of a data processing device provided in an embodiment of the present application is shown in FIG. Fig.13 As shown, the data processing device 130 of this embodiment includes: a processor 1301 and a memory 1302;

[0197] Memory 1302, used to store computer-executable instructions;

[0198] The processor 1301 is used to execute the computer-executable instructions stored in the memory to implement the various steps performed by the data processing method in the above embodiment. For details, please refer to the relevant description in the above method embodiment.

[0199] Optionally, the memory 1302 may be independent or integrated with the processor 1301 .

[0200] When the memory 1302 is independently provided, the data processing device further includes a bus 1303 for connecting the memory 1302 and the processor 1301 .

[0201] An embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the data processing method executed by the above data processing device is implemented.

[0202] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0203] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (English: processor) to perform some steps of the method described in each embodiment of the present application.

[0204] It should be understood that the above processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor or a combination of hardware and software modules in the processor.

[0205] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0206] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0207] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0208] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0209] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A data processing method, characterized in that: include: Determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location; Determining, according to the starting geographical location and a first target geographical location among the target geographical locations, a first time range for the data batch to arrive at the first target geographical location; Pushing the data belonging to the first target geographical location in the data batch to a target terminal; the target terminal is a terminal device held by a delivery person, or a terminal device with a cargo delivery function; Wherein, when the target terminal is a terminal device with a cargo delivery function, the target terminal is made to arrive at the first target geographical location within the first time range to obtain the cargo corresponding to the data; In the case where the target terminal is a terminal device held by a delivery person, the delivery person corresponding to the target terminal can arrive at the first target geographical location within the first time range to obtain the goods corresponding to the data.

2. The method according to claim 1, characterized in that The target terminal is determined in the following manner: Determine at least one terminal within a preset range from the first target geographical location; Determining a real-time geographic location of a first terminal among the at least one terminal; Determine a second time range for the first terminal to arrive at the first target geographical location according to the distance between the real-time geographical location and the first target geographical location; If the second time range is within the first time range, determining the first terminal as a candidate terminal; A terminal that reaches the first target geographical location earliest is selected from the candidate terminals as the target terminal.

3. The method according to claim 2, characterized in that After determining, based on the distance between the real-time geographic location and the first target geographic location, a second time range for the first terminal to arrive at the first target geographic location, the method further includes: Determining the amount of data to be processed by the first terminal; Determining a waiting time for the first terminal to be processed according to the amount of data to be processed; The second time range is adjusted according to the to-be-processed time length.

4. The method according to any one of claims 1 to 3, characterized in that: The step of determining at least one data batch according to the data to be processed includes: According to the starting geographical location, obtaining a data processing scope; dividing the processing range into a plurality of sub-processing ranges; Treat the data within the same sub-processing range as the same data batch.

5. The method according to claim 4, characterized in that The method further comprises: If the amount of data in the same sub-processing range is lower than the preset value, the data in the sub-processing range will be divided into other sub-processing ranges.

6. The method according to claim 4, characterized in that The method further comprises: In the same data batch, the target data quantity of the data batch is determined according to the processing time corresponding to each data; If the amount of data in the data batch is less than or equal to the target amount of data, taking the data batch as a candidate batch; If the amount of data in the data batch is greater than the target amount of data, splitting the data batch into at least two candidate batches; A data batch is determined among a plurality of candidate batches.

7. The method according to claim 6, characterized in that The step of determining a data batch from a plurality of candidate batches comprises: Determine the maximum amount of data in a data batch; One or more candidate batches whose sum does not exceed the maximum data amount are treated as the same data batch.

8. The method according to claim 2, characterized in that: The method further comprises: If the target terminal cannot reach the first target geographical location within the first time range, a terminal that arrives the earliest is selected from among the candidate terminals as a new target terminal.

9. A data processing device, characterized in that: include: A determination module, configured to determine at least one data batch according to the data to be processed, wherein each data batch corresponds to a starting geographical location and at least one target geographical location; The determination module is further configured to determine a first time range for the data batch to arrive at a first target geographical location according to the starting geographical location and a first target geographical location among the target geographical locations; A processing module is used to push the data belonging to the first target geographic location in the data batch to a target terminal, where the target terminal is a terminal device held by a delivery personnel, or a terminal device with a cargo delivery function; wherein, when the target terminal is a terminal device with a cargo delivery function, the target terminal is enabled to arrive at the first target geographic location within the first time range to obtain the data; and when the target terminal is a terminal device held by a delivery personnel, the delivery personnel corresponding to the target terminal is enabled to arrive at the first target geographic location within the first time range to obtain the cargo corresponding to the data.

10. A data processing device, characterized in that: include: Memory, used to store programs; A processor, configured to execute the program stored in the memory; when the program is executed, the processor is configured to execute the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The method comprises instructions which, when executed on a computer, cause the computer to perform the method as claimed in any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

Images