Freight order generation method and device, equipment and storage medium

Abstract

The invention provides a freight order generation method, apparatus and device, and a storage medium. The method comprises the steps of receiving an order generation instruction input by a target user; the order generation instruction carries a user identifier corresponding to a target user; in response to the order generation instruction, judging whether the target user is a registered user based on the user identifier; if the target user is a registered user, determining N pieces of historical cargo information associated with the target user; n is a positive integer. In the embodiment of the invention, under the condition that a user is a registered user, N pieces of historical cargo information associated with the user are determined based on historical data, and then a freight order is generated based on the N pieces of historical cargo information; therefore, the user does not need to repeatedly fill in the freight information when ordering each time, so that the operation steps of the user are reduced, and the freight order is more convenient to generate.

Description

Technical Field

[0001] The present application relates to the field of freight, and in particular to a method, device, equipment and storage medium for generating a freight order. Background Art

[0002] In the field of logistics, users can generate freight orders through applications on electronic devices. In the process of generating freight orders, users need to fill in information such as the name, type, type and volume of the goods on the order interface. Based on the above information filled in by the user, an electronic freight order is generated and a vehicle is matched for the user.

[0003] However, the user needs to repeatedly fill in the above information each time when placing an order, which increases the amount of operations for the user in generating a freight order, thereby making the generation of a freight order more cumbersome. Summary of the invention

[0004] The main purpose of this application is to provide a freight order generation method, device, computer equipment and storage medium, aiming to solve the technical problem that the generation of freight orders is relatively complicated.

[0005] To achieve the above objectives, the present application provides a method for generating a freight order, the method comprising:

[0006] Receiving an order generation instruction input by a target user; the order generation instruction carries a user identifier corresponding to the target user;

[0007] In response to the order generation instruction, based on the user identifier, determining whether the target user is a registered user;

[0008] If the target user is a registered user, then determine N historical goods information associated with the target user; N is a positive integer;

[0009] A freight order is generated based on the target user's input of the N historical cargo information.

[0010] Optionally, judging whether the target user is a registered user based on the user identifier includes:

[0011] Querying a preset database to see whether the user identifier is stored;

[0012] If the database stores the user identifier, determining that the target user is a registered user;

[0013] If the database does not store the user identifier, determining that the target user is an unregistered user;

[0014] The database stores user identifiers corresponding to registered users.

[0015] Optionally, the determining N items of goods information associated with the target user includes:

[0016] Querying a user identifier corresponding to the target user in a preset mapping table;

[0017] Determine N goods information associated with the user identifier;

[0018] The mapping table is used to store the mapping relationship between the user identification and the goods information.

[0019] Optionally, after determining whether the target user is a registered user, the method further includes:

[0020] If the target user is an unregistered user, receiving the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo picture input by the target user;

[0021] Determine the volume of the cargo based on the cargo picture;

[0022] Determine the freight itinerary based on the freight transportation starting point and the freight transportation destination; match the freight vehicle based on the freight volume, the freight type and the freight weight;

[0023] A freight order is generated based on the freight itinerary and the freight vehicle.

[0024] Optionally, generating a freight order based on the target user's input of the N goods information includes:

[0025] receiving input of target goods information from the target user in the N historical goods information;

[0026] In response to the target user inputting target cargo information, obtaining the cargo transportation starting point, cargo transportation destination, cargo type, cargo weight and cargo picture of the target cargo information;

[0027] Determine the volume of the cargo based on the cargo picture;

[0028] Determine a freight itinerary based on the freight transportation starting point and the freight transportation destination;

[0029] Matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight;

[0030] A freight order is generated based on the freight itinerary and the freight vehicle.

[0031] Optionally, determining the volume of the cargo based on the cargo picture includes:

[0032] Performing point cloud processing on the cargo image to obtain a target point cloud;

[0033] Determine a bounding box corresponding to the target point cloud;

[0034] The volume of the bounding box corresponding to the target point cloud is determined as the cargo volume.

[0035] Optionally, matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight includes:

[0036] Determine the type of freight vehicle according to the type of goods;

[0037] Determining the carrying capacity of the freight vehicle according to the weight of the freight;

[0038] Determining the model of the freight vehicle according to the volume of the cargo;

[0039] The target freight vehicle for matching the freight order is determined according to the type of the freight vehicle, the carrying capacity of the freight vehicle and the model of the freight vehicle.

[0040] In addition, to achieve the above-mentioned purpose, the present application also provides a freight order generation device, the freight order generation device comprising:

[0041] A first receiving module is used to receive an order generation instruction input by a target user; the order generation instruction carries a user identifier corresponding to the target user;

[0042] A judgment module, configured to judge whether the target user is a registered user based on the user identifier in response to the order generation instruction;

[0043] A first determination module, configured to determine N historical goods information associated with the target user if the target user is a registered user; N is a positive integer;

[0044] The first generating module is used to generate a freight order based on the input of the N historical cargo information by the target user.

[0045] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0046] The computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the freight order generation methods proposed in the embodiments of the present application are implemented.

[0047] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0048] The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps of any one of the freight order generation methods proposed in the embodiments of the present application are implemented.

[0049] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0050] The present application provides a method, device, equipment and storage medium for generating a freight order, the method comprising: receiving an order generation instruction input by a target user; the order generation instruction carries a user identifier corresponding to the target user; in response to the order generation instruction, judging whether the target user is a registered user based on the user identifier; if the target user is a registered user, determining N historical cargo information associated with the target user; N is a positive integer. In an embodiment of the present application, when the user is a registered user, based on historical data, determining N historical cargo information associated with the user, and then generating a freight order based on the above N historical cargo information; in this way, the user does not need to repeatedly fill in the freight information each time an order is placed, thereby reducing the user's operation steps and making the generation of freight orders more convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. 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 work.

[0052] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0053] Figure 2 is a flow chart of a method for generating a freight order provided in an embodiment of the present application;

[0054] Figure 3 is an application flow chart of the method for generating a freight order provided in an embodiment of the present application;

[0055] Figure 4 It is a structural schematic diagram of an embodiment of a freight order generating device provided in an embodiment of the present application;

[0056] Figure 5 It is a basic structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] The freight order generation method provided in the embodiment of the present application is applied to the freight order generation device. Unless otherwise defined, all technical and scientific terms used in this article have the same meaning as those generally understood by technicians in the technical field of this application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0058] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0059] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0060] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0061] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social online platform software, etc.

[0062] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0063] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0064] It should be noted that the freight order generation method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the freight order generation device is generally set in the server / terminal device.

[0065] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0066] Please refer to Figure 2 , shows a flow chart of an embodiment of the method for generating a freight order according to the present application. The embodiment of the present application can acquire and process relevant data based on artificial intelligence technology.

[0067] The method for generating a freight order provided in the embodiment of the present application comprises the following steps:

[0068] S210, receiving an order generation instruction input by a target user.

[0069] In an optional application scenario, the target user can generate an electronic freight order through the application.

[0070] In the above application scenario, the target user can perform relevant operations on the application to generate an order generation instruction, wherein the order generation instruction carries a user identifier corresponding to the target user.

[0071] Optionally, the user identification may be represented by a binary number.

[0072] S220: In response to the order generation instruction, determine whether the target user is a registered user based on the user identifier.

[0073] As mentioned above, the order generation instruction carries the user identification.

[0074] In this step, after receiving the order generation instruction, respond to the order generation instruction and determine whether the target user is a registered user based on the user identifier.

[0075] Optionally, if the target user is a registered user, it means that the application has stored the historical data of the target user; if the target user is an unregistered user, it means that the application has not stored the historical data of the target user.

[0076] S230: If the target user is a registered user, determine N historical goods information associated with the target user.

[0077] In this step, if the target user is a registered user, the historical data of the target user is read, and N historical goods information associated with the target user is determined based on the historical data. For specific implementation methods, please refer to the subsequent embodiments.

[0078] Among them, historical cargo information includes cargo type, cargo weight and cargo volume.

[0079] Wherein, N is a positive integer.

[0080] S240: Generate a freight order based on the target user's input of the N historical cargo information.

[0081] In this step, after determining the N historical cargo information, the application interface displays the N historical cargo information, and the user performs relevant operations on the application interface to input the N historical cargo information. Further, based on the user's input of the N historical cargo information, a freight order is generated.

[0082] In the embodiment of the present application, an order generation instruction input by a target user is received; the order generation instruction carries a user identifier corresponding to the target user; in response to the order generation instruction, based on the user identifier, it is determined whether the target user is a registered user; if the target user is a registered user, N historical goods information associated with the target user is determined; N is a positive integer. In the embodiment of the present application, if the user is a registered user, based on historical data, N historical goods information associated with the user is determined, and then a freight order is generated based on the above N historical goods information; in this way, the user does not need to repeatedly fill in the freight information each time an order is placed, thereby reducing the user's operation steps and making the generation of freight orders more convenient.

[0083] Optionally, judging whether the target user is a registered user based on the user identifier includes:

[0084] Querying a preset database to see whether the user identifier is stored;

[0085] If the database stores the user identifier, determining that the target user is a registered user;

[0086] If the database does not store the user identifier, determining that the target user is an unregistered user;

[0087] The database stores user identifiers corresponding to registered users.

[0088] In this embodiment, a database is pre-set, and the database stores user identifiers corresponding to registered users.

[0089] In this embodiment, the order generation instruction is parsed to obtain the user identifier, and the user identifier is queried in the database. If the database stores the user identifier, it means that the target user is a registered user; if the database does not store the user identifier, it means that the target user is an unregistered user.

[0090] Exemplarily, the user ID corresponding to the target user is 11, and the binary number 11 is found in the database, so the target user is determined to be a registered user. In this embodiment, the user IDs of registered users are pre-stored in the database, and the user IDs are searched in the database to accurately determine whether the target user is a registered user.

[0091] Optionally, the determining N items of goods information associated with the target user includes:

[0092] Querying a user identifier corresponding to the target user in a preset mapping table;

[0093] Determine N goods information associated with the user identifier;

[0094] The mapping table is used to store the mapping relationship between the user identification and the goods information.

[0095] In this embodiment, a mapping table is pre-set, and the mapping table is used to store the mapping relationship between the user identification and the goods information.

[0096] In this embodiment, after determining that the target user is a registered user, historical data of the target user may be obtained.

[0097] Specifically, the user ID corresponding to the target user is queried in a preset mapping table. Since the mapping table stores the mapping relationship between the user ID and the goods information, N goods information associated with the user ID can be obtained.

[0098] In an application scenario where an electronic freight order is generated through an application, after obtaining N goods information, the N goods information is displayed on the application interface; or, a drop-down option control is displayed on the application interface, and the target user displays different goods information by manipulating the drop-down option control.

[0099] It should be understood that after the target user generates a freight order, the mapping relationship between the user identification corresponding to the target user and the freight information will be stored in the mapping table.

[0100] Optionally, after determining whether the target user is a registered user, the method further includes:

[0101] If the target user is an unregistered user, receiving the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo picture input by the target user;

[0102] Determine the volume of the cargo based on the cargo picture;

[0103] Determine a freight itinerary based on the freight transportation starting point and the freight transportation destination;

[0104] Matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight;

[0105] A freight order is generated based on the freight itinerary and the freight vehicle.

[0106] In this embodiment, if the target user is an unregistered user, the target user is required to input the relevant data of the goods, and then a freight order is generated according to the data input by the user.

[0107] Specifically, the target users enter the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo pictures by performing corresponding operations on the application.

[0108] Furthermore, based on the cargo picture input by the user, the cargo volume is determined. For specific implementation methods, please refer to the subsequent embodiments.

[0109] In this embodiment, the freight trip is determined based on the freight delivery starting point and the freight delivery destination. Optionally, multiple trips with the freight delivery starting point as the trip starting point and the freight delivery destination as the trip destination can be obtained, and the trip with the shortest path is determined as the freight trip.

[0110] After obtaining the cargo volume, the cargo vehicle is matched based on the cargo volume, cargo type and cargo weight. For specific implementation methods, please refer to the subsequent embodiments.

[0111] Furthermore, the above freight trip data and freight vehicle data are aggregated to generate a freight order.

[0112] The freight order generated in this embodiment is generated based on the freight itinerary and the freight vehicle, so as to match the most suitable vehicle for the goods and select the most suitable itinerary, thereby improving the efficiency of freight transportation.

[0113] Optionally, generating a freight order based on the target user's input of the N goods information includes:

[0114] receiving input of target goods information from the target user in the N historical goods information;

[0115] In response to the target user inputting target cargo information, obtaining the cargo transportation starting point, cargo transportation destination, cargo type, cargo weight and cargo picture of the target cargo information;

[0116] Determine the volume of the cargo based on the cargo picture;

[0117] Determine a freight itinerary based on the freight transportation starting point and the freight transportation destination;

[0118] Matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight;

[0119] A freight order is generated based on the freight itinerary and the freight vehicle.

[0120] In this embodiment, if the target user is a registered user, the target cargo information is determined based on the target user's input of N historical cargo information, and then the target cargo information is obtained. The above-mentioned target cargo information is historical data recording the cargo transportation starting point, cargo transportation destination, cargo type, cargo weight and cargo pictures.

[0121] Optionally, the target cargo information is parsed to obtain the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo pictures.

[0122] Based on the cargo picture input by the user, the cargo volume is determined. For specific implementation methods, please refer to the subsequent embodiments.

[0123] In this embodiment, the freight trip is determined based on the freight delivery starting point and the freight delivery destination. Optionally, multiple trips with the freight delivery starting point as the trip starting point and the freight delivery destination as the trip destination can be obtained, and the trip with the shortest path is determined as the freight trip.

[0124] After obtaining the cargo volume, the cargo vehicle is matched based on the cargo volume, cargo type and cargo weight. For specific implementation methods, please refer to the subsequent embodiments.

[0125] Furthermore, the above freight trip data and freight vehicle data are aggregated to generate a freight order.

[0126] The freight order generated in this embodiment is generated based on the freight itinerary and the freight vehicle, so as to match the most suitable vehicle for the goods and select the most suitable itinerary, thereby improving the efficiency of freight transportation.

[0127] The following is a detailed description of how to determine the volume of goods based on the goods pictures:

[0128] Optionally, determining the volume of the cargo based on the cargo picture includes:

[0129] Performing point cloud processing on the cargo image to obtain a target point cloud;

[0130] Determine a bounding box corresponding to the target point cloud;

[0131] The volume of the bounding box corresponding to the target point cloud is determined as the cargo volume.

[0132] In this embodiment, point cloud processing may be performed on the cargo image to obtain a target point cloud, and a bounding box corresponding to the target point cloud may be determined.

[0133] Specifically, the cargo image may be preprocessed first, for example, denoising the image and enhancing the image contrast; after preprocessing the cargo image, the depth information of the cargo image may be extracted, for example, the OpenCV library and a deep learning model may be used to extract the depth information of the cargo image.

[0134] According to the extracted depth information, the two-dimensional image is converted into three-dimensional point cloud data. This step usually involves combining each pixel in the image with its corresponding depth value to generate three-dimensional coordinate points and obtain the target point cloud. After generating the point cloud data, various point cloud processing software or libraries can be used for further processing and analysis to obtain the bounding box corresponding to the target point cloud. For example, open source libraries such as CloudCompare, PCL (Point Cloud Library), and Open3D can be used to perform operations such as filtering, segmentation, registration, and visualization of point clouds.

[0135] The volume of the bounding box corresponding to the target point cloud is determined as the cargo volume.

[0136] In this embodiment, the volume of the cargo can be intelligently calculated by performing point cloud processing on the cargo image.

[0137] The following is a detailed description of how to match the freight vehicles corresponding to the goods:

[0138] Optionally, matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight includes:

[0139] Determine the type of freight vehicle according to the type of goods;

[0140] Determining the carrying capacity of the freight vehicle according to the weight of the freight;

[0141] Determining the model of the freight vehicle according to the volume of the cargo;

[0142] The target freight vehicle for matching the freight order is determined according to the type of the freight vehicle, the carrying capacity of the freight vehicle and the model of the freight vehicle.

[0143] In this embodiment, the type of freight vehicle is determined according to the type of cargo. For example, when the cargo is frozen goods, the freight vehicle is determined to be a refrigerated truck. The carrying capacity of the freight vehicle is determined according to the weight of the cargo, that is, the carrying capacity of the freight vehicle should be greater than the weight of the cargo. The model of the freight vehicle is determined according to the volume of the cargo. For example, according to the size of the cargo, the model of the vehicle is determined to be a car, an SUV, a van, or a truck.

[0144] Then, the matching target freight vehicle is determined based on the type, carrying capacity and vehicle model of the above freight vehicles.

[0145] To understand the overall technical solution, please refer to Figure 3 ,like Figure 3 As shown, when an order generation instruction is received from a target user, it is determined whether the target user is a registered user; if the target user is a registered user, N historical cargo information associated with the target user is displayed; the target user's input of the N historical cargo information is received, the target cargo information is determined, and then a freight order is generated based on the target cargo information.

[0146] If the target user is an unregistered user, the target user is required to fill in the target cargo information, namely, the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo picture, and then generate a freight order based on the above cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo picture.

[0147] See also Figure 4 The embodiment of the present application provides a freight order generating device 400, and the freight order generating device 400 includes:

[0148] The first receiving module 410 is used to receive an order generation instruction input by a target user; the order generation instruction carries a user identifier corresponding to the target user;

[0149] A determination module 420, configured to determine, in response to the order generation instruction, whether the target user is a registered user based on the user identifier;

[0150] The first determination module 430 is used to determine N historical goods information associated with the target user if the target user is a registered user; N is a positive integer;

[0151] The first generating module 440 is used to generate a freight order based on the input of the N historical cargo information by the target user.

[0152] Optionally, the judging module 420 is specifically configured to:

[0153] Querying a preset database to see whether the user identifier is stored;

[0154] If the database stores the user identifier, determining that the target user is a registered user;

[0155] If the database does not store the user identifier, determining that the target user is an unregistered user;

[0156] The database stores user identifiers corresponding to registered users.

[0157] Optionally, the first determining module 430 is specifically configured to:

[0158] Querying a user identifier corresponding to the target user in a preset mapping table;

[0159] Determine N goods information associated with the user identifier;

[0160] The mapping table is used to store the mapping relationship between the user identification and the goods information.

[0161] Optionally, the freight order generating device 400 further includes:

[0162] A second receiving module is used for receiving the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo picture input by the target user if the target user is an unregistered user;

[0163] A second determination module, configured to determine the volume of the cargo based on the cargo picture;

[0164] A third determining module is used to determine the freight itinerary based on the freight transportation starting point and the freight transportation destination;

[0165] a fourth determination module, configured to match a freight vehicle based on the cargo volume, the cargo type, and the cargo weight;

[0166] The second generating module is used to generate a freight order based on the freight itinerary and the freight vehicle.

[0167] Optionally, the first generating module 440 is specifically configured to:

[0168] receiving input of target goods information from the target user in the N historical goods information;

[0169] In response to the target user inputting target cargo information, obtaining the cargo transportation starting point, cargo transportation destination, cargo type, cargo weight and cargo picture of the target cargo information;

[0170] Determine the volume of the cargo based on the cargo picture;

[0171] Determine a freight itinerary based on the freight transportation starting point and the freight transportation destination;

[0172] Matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight;

[0173] A freight order is generated based on the freight itinerary and the freight vehicle.

[0174] Optionally, the second determining module and the first generating module 440 are further specifically configured to:

[0175] Performing point cloud processing on the cargo image to obtain a target point cloud;

[0176] Determine a bounding box corresponding to the target point cloud;

[0177] The volume of the bounding box corresponding to the target point cloud is determined as the cargo volume.

[0178] Optionally, the fourth determining module and the first generating module 440 are further specifically configured to:

[0179] Determine the type of freight vehicle according to the type of goods;

[0180] Determining the carrying capacity of the freight vehicle according to the weight of the freight;

[0181] Determining the model of the freight vehicle according to the volume of the cargo;

[0182] The target freight vehicle for matching the freight order is determined according to the type of the freight vehicle, the carrying capacity of the freight vehicle and the model of the freight vehicle.

[0183] To solve the above technical problems, the present application also provides a computer device. Figure 5 , Figure 5 This is a basic structural block diagram of the computer device in this embodiment.

[0184] The computer device 5 includes a memory 51, a processor 52, and a network interface 53 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 5 with components 51-53, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0185] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0186] The memory 51 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 51 can be an internal storage unit of the computer device 5, such as a hard disk or memory of the computer device 5. In other embodiments, the memory 51 can also be an external storage device of the computer device 5, such as a plug-in hard disk equipped on the computer device 5, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Of course, the memory 51 can also include both the internal storage unit of the computer device 5 and its external storage device. In this embodiment, the memory 51 is generally used to store the operating system and various application software installed on the computer device 5, such as the program code of the freight order generation method, etc. In addition, the memory 51 can also be used to temporarily store various types of data that have been output or are to be output.

[0187] The processor 52 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 52 is generally used to control the overall operation of the computer device 5. In this embodiment, the processor 52 is used to run the program code stored in the memory 51 or process data, such as running the program code of the freight order generation method.

[0188] The network interface 53 may include a wireless network interface or a wired network interface. The network interface 53 is generally used to establish a communication connection between the computer device 5 and other electronic devices.

[0189] The present application also provides another embodiment, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores the freight order generation program, and the freight order generation program can be executed by at least one processor so that the at least one processor performs the steps of the freight order generation method as described above.

[0190] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware online platform, and of course, by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0191] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0192] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for generating a freight order, characterized in that: include: Receive order generation instructions input by target users; The order generation instruction carries a user identifier corresponding to the target user; In response to the order generation instruction, based on the user identifier, determining whether the target user is a registered user; If the target user is a registered user, then determine N historical goods information associated with the target user; N is a positive integer; A freight order is generated based on the target user's input of the N historical cargo information.

2. The method according to claim 1, characterized in that The determining, based on the user identifier, whether the target user is a registered user includes: Querying a preset database to see whether the user identifier is stored; If the database stores the user identifier, determining that the target user is a registered user; If the database does not store the user identifier, determining that the target user is an unregistered user; The database stores user identifiers corresponding to registered users.

3. The method according to claim 1, characterized in that The determining of N goods information associated with the target user includes: Querying a user identifier corresponding to the target user in a preset mapping table; Determine N goods information associated with the user identifier; The mapping table is used to store the mapping relationship between the user identification and the goods information.

4. The method according to claim 1, characterized in that: After determining whether the target user is a registered user, the method further includes: If the target user is an unregistered user, receiving the cargo delivery starting point, cargo delivery destination, cargo type, cargo weight and cargo picture input by the target user; Determine the volume of the cargo based on the cargo picture; Determine the freight itinerary based on the freight transportation starting point and the freight transportation destination; match the freight vehicle based on the freight volume, the freight type and the freight weight; A freight order is generated based on the freight itinerary and the freight vehicle.

5. The method according to claim 1, characterized in that The generating of the freight order based on the input of the N goods information by the target user comprises: receiving input of target goods information from the target user among the N historical goods information; In response to the target user inputting target cargo information, obtaining the cargo transportation starting point, cargo transportation destination, cargo type, cargo weight and cargo picture of the target cargo information; Determine the volume of the cargo based on the cargo picture; Determine a freight itinerary based on the freight transportation starting point and the freight transportation destination; Matching a freight vehicle based on the cargo volume, the cargo type, and the cargo weight; A freight order is generated based on the freight itinerary and the freight vehicle.

6. The method according to claim 4 or 5, characterized in that: The determining the volume of the cargo based on the cargo picture includes: Performing point cloud processing on the cargo image to obtain a target point cloud; Determine a bounding box corresponding to the target point cloud; The volume of the bounding box corresponding to the target point cloud is determined as the cargo volume.

7. The method according to claim 4 or 5, characterized in that: The matching of freight vehicles based on the cargo volume, the cargo type and the cargo weight includes: Determine the type of freight vehicle according to the type of goods; Determining the carrying capacity of the freight vehicle according to the weight of the freight; Determining the model of the freight vehicle according to the volume of the cargo; The target freight vehicle for matching the freight order is determined according to the type of the freight vehicle, the carrying capacity of the freight vehicle and the model of the freight vehicle.

8. A freight order generating device, characterized in that: include: A first receiving module, used to receive an order generation instruction input by a target user; The order generation instruction carries a user identifier corresponding to the target user; A judgment module, configured to judge whether the target user is a registered user based on the user identifier in response to the order generation instruction; A first determination module, configured to determine N historical goods information associated with the target user if the target user is a registered user; N is a positive integer; The first generating module is used to generate a freight order based on the input of the N historical cargo information by the target user.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the freight order generating method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the freight order generation method according to any one of claims 1 to 7 are implemented.

Images