CN112651554A - General carrying tool management method and device based on big data cloud platform - Google Patents
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Abstract
The invention provides a general carrying tool management method and device based on a big data cloud platform. The method comprises the following steps: acquiring information of goods to be carried, and acquiring the number of carrying tools to be dispatched according to the information of the goods to be carried; acquiring all the carrying tool information, screening out the carrying tools in an idle state according to the carrying tool information, and recording the number of the carrying tools in the idle state; and comparing the number of the idle state carriers with the number of the carriers to be dispatched, and distributing the idle state carriers according to the comparison result. According to the invention, the idle carrying tools are automatically screened out through carrying goods information, and the running route of the carrying tools is automatically planned according to the positions of the carrying tools and the coordinates of the designated distribution points, so that the management efficiency of the carrying tools is improved.
Description
Technical Field
The invention relates to the technical field of computer software, in particular to a general vehicle management method and device based on a big data cloud platform.
Background
The logistics dealer mainly is the entrusting of receiving the entrusting person, transports the goods of entrusting person to corresponding place through the carrier and is received by the receiver, but before freight, still need distribute the goods to different carriers according to the difference of goods, just can carry out next transportation, also can lead to freight transportation inefficiency because there is not the carrier to arrange simultaneously.
The existing carrier management method is often managed manually, the management mode is not high enough in efficiency, and when the carrier needs to be used, the carrier often does not have enough carrier to be used, and the carrier needs to manually run to a specified position and cannot be automatically parked to the specified position, so that a general carrier management method based on a big data cloud platform is urgently needed to improve the existing carrier management method.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
In view of this, the invention provides a method and a device for managing a universal vehicle based on a big data cloud platform, and aims to solve the technical problem that the management efficiency of the universal vehicle cannot be improved in an automatic driving mode in the prior art.
The technical scheme of the invention is realized as follows:
in one aspect, the invention provides a general vehicle management method based on a big data cloud platform, which comprises the following steps:
s1, acquiring information of goods to be carried, and acquiring the number of carrying tools to be dispatched according to the information of the goods to be carried;
s2, acquiring all the carrier information, screening out the carriers in the idle state according to the carrier information, and recording the number of the carriers in the idle state;
s3, comparing the number of idle vehicles with the number of vehicles to be dispatched, and distributing the idle vehicles according to the comparison result.
On the basis of the foregoing technical solution, preferably, before acquiring information of the cargo to be shipped and acquiring the number of the vehicles to be scheduled according to the information of the cargo to be shipped in step S1, the method further includes the following steps of acquiring local historical information of the cargo to be shipped and corresponding information of the vehicles, where the historical information of the cargo to be shipped includes: the name of the shipment, the number of the shipments, and the category of the shipments, the carrier information includes: and the category of the carrying tools and the quantity of the carrying tools are obtained, a carrying goods classification table is established according to the local historical carrying goods information and the corresponding carrying tool information, the information of the goods to be carried is obtained, and the quantity of the carrying tools to be dispatched is obtained according to the information of the goods to be carried.
On the basis of the above technical scheme, preferably, acquire the information of the goods to be shipped, acquire the number of the tools to be dispatched according to the information of the goods to be shipped, and further include the following steps of acquiring the information of the goods to be shipped, wherein the information of the goods to be shipped includes: the method comprises the steps of classifying information of goods to be carried according to a goods carrying classification table, counting the number of the goods to be carried in each category, and acquiring the number of carrying tools to be scheduled through the goods carrying classification table.
In addition to the above technical solution, preferably, in step S2, acquiring all pieces of vehicle information, screening a vehicle in an idle state according to the pieces of vehicle information, and recording the number of vehicles in the idle state, further includes the following steps of acquiring all pieces of vehicle information, where the pieces of vehicle information include: location information, a current state, and a tool category, the current state including: and idling and carrying, namely screening out the carrying tools in the idling state from the carrying tool information, carrying out classification statistics according to the types of the carrying tools, and recording the number of the carrying tools in each type of the idling state.
On the basis of the foregoing technical solution, preferably, in step S3, comparing the number of idle vehicles with the number of vehicles to be scheduled, and allocating the idle vehicles according to the comparison result, further including the steps of comparing the number of idle vehicles with the number of vehicles to be scheduled, and when the number of idle vehicles is greater than the number of vehicles to be scheduled, allocating the cargo to be shipped to the corresponding vehicle to be scheduled; and when the number of the vehicles in the idle state is less than that of the vehicles to be dispatched, the administrator is fed back that the number of the vehicles in the idle state is insufficient.
On the basis of the above technical solution, preferably, when the number of the carriers in the idle state is greater than the number of the carriers to be scheduled, the cargo to be shipped is allocated to the corresponding carriers to be scheduled, and the method further includes the steps of acquiring a carrier management coordinate when the number of the carriers in the idle state is greater than the number of the carriers to be scheduled, generating an automatic carrier traveling route according to the position information of the carriers and the carrier management coordinate, sending the automatic traveling route to the corresponding carriers in the idle state, recording the traveling route of the carriers in the idle state in real time, and stopping recording when the carriers in the idle state reach the carrier management coordinate.
On the basis of the above technical solution, preferably, the automatic travel route is sent to a corresponding idle-state vehicle, and a travel route of the idle-state vehicle is recorded in real time, and when the idle-state vehicle reaches a vehicle management coordinate, the recording is stopped, and the method further includes the steps of obtaining a local historical travel route, and optimizing the local historical travel route according to the travel route of the idle-state vehicle.
Still further preferably, the big data cloud platform-based universal vehicle management device includes:
the acquisition module is used for acquiring information of goods to be carried and acquiring the number of carrying tools to be scheduled according to the information of the goods to be carried;
the recording module is used for acquiring all the information of the carrying tools, screening out the carrying tools in an idle state according to the information of the carrying tools and recording the number of the carrying tools in the idle state;
and the distribution module is used for comparing the number of the idle-state carrying tools with the number of the carrying tools to be dispatched, and distributing the idle-state carrying tools according to the comparison result.
In a second aspect, the big data cloud platform-based universal vehicle management method further includes an apparatus, including: the system comprises a memory, a processor and a big data cloud platform based general vehicle management method program stored on the memory and capable of running on the processor, wherein the big data cloud platform based general vehicle management method program is configured to realize the steps of the big data cloud platform based general vehicle management method.
In a third aspect, the method for managing a universal vehicle based on a big data cloud platform further includes a medium, where the medium is a computer medium, and a program of the method for managing a universal vehicle based on a big data cloud platform is stored on the computer medium, and when executed by a processor, the method for managing a universal vehicle based on a big data cloud platform implements the steps of the method for managing a universal vehicle based on a big data cloud platform as described above.
Compared with the prior art, the universal vehicle management method based on the big data cloud platform has the following beneficial effects that:
(1) the idle carrying tool information is automatically screened out through carrying cargo information, and the carrying tool information is controlled to automatically reach a driving point, so that the management efficiency of the carrying tool is improved, and the user experience is improved.
(2) Through obtaining the optimization to the route many times, can improve the efficiency that the transport means reaches the management point automatically, the indirect whole transport means management efficiency that has promoted.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of an apparatus in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flowchart of a first embodiment of a method for managing a generic vehicle based on a big data cloud platform according to the present invention;
fig. 3 is a functional module diagram of a first embodiment of a method for managing a generic vehicle based on a big data cloud platform according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the device, and that in actual implementations the device may include more or less components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005 as one medium may include an operating system, a network communication module, a user interface module, and a general vehicle management method program based on a big data cloud platform.
In the device shown in fig. 1, the network interface 1004 is mainly used for establishing a communication connection between the device and a server storing all data required in the big data cloud platform-based universal vehicle management method system; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the big data cloud platform-based universal vehicle management method device may be arranged in the big data cloud platform-based universal vehicle management method device, and the big data cloud platform-based universal vehicle management method device calls the big data cloud platform-based universal vehicle management method program stored in the memory 1005 through the processor 1001 and executes the big data cloud platform-based universal vehicle management method provided by the present invention.
With reference to fig. 2, fig. 2 is a schematic flowchart of a first embodiment of a method for managing a generic vehicle based on a big data cloud platform according to the present invention.
In this embodiment, the method for managing a universal vehicle based on a big data cloud platform includes the following steps:
s10: and acquiring information of the goods to be carried, and acquiring the number of the carrying tools to be dispatched according to the information of the goods to be carried.
It should be understood that, in the embodiment of the present invention, the system may obtain local historical shipment information and corresponding carrier information, where the historical shipment information includes: the name of the shipment, the number of the shipments, and the category of the shipments, the carrier information includes: and the category of the carrying tools and the quantity of the carrying tools are obtained, a carrying goods classification table is established according to the local historical carrying goods information and the corresponding carrying tool information, the information of the goods to be carried is obtained, and the quantity of the carrying tools to be dispatched is obtained according to the information of the goods to be carried.
It should be understood that information of the cargo to be carried is then obtained, the information of the cargo to be carried including: the method comprises the steps of classifying information of goods to be carried according to a goods carrying classification table, counting the number of the goods to be carried in each category, and acquiring the number of carrying tools to be scheduled through the goods carrying classification table.
S20: and acquiring all the carrier information, screening the carriers in the idle state according to the carrier information, and recording the number of the carriers in the idle state.
It should be understood that thereafter, the system will obtain all vehicle information, including: location information, a current state, and a tool category, the current state including: and idling and carrying, namely screening out the carrying tools in the idling state from the carrying tool information, carrying out classification statistics according to the types of the carrying tools, and recording the number of the carrying tools in each type of the idling state.
S30: and comparing the number of the idle state carriers with the number of the carriers to be dispatched, and distributing the idle state carriers according to the comparison result.
It should be understood that, finally, the system will compare the number of the idle-state carriers with the number of the carriers to be scheduled, and when the number of the idle-state carriers is greater than the number of the carriers to be scheduled, allocate the goods to be carried to the corresponding carriers to be scheduled; and when the number of the vehicles in the idle state is less than that of the vehicles to be dispatched, the administrator is fed back that the number of the vehicles in the idle state is insufficient.
It should be understood that, specifically, when the number of the vehicles in the idle state is greater than the number of the vehicles to be scheduled, the vehicle management coordinates are obtained, an automatic vehicle traveling route is generated according to the position information of the vehicle and the vehicle management coordinates, the automatic traveling route is sent to the corresponding vehicle in the idle state, the traveling route of the vehicle in the idle state is recorded in real time, and when the vehicle in the idle state reaches the vehicle management coordinates, the recording is stopped.
It should be appreciated that the system will eventually also obtain a local historical travel route that is optimized based on the travel route of the idle state vehicle.
The above description is only for illustrative purposes and does not limit the technical solutions of the present application in any way.
As can be easily found from the above description, the present embodiment provides a method and an apparatus for managing a universal vehicle based on a big data cloud platform. The method comprises the following steps: acquiring information of goods to be carried, and acquiring the number of carrying tools to be dispatched according to the information of the goods to be carried; acquiring all the carrying tool information, screening out the carrying tools in an idle state according to the carrying tool information, and recording the number of the carrying tools in the idle state; and comparing the number of the idle state carriers with the number of the carriers to be dispatched, and distributing the idle state carriers according to the comparison result. According to the embodiment, the idle carrying tools are automatically screened out through carrying goods information, the running route of the carrying tools is automatically planned according to the positions of the carrying tools and the coordinates of the designated distribution points, and the management efficiency of the carrying tools is improved.
In addition, the embodiment of the invention also provides a general vehicle management device based on the big data cloud platform. As shown in fig. 3, the general vehicle management apparatus based on the big data cloud platform includes: the system comprises an acquisition module 10, a recording module 20 and a distribution module 30.
The acquiring module 10 is used for acquiring information of goods to be carried and acquiring the number of carrying tools to be scheduled according to the information of the goods to be carried;
the recording module 20 is configured to obtain information of all carriers, screen out carriers in an idle state according to the information of the carriers, and record the number of the carriers in the idle state;
and the allocating module 30 is configured to compare the number of idle vehicles with the number of vehicles to be scheduled, and allocate the idle vehicles according to the comparison result.
In addition, it should be noted that the above-described embodiments of the apparatus are merely illustrative, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of the modules to implement the purpose of the embodiments according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may be referred to a general vehicle management method based on a big data cloud platform provided in any embodiment of the present invention, and are not described herein again.
In addition, an embodiment of the present invention further provides a medium, where the medium is a computer medium, and a program of a universal vehicle management method based on a big data cloud platform is stored on the computer medium, and when executed by a processor, the program of the universal vehicle management method based on the big data cloud platform implements the following operations:
s1, acquiring information of goods to be carried, and acquiring the number of carrying tools to be dispatched according to the information of the goods to be carried;
s2, acquiring all the carrier information, screening out the carriers in the idle state according to the carrier information, and recording the number of the carriers in the idle state;
s3, comparing the number of idle vehicles with the number of vehicles to be dispatched, and distributing the idle vehicles according to the comparison result.
Further, when executed by a processor, the big data cloud platform-based universal vehicle management method program further realizes the following operations:
obtaining local historical shipment information and corresponding shipment tool information, wherein the historical shipment information comprises: the name of the shipment, the number of the shipments, and the category of the shipments, the carrier information includes: and the category of the carrying tools and the quantity of the carrying tools are obtained, a carrying goods classification table is established according to the local historical carrying goods information and the corresponding carrying tool information, the information of the goods to be carried is obtained, and the quantity of the carrying tools to be dispatched is obtained according to the information of the goods to be carried.
Further, when executed by a processor, the big data cloud platform-based universal vehicle management method program further realizes the following operations:
acquiring information of goods to be carried, wherein the information of the goods to be carried comprises: the method comprises the steps of classifying information of goods to be carried according to a goods carrying classification table, counting the number of the goods to be carried in each category, and acquiring the number of carrying tools to be scheduled through the goods carrying classification table.
Further, when executed by a processor, the big data cloud platform-based universal vehicle management method program further realizes the following operations:
obtaining all vehicle information, the vehicle information comprising: location information, a current state, and a tool category, the current state including: and idling and carrying, namely screening out the carrying tools in the idling state from the carrying tool information, carrying out classification statistics according to the types of the carrying tools, and recording the number of the carrying tools in each type of the idling state.
Further, when executed by a processor, the big data cloud platform-based universal vehicle management method program further realizes the following operations:
comparing the number of the idle-state carrying tools with the number of the carrying tools to be scheduled, and distributing the goods to be carried to the corresponding carrying tools to be scheduled when the number of the idle-state carrying tools is larger than the number of the carrying tools to be scheduled; and when the number of the vehicles in the idle state is less than that of the vehicles to be dispatched, the administrator is fed back that the number of the vehicles in the idle state is insufficient.
Further, when executed by a processor, the big data cloud platform-based universal vehicle management method program further realizes the following operations:
when the number of the carrying tools in the idle state is larger than that of the carrying tools to be scheduled, obtaining management coordinates of the carrying tools, generating an automatic driving route of the carrying tools according to the position information of the carrying tools and the management coordinates of the carrying tools, sending the automatic driving route to the corresponding carrying tools in the idle state, recording the driving route of the carrying tools in the idle state in real time, and stopping recording when the carrying tools in the idle state reach the management coordinates of the carrying tools.
Further, when executed by a processor, the big data cloud platform-based universal vehicle management method program further realizes the following operations:
and acquiring a local historical driving route, and optimizing the local historical driving route according to the traveling route of the idle-state vehicle.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A general vehicle management method based on a big data cloud platform is characterized by comprising the following steps: comprises the following steps;
s1, acquiring information of goods to be carried, and acquiring the number of carrying tools to be dispatched according to the information of the goods to be carried;
s2, acquiring all the carrier information, screening out the carriers in the idle state according to the carrier information, and recording the number of the carriers in the idle state;
s3, comparing the number of idle vehicles with the number of vehicles to be dispatched, and distributing the idle vehicles according to the comparison result.
2. The big data cloud platform-based universal vehicle management method according to claim 1, wherein: in step S1, before obtaining information of the cargo to be shipped and obtaining the number of the carriers to be scheduled according to the information of the cargo to be shipped, the method further includes the following steps of obtaining local historical information of the cargo to be shipped and corresponding information of the carriers, where the historical information of the cargo to be shipped includes: the name of the shipment, the number of the shipments, and the category of the shipments, the carrier information includes: and the category of the carrying tools and the quantity of the carrying tools are obtained, a carrying goods classification table is established according to the local historical carrying goods information and the corresponding carrying tool information, the information of the goods to be carried is obtained, and the quantity of the carrying tools to be dispatched is obtained according to the information of the goods to be carried.
3. The big data cloud platform-based universal vehicle management method according to claim 2, wherein: the method comprises the steps of obtaining information of goods to be carried, obtaining the number of carrying tools to be dispatched according to the information of the goods to be carried, and obtaining the information of the goods to be carried, wherein the information of the goods to be carried comprises the following steps: the method comprises the steps of classifying information of goods to be carried according to a goods carrying classification table, counting the number of the goods to be carried in each category, and acquiring the number of carrying tools to be scheduled through the goods carrying classification table.
4. The big data cloud platform-based universal vehicle management method according to claim 3, wherein: in step S2, acquiring all pieces of carrier information, screening out carriers in an idle state according to the pieces of carrier information, and recording the number of carriers in the idle state, further including the following steps of acquiring all pieces of carrier information, where the pieces of carrier information include: location information, a current state, and a tool category, the current state including: and idling and carrying, namely screening out the carrying tools in the idling state from the carrying tool information, carrying out classification statistics according to the types of the carrying tools, and recording the number of the carrying tools in each type of the idling state.
5. The big data cloud platform-based universal vehicle management method according to claim 4, wherein: in step S3, comparing the number of idle carriers with the number of carriers to be scheduled, and allocating the carriers in the idle state according to the comparison result, further including the steps of comparing the number of idle carriers with the number of carriers to be scheduled, and allocating the cargo to be shipped to the corresponding carriers to be scheduled when the number of idle carriers is greater than the number of carriers to be scheduled; and when the number of the vehicles in the idle state is less than that of the vehicles to be dispatched, the administrator is fed back that the number of the vehicles in the idle state is insufficient.
6. The big data cloud platform-based universal vehicle management method according to claim 5, wherein: when the number of the carrying tools in the idle state is larger than that of the carrying tools to be dispatched, distributing the goods to be carried to the corresponding carrying tools to be dispatched.
7. The big data cloud platform-based universal vehicle management method according to claim 6, wherein: and sending the automatic running route to a corresponding idle-state carrier, recording the running route of the idle-state carrier in real time, and stopping recording when the idle-state carrier reaches a carrier management coordinate.
8. A big data cloud platform-based universal vehicle management device is characterized by comprising:
the acquisition module is used for acquiring information of goods to be carried and acquiring the number of carrying tools to be scheduled according to the information of the goods to be carried;
the recording module is used for acquiring all the information of the carrying tools, screening out the carrying tools in an idle state according to the information of the carrying tools and recording the number of the carrying tools in the idle state;
and the distribution module is used for comparing the number of the idle-state carrying tools with the number of the carrying tools to be dispatched, and distributing the idle-state carrying tools according to the comparison result.
9. An apparatus, characterized in that the apparatus comprises: a memory, a processor, and a big data cloud platform based generic vehicle management method program stored on the memory and executable on the processor, the big data cloud platform based generic vehicle management method program configured to implement the steps of the big data cloud platform based generic vehicle management method of any of claims 1 to 7.
10. A medium, which is a computer medium, wherein the computer medium stores thereon a big data cloud platform-based universal vehicle management method program, and when the big data cloud platform-based universal vehicle management method program is executed by a processor, the method of implementing the big data cloud platform-based universal vehicle management method according to any one of claims 1 to 7 is performed.
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| CN102496096A (en) * | 2011-11-25 | 2012-06-13 | 深圳市赛格导航科技股份有限公司 | High-efficient logistic scheduling system and method |
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