CN111008756A - Transportation scheduling method, system and computer readable storage medium - Google Patents
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Abstract
The invention discloses a transportation scheduling method, a transportation scheduling system and a computer readable storage medium, which belong to the technical field of logistics scheduling and comprise the following steps: s1, the intelligent sensing front end acquires real-time data of the goods and uploads the real-time data to the data analysis platform; s2, the data analysis platform receives the data uploaded by the intelligent sensing front end, and is in butt joint with the information transmitted by the preset interface to generate fused cargo data, and whether the abnormality exists is judged; s3, if there is abnormity, identifying the abnormity, generating an abnormal data packet, uploading to the fault processing platform, if there is no abnormity, classifying the fused goods data according to the preset stage, and transmitting the classified goods type data to the data display platform; and S4, the data display platform receives and outputs the data transmitted by the data analysis platform. According to the invention, each sensor module is integrated into a large system, so that the dispatching of logistics transportation is realized, and the movement of logistics and the damage condition of the package label can be displayed in time.
Description
Technical Field
The invention relates to the technical field of logistics scheduling, in particular to a transportation scheduling method, a transportation scheduling system and a computer readable storage medium.
Background
With the continuous development of society, people select goods from short distance to the present world, but along with the selection, the demand of goods logistics industry is increasing. Many emerging technologies are gradually moving from laboratories to commercial applications, and scientific technologies are also becoming important supports in logistics. In each link of storage, transportation and delivery in the commodity circulation, the development of pressing close to of scientific and technological for the efficiency of commodity circulation constantly improves, but along with the stable growth of international trade at present, more past wisdom commodity circulation direction development of commodity circulation industry. Along with the rapid rise of the E-commerce as a new bright spot, most people select channels such as online shopping and international shopping, and then the commodity circulation industry is driven to rapidly rise, the wrapping amount and the workload and the management difficulty of commodity circulation workers are greatly increased, the flexibility, the informatization and the intellectualization of the E-commerce logistics storage center sorting system cannot be realized, and the completeness of the wrapping is difficult to ensure in the actual logistics process.
In the current technology, a logistics system cannot meet the increasing development of people for the logistics industry, and although a logistics state monitoring method and a logistics state monitoring system based on multi-sensor fusion exist at present, each sensor module is integrated into a large system, so that the technology for realizing transportation scheduling is deficient. In cross-border logistics, due to the problem of network protocols, the cross-country data interaction speed is low, and when goods are damaged in the transportation process, the logistics flow direction cannot be displayed in time.
Disclosure of Invention
The invention aims to solve the technical problem that the flow direction tracking is not timely in the prior art, and the transportation scheduling method and the transportation scheduling system integrate all sensor modules into a large system, thereby realizing the scheduling of logistics transportation. In cross-border logistics, the logistics trend and the damage condition of the package label can be displayed in time.
In order to achieve the above purpose, the invention provides the following technical scheme:
in one aspect, the invention provides a transportation scheduling method, which specifically comprises the following steps: s1, the intelligent sensing front end acquires real-time data of the goods and uploads the real-time data of the goods to a data analysis platform; s2, the data analysis platform receives the real-time goods data uploaded by the intelligent sensing front end, butt joints the real-time goods data with information transmitted by a preset interface to generate fused goods data, and judges whether the fused goods data are abnormal or not; s3, if there is abnormity, identifying the abnormity, generating an abnormal data packet, uploading the abnormal data packet to a fault processing platform, if there is no abnormity, classifying the fused cargo data according to a preset stage, and transmitting the classified cargo type data to a data display platform; and S4, the data display platform receives the goods type data transmitted by the data analysis platform and outputs and displays the goods type data.
Further, the real-time cargo data comprises cargo label data and cargo position data.
Further, the preset interface comprises a storage platform interface, a market platform interface and a transportation logistics interface.
Further, the preset stages include a first stage of warehouse operation, a second stage of cargo logistics, and a third stage of cargo distribution.
On the other hand, the invention also provides a transportation scheduling system, which comprises an intelligent sensing front end, a data analysis platform, a fault processing platform and a data display platform; the intelligent sensing front end is used for acquiring real-time data of goods and uploading the real-time data of the goods to the data analysis platform; the data analysis platform is used for receiving the real-time goods data uploaded by the intelligent sensing front end, butting the real-time goods data with information transmitted by a preset interface to generate fused goods data, judging whether the fused goods data are abnormal or not, identifying abnormal conditions if the fused goods data are abnormal, generating abnormal data packets and uploading the abnormal data packets to the fault processing platform; if no abnormity exists, classifying the fused goods data according to a preset stage, and transmitting the classified goods type data to a data display platform; the fault processing platform is used for receiving the abnormal data packet uploaded by the data analysis platform, processing the abnormal data packet and transmitting a processing result to the data display platform; and the data display platform is used for receiving the goods type data transmitted by the data analysis platform and the data transmitted by the fault processing platform and outputting and displaying the goods type data.
Further, the intelligent sensing front end comprises a wireless sensor, and the wireless sensor is used for acquiring indoor logistics information and outdoor logistics information of remote logistics and judging the position of the goods.
Further, wireless sensor includes bluetooth module, GPS orientation module, mobile network module and wiFi module, bluetooth module is used for indoor location, and GPS module is used for outdoor location, and WIFI module and mobile network module are used for supplementary indoor location and outdoor location.
Further, the data analysis platform comprises a communication module, a format conversion module, a processing module and a message generation module, wherein the communication module is used for transmitting data with the intelligent sensing front end and the data display platform, the format conversion module is used for converting the format of the received data, the processing module is used for processing the data, and the message generation module is used for generating corresponding data required by the next module.
Further, the data display platform comprises a data receiving module, a data output module and a data display module, the data receiving module is used for receiving the cargo type data transmitted by the data analysis platform, the data output module is used for outputting the cargo type data, and the data display module is used for performing integrated display on the output data.
Meanwhile, the present invention also provides a computer-readable storage medium storing a computer program, which when executed by a processor implements the steps in the method as described above.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the system and the computer readable storage medium provided by the invention, each sensor module is integrated into a large system, so that the dispatching of logistics transportation is realized, and each terminal can display the logistics trend and the damage condition of the package label in time. Particularly, due to the problem of cross-border logistics network protocol, the communication is not timely, and the logistics direction and the damage condition of the package label can be timely displayed by each terminal by adopting the method and the system. The technical problem of rapid display through the fault processing platform when the goods label is abnormal in the dispatching process can be solved, the personnel can more timely handle abnormal conditions in cross-border logistics for related work, and greater loss is avoided.
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FIG. 1 is a schematic flow chart of a transportation scheduling method according to the present invention;
FIG. 2 is a schematic diagram of a transportation scheduling system according to the present invention;
FIG. 3 is a detailed block diagram of a transportation scheduling system according to the present invention;
FIG. 4 is a diagram of a preferred architecture of the intelligent sensing front end of a transportation scheduling system of the present invention;
fig. 5 is a preferred block diagram of a transportation scheduling system of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and embodiments. It should be understood that the scope of the above-described subject matter is not limited to the following examples, and any techniques implemented based on the disclosure of the present invention are within the scope of the present invention.
RFID is one of the key basic technologies of the Internet of things, and the RFID label is applied to the fields of commodity storage and logistics, can provide static information of commodities, and can also provide dynamic information such as the positions of the commodities and the surrounding temperature and humidity, so that the intelligent variation degree of the RFID label is greatly improved.
Example 1
The invention discloses a transportation scheduling method, a transportation scheduling system and a computer readable storage medium, and the specific implementation mode is as follows as well known:
fig. 1 is a flow diagram illustrating a transportation scheduling method according to an example embodiment. Referring to fig. 1, a transportation scheduling method of the present embodiment includes the following steps:
and step S1, the intelligent sensing front end acquires real-time data of the goods and uploads the real-time data of the goods to the data analysis platform.
The real-time goods data comprise goods label data and goods position data. For each item, an RFID tag is mounted thereon. In the process of automatically identifying the goods, the data stored in the RFID tag can be identified, and the stored data is information of the goods, such as the name and type of the goods, or addresses of both the sender and the receiver, and telephone, etc. Preferably, the RFID is a semi-active RFID tag. In a large range covered by a high-frequency signal, a plurality of low-frequency readers are arranged at different positions for activating semi-active RFID products, so that the positioning of goods is completed, and the acquisition and transmission of information are realized. Here, the low frequency reader may be installed in the warehouse to facilitate locating the goods in the warehouse.
The purpose of collecting real-time data of goods is to know the position of goods at corresponding time. It is convenient to have an accurate location to the position that goods are located. After the real-time data of the corresponding goods are acquired, the acquired real-time data of the goods are uploaded to a data analysis platform, and the next step of operation is carried out.
And step S2, the data analysis platform receives the real-time goods data uploaded by the intelligent sensing front end, butt joints the real-time goods data with information transmitted by a preset interface to generate fused goods data, and judges whether the fused goods data is abnormal or not.
The data analysis platform is used for butt-jointing the real-time goods data uploaded from the intelligent sensing front end with the warehousing platform interface, the market platform interface and the transportation logistics interface to generate fused goods data and judging whether the fused goods data is abnormal or not. If the goods are lost or the data are lost and the related data cannot be acquired, the acquired fused goods data is abnormal.
And step S3, if the abnormal condition exists, the abnormal condition is identified, an abnormal data packet is generated and uploaded to the fault processing platform, if the abnormal condition does not exist, the fused goods data is classified according to the preset stage, and the classified goods type data is transmitted to the data display platform.
And if the abnormality exists, identifying the specific abnormal condition. Identifying abnormal conditions includes data loss, data anomalies, and data duplication. The data loss means that the fused goods data cannot be received, for example, the package is lost in the middle; the data abnormality means that the data is obviously inconsistent with the preset time and place and the reason of the abnormality is not noted; data repetition is the occurrence of data repetition multiple times. And after the abnormal condition is identified, an abnormal data packet is generated and uploaded to a fault analysis platform, so that the personnel responsible for the related work can conveniently and quickly check the abnormal data packet.
If the abnormal condition does not exist, classifying the fused goods data according to the stage where the fused goods data are located, wherein the preset stages are a first stage, a second stage and a third stage. The first stage is that the goods are in the warehouse, including the goods warehouse-in, the goods storage in the warehouse and the goods warehouse-out; the second stage is that the goods are in the logistics stage, including that the goods are in transportation and in a certain transfer station, and since the stage is the prior art, redundant description is not repeated here; the third phase is a cargo distribution phase, which comprises the distance of the cargo from the destination and the predicted arrival time. In the stage, the Dijkstra algorithm is used for determining the arrival time to configure the routing, the scheduling problem is analyzed, and the corresponding data are respectively stored in different working groups, so that the scheduling is convenient.
The goods type data generated by the method comprises information of the specific stage of the goods, the data is subjected to modular processing, the redundancy of complex data is reduced, and different types of data are stored in different working groups. And then the obtained cargo type data is transmitted to a data display platform, and when the cargo is abnormal, the cargo type data can be known in time through a fault analysis platform.
And step S4, the data display platform receives the goods type data transmitted by the data analysis platform and outputs and displays the goods type data.
The goods are output and displayed by the analyzed goods type data, and the output and displayed information comprises basic information of the goods, such as names and types of the goods or addresses, telephones and other information of both sending and receiving parties; address information of the goods, such as position information of the goods which are collected last time; the cargo type data of the cargo is the first, second or third stage.
Through the implementation of the steps of the method, complex data can be processed, information can be displayed more visually, the work of related personnel is facilitated, the labor consumption is reduced, and the logistics speed is increased.
Example 2
Besides the transportation scheduling method provided by the invention, the invention also provides a transportation scheduling system. As shown in fig. 2, the system includes a smart sensor front-end 10, a data analysis platform 20, a fault handling platform 30, and a data display platform 40.
And the intelligent sensing front end 10 is used for acquiring real-time data of the goods and uploading the real-time data of the goods to the data analysis platform 20.
The data analysis platform 20 is used for receiving the real-time cargo data uploaded by the intelligent sensing front end 10, butting the real-time cargo data with information transmitted by a preset interface to generate fused cargo data, judging whether the fused cargo data is abnormal or not, if so, identifying abnormal conditions, generating abnormal data packets, and uploading the abnormal data packets to the fault processing platform; if no abnormity exists, the fused goods data are classified according to a preset stage, and the classified goods type data are transmitted to the data display platform 40.
And the fault processing platform 30 is configured to receive the abnormal data packet uploaded by the data analysis platform 20, receive an instruction for processing the abnormal data packet, process the abnormal data packet, and transmit a processing result to the data display platform 40.
And the data display platform 40 is used for receiving the goods type data transmitted by the data analysis platform 20 and outputting and displaying the goods type data.
The data analysis platform 20 sends the abnormal data packet to the fault processing platform 30, and the fault processing platform 30 displays the fault type in the abnormal data packet analyzed by the data analysis platform 20, and then receives an operation instruction of an operator on the abnormal data packet, such as unprocessed, processed, and other reasons. And then transmitting the received processing result to a data display platform to display the processing result.
The relevant modules provided in the system are used for executing the relevant instructions in the transportation scheduling method, and are not described herein again because they have been described in detail above.
Through this system, integrate each sensor module to a big system to realize transportation scheduling rationalization, the construction is selected flexible automation, intellectuality, when the abnormal conditions appearing, also can the rapid processing reaction.
As shown in fig. 3, the smart front end 10 includes a wireless sensor, and the wireless sensor is used to acquire indoor logistics information and outdoor logistics information of remote logistics, so as to determine the location of the cargo.
Preferably, the wireless sensor comprises a Bluetooth module, a GPS module, a mobile network module and a WIFI module, the Bluetooth module is used for indoor positioning, the GPS module is used for outdoor positioning, and the WIFI module is used for assisting indoor positioning and outdoor positioning. When the goods are in the room, the Bluetooth module and the WIFI module can be started to position the specific positions of the goods, and when the goods are in the outdoor place, the goods are positioned through the GPS module and the mobile network module.
Preferably, as shown in fig. 4, the smart sensor front end 10 is provided with a bluetooth signal module, a vehicle radar module, a vehicle video module, and a switching control main module. The Bluetooth signal module is used for acquiring position data, the vehicle-mounted radar module is used for acquiring distance data, and the vehicle-mounted video module is used for acquiring video data.
Further, the data analysis platform 20 includes a communication module, a format conversion module, a processing module, and a message generation module, where the communication module is used to transmit data with the smart sensor front-end 10 and the data display platform 40, the format conversion module is used to convert the format of the received data, the processing module is used to process the data, and the message generation module is used to generate corresponding data required by the next module.
The fault processing platform 30 includes a data receiving module for receiving the abnormal data packet sent by the data analysis platform 20, a fault display module for displaying the fault type in the abnormal data packet, an instruction receiving module for receiving the operation instruction of the worker, and a communication module for transmitting the received instruction to the data display platform.
The data display platform 40 includes a data receiving module, a data output module and a data display module, the data receiving module is configured to receive the cargo type data transmitted by the data analysis platform 20, the data output module is configured to output the cargo type data, and the data display module is configured to integrate and display the output data.
Preferably, as shown in fig. 5, the system is provided with a sensor module, a reminder module, a first storage module, a first processing module and a first communication module. The sensor module is in the smart sensor front-end 10 for acquiring front-end data. The reminding module is arranged in the data display platform 40 and used for sending reminding information to the user. The first storage module is in the data analysis platform 20 for storing the analyzed related data. The first processing module is in the failure processing platform 30, and is used for processing the related information of the abnormal data packet. The first communication module is used for communication between each module and the platform.
The invention enhances the safety of data interaction, and goods are accurately sensed, tracked and positioned by the RFID label and the Internet of things intelligent sensing technology; the Bluetooth module and the WIFI module are adopted for indoor accurate positioning, and the GPS module and the mobile data module are adopted for outdoor accurate positioning; thereby the technical problems of high cost and low efficiency of the traditional logistics are avoided. The invention integrates each sensor module into a large system, thereby realizing the dispatching of logistics transportation. In cross-border logistics, the logistics trend and the damage condition of the package label can be displayed in time.
Example 3
Meanwhile, the invention also provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and the steps in the method are realized when the computer program is executed by a processor. Since the steps of the method have been described in detail, they are not described in detail herein.
In summary, the above description is only a detailed description of the preferred embodiments of the present invention, and not intended to limit the scope of the present invention. In practical applications, a person skilled in the art can make several modifications according to the technical solution. Any modification, equivalent replacement, partial application, etc. made on the basis of the principle set forth in the present invention shall be included in the scope of protection of the present invention.
Claims (10)
1. A transportation scheduling method is characterized by comprising the following steps:
s1, the intelligent sensing front end acquires real-time data of the goods and uploads the real-time data of the goods to a data analysis platform;
s2, the data analysis platform receives the real-time goods data uploaded by the intelligent sensing front end, butt joints the real-time goods data with information transmitted by a preset interface to generate fused goods data, and judges whether the fused goods data are abnormal or not;
s3, if there is abnormity, identifying the abnormity, generating an abnormal data packet, uploading the abnormal data packet to a fault processing platform, if there is no abnormity, classifying the fused cargo data according to a preset stage, and transmitting the classified cargo type data to a data display platform;
and S4, the data display platform receives the goods type data transmitted by the data analysis platform and outputs and displays the goods type data.
2. The transportation scheduling method of claim 1, wherein the real-time cargo data comprises cargo tag data and cargo location data.
3. The transportation scheduling method of claim 1, wherein the predetermined interface comprises a warehousing platform interface, a shopping mall platform interface and a transportation logistics interface.
4. The transportation scheduling method of claim 1, wherein the preset phases include a first phase of warehouse operations, a second phase of cargo logistics, and a third phase of cargo distribution.
5. A transportation scheduling system is characterized by comprising an intelligent sensing front end, a data analysis platform, a fault processing platform and a data display platform;
the intelligent sensing front end is used for acquiring real-time data of goods and uploading the real-time data of the goods to the data analysis platform;
the data analysis platform is used for receiving the real-time goods data uploaded by the intelligent sensing front end, butting the real-time goods data with information transmitted by a preset interface to generate fused goods data, judging whether the fused goods data are abnormal or not, identifying abnormal conditions if the fused goods data are abnormal, generating abnormal data packets and uploading the abnormal data packets to the fault processing platform; if no abnormity exists, classifying the fused goods data according to a preset stage, and transmitting the classified goods type data to a data display platform;
the fault processing platform is used for receiving the abnormal data packet uploaded by the data analysis platform, receiving an instruction for processing the abnormal data packet, processing the abnormal data packet and transmitting a processing result to the data display platform;
and the data display platform is used for receiving the goods type data transmitted by the data analysis platform and the data transmitted by the fault processing platform and outputting and displaying the goods type data.
6. The transportation scheduling system of claim 5, said intelligent sensing front end comprising wireless sensors for obtaining indoor logistics information and outdoor logistics information of remote logistics and determining where the cargo is located.
7. The transportation scheduling system of claim 6 wherein the wireless sensor comprises a bluetooth module, a GPS positioning module, a mobile network module, and a WiFi module, the bluetooth module being used for indoor positioning, the GPS module being used for outdoor positioning, and the WiFi module and the mobile network module being used to assist in indoor positioning and outdoor positioning.
8. The transportation scheduling system of claim 5, wherein the data analysis platform comprises a communication module for communicating data with the smart aware front-end and the data display platform, a format conversion module for converting the format of the received data, a processing module for processing the data, and a message generation module for generating corresponding data required by a next module.
9. The transportation scheduling system of claim 5, wherein the data display platform comprises a data receiving module, a data output module and a data display module, the data receiving module is configured to receive the cargo type data transmitted by the data analysis platform, the data output module is configured to output the cargo type data, and the data display module is configured to perform integrated display on the output data.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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| CN113344468B (en) * | 2021-07-28 | 2024-01-26 | 厦门海晟融创信息技术有限公司 | Industrial big data-based process quality control analysis platform |
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