CN116485304A - Logistics rapid distribution analysis system based on intelligent logistics - Google Patents
Logistics rapid distribution analysis system based on intelligent logistics Download PDFInfo
- Publication number
- CN116485304A CN116485304A CN202310534938.0A CN202310534938A CN116485304A CN 116485304 A CN116485304 A CN 116485304A CN 202310534938 A CN202310534938 A CN 202310534938A CN 116485304 A CN116485304 A CN 116485304A
- Authority
- CN
- China
- Prior art keywords
- congestion
- logistics
- time point
- point
- route data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0835—Relationships between shipper or supplier and carriers
- G06Q10/08355—Routing methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
Landscapes
- Business, Economics & Management (AREA)
- Economics (AREA)
- Engineering & Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Marketing (AREA)
- Accounting & Taxation (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Human Resources & Organizations (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a logistics rapid distribution analysis system based on intelligent logistics, which relates to the technical field of logistics distribution, and solves the technical problems that the distribution time of a freight vehicle is prolonged and the logistics distribution progress is influenced when the transportation route is not analyzed and confirmed and the transportation route is blocked, the corresponding congestion road section and the corresponding congestion time point are determined according to specific route data, the departure time point of the corresponding vehicle is confirmed later, the specific time point of the congestion road section is analyzed under the normal running state of the vehicle according to the normal speed of the vehicle, when the specific time point is determined to belong to the corresponding congestion time point, the departure point is required to be adjusted if the congestion time point belongs to the corresponding point, the congestion time point is avoided, and the method can reduce the time delay caused by external factors in the logistics distribution process and improve the overall distribution efficiency in the logistics distribution process.
Description
Technical Field
The invention belongs to the technical field of logistics distribution, and particularly relates to a logistics rapid distribution analysis system based on intelligent logistics.
Background
The intelligent logistics is a modern logistics mode for realizing the fine, dynamic and visual management of each link of logistics through intelligent technical means such as intelligent software and hardware, the Internet of things and big data, improving the intelligent analysis decision and the automatic operation execution capacity of a logistics system and improving the logistics operation efficiency.
The invention discloses a logistics rapid distribution analysis system based on intelligent logistics, which belongs to the technical field of intelligent logistics, provides animation display for the placement of an express according to the internal form of a compartment of an express cabinet, can be transmitted to an express end, and is more beneficial to placing multiple express items of the same addressee in the same compartment after an emergency dispatch unit is started, so that the time waste caused by subjective judgment of the express is reduced, and meanwhile, damage caused by strong plugs to the express items is prevented.
In the process of logistics dispatch, the intelligent logistics generally adopts a designated freight vehicle to dispatch the logistics according to the determined destination, and the corresponding logistics is transported to the designated point, but in the actual dispatch process, the transportation route of the freight vehicle is not analyzed and confirmed, so that when the transportation route has traffic jam, the dispatch time of the freight vehicle is prolonged, and the logistics dispatch progress is affected.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art; therefore, the invention provides a logistics rapid distribution analysis system based on intelligent logistics, which is used for solving the technical problems that the distribution time of a freight vehicle is prolonged and the logistics distribution progress is influenced when the transportation route of the freight vehicle is not analyzed and confirmed and the traffic jam condition exists in the transportation route.
In order to achieve the above objective, according to an embodiment of the first aspect of the present invention, a rapid logistics distribution analysis system based on smart logistics is provided, which includes an order center, a display terminal, a logistics distribution center and a cloud;
the logistics distribution center comprises a distribution route confirmation unit, an adjustment unit, a route data analysis unit, a destination confirmation unit and a self-adaptive planning unit;
the order center is used for operating by external operators and transmitting the confirmed logistics distribution order to the logistics distribution center;
the delivery route confirmation unit is used for receiving the confirmed logistics delivery order, confirming a departure point and a destination point from the logistics delivery order, confirming a delivery route according to the departure point and the destination point, and transmitting the confirmed delivery route to the route data analysis unit;
the route data analysis unit acquires route data of the delivery route from the cloud according to the confirmed delivery route, analyzes the route data, confirms a congestion period, confirms an optimal fit delivery point by combining and analyzing a departure time point of a logistics delivery order and the congestion period, and transmits the confirmed optimal fit delivery point to the adjustment unit.
Further, the specific way of the route data analysis unit for analyzing the route data is as follows:
acquiring a large amount of route data belonging to the distribution route from the cloud, marking the route data belonging to the working day as one type of route data, and marking the route data not belonging to the working day as two types of route data;
from a large amount of route data, confirming the congestion road section in the route data, wherein the congestion road section is a certain road section in the route data, and the confirmation mode is as follows: recording the occurrence times of the same congestion road section, marking the same congestion road section as CS, obtaining the total recording times of route data, marking the same as SS, obtaining a comparison parameter BD by CS/SS=BD, comparing the comparison parameter BD with a preset value Y1, and when BD is less than Y1, not confirming, otherwise, marking the corresponding road section as the congestion road section, recording the specific congestion time point of the congestion road section, extracting the time point of the initial congestion time point and the time point of the congestion ending from a large number of recorded congestion time points, which is equivalent to extracting the maximum value and the minimum value, and constructing a working day congestion time interval by the time point of the initial congestion time point and the time point of the congestion ending;
confirming a congestion road section appearing in the route data from a large amount of second-class route data, recording specific congestion time points of the congestion road section, extracting the most initial congestion time point and the time point of ending the congestion from the recorded large amount of congestion time points, namely extracting the maximum value and the minimum value, and constructing a non-working day congestion time interval by the first congestion time point and the time point of ending the congestion;
confirming a departure time point of a logistics distribution order, analyzing a specific time point when a corresponding vehicle arrives at a congestion road section according to a normal vehicle speed, and setting the time point as a time point to be changed to confirm whether a departure day is a working day or not:
if the time point is a working day, analyzing whether the time point to be changed is located in a working day congestion time interval, if the time point is a working day congestion time interval, generating an adjusting signal, transmitting the adjusting signal into an adjusting unit, and if the time point is not the working day congestion time interval, not performing any processing;
if the time point does not belong to the working day, whether the time point to be changed is located in the congestion time interval of the non-working day is analyzed, if the time point belongs to the interval, an adjusting signal is generated and transmitted to an adjusting unit, and if the time point does not belong to the interval, no processing is performed.
Preferably, the adjusting unit receives the point in time to be changed and the adjusting signal, and provides the external operator with self-adjustment to trim the departure point in time of the vehicle.
Preferably, the destination confirmation unit confirms a plurality of logistics fast forwarding belonging to the same park, and transmits the confirmed logistics express information to the self-adaptive planning unit.
Preferably, the self-adaptive planning unit obtains a destination warehouse layout corresponding to the park from the park according to the confirmed logistics express information, and performs self-adaptive planning on the dispatch mode of the dispatched objects, and the specific mode is as follows:
confirming a designated park from the logistics express information, and acquiring a destination warehouse layout of the park from the cloud;
according to the destination warehouse layout, taking a park entrance as an initial point, confirming position information of different dispatch objects from a plurality of logistics express information, confirming a group of dispatch objects closest to the initial point according to the position information, searching a group of dispatch objects closest to the next group by taking the confirmed dispatch objects as the initial point, and so on, and constructing a group of dispatch tables;
and transmitting the constructed dispatch table to a display terminal for display, so that a logistics dispatcher can complete logistics dispatch in the shortest time.
Compared with the prior art, the invention has the beneficial effects that: determining a corresponding congestion road section and a corresponding congestion time point according to specific route data, subsequently confirming a departure time point of a corresponding vehicle, analyzing the specific time point of the congestion road section when the vehicle arrives in a normal running state according to the normal speed of the vehicle, and when the specific time point arrives is determined to belong to the corresponding congestion time point, if the congestion time point belongs to the corresponding point, adjusting the departure point to avoid the congestion time point;
according to the position information of the logistics and the destination warehouse layout diagram, and the dispatch table is generated, dispatch is performed sequentially, so that the situation of disordered dispatch is avoided, dispatch efficiency can be improved, and dispatch time is reduced.
Drawings
Fig. 1 is a schematic diagram of a principle frame of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, the present application provides a logistics rapid distribution analysis system based on intelligent logistics, which includes an order center, a display terminal, a logistics distribution center and a cloud end;
the order center is electrically connected with the input end of the logistics distribution center, and the logistics distribution center is electrically connected with the input end of the display terminal;
the logistics distribution center comprises a distribution route confirmation unit, an adjustment unit, a route data analysis unit, a destination confirmation unit and an adaptive planning unit, wherein the distribution route confirmation unit is electrically connected with the input end of the route data analysis unit, the route data analysis unit is electrically connected with the input end of the adjustment unit, the destination confirmation unit is electrically connected with the input end of the adaptive planning unit, and the cloud end is electrically connected with the input end of the adaptive planning unit;
the order center is used for operating by external operators and transmitting the confirmed logistics distribution order to the logistics distribution center;
the distribution route confirmation unit in the logistics distribution center receives the confirmed logistics distribution order, confirms a starting point and a destination point from the logistics distribution order, confirms a distribution route according to the starting point and the destination point, and transmits the confirmed distribution route to the route data analysis unit;
the route data analysis unit obtains route data of the delivery route from the cloud according to the confirmed delivery route, analyzes the route data, confirms a congestion period, confirms an optimal fit delivery point by combining and analyzing a departure time point of a logistics delivery order and the congestion period, and transmits the confirmed optimal fit delivery point to the adjustment unit, and particularly obtains route data of a past day, wherein the route data comprises a congestion section and a congestion duration of the section, and the specific analysis mode is as follows:
obtaining a large amount of route data belonging to the delivery route from the cloud, marking the route data belonging to the working day as one type of route data, marking the route data not belonging to the working day as two types of route data, and particularly, distinguishing and analyzing are needed because the congestion conditions are different during the working day and the non-working day, so that the confirmed congestion route is more accurate in different time;
from a large amount of route data, confirming the congestion road section in the route data, wherein the congestion road section is a certain road section in the route data, and the confirmation mode is as follows: recording the occurrence times of the same congestion road section, marking the same congestion road section as CS, obtaining the total recording times of route data, marking the same congestion road section as SS, wherein one group of periods represents one time, each group of periods is separated by 24 hours, the CS/SS=BD is adopted to obtain a comparison parameter BD, the comparison parameter BD is compared with a preset value Y1, wherein the specific value of Y1 is drawn by an operator according to experience, when BD is less than Y1, the corresponding road section is not confirmed, otherwise, the corresponding road section is marked as the congestion road section, the specific congestion time point of the congestion road section is recorded, the time point of the initial congestion time point and the time point of the congestion ending are extracted from the recorded mass congestion time points, the time point of the congestion ending is equivalent to the extraction of the maximum value and the minimum value, and the time point of the congestion ending is used for constructing a working day congestion time interval;
confirming a congestion road section appearing in the route data from a large amount of second-class route data, recording specific congestion time points of the congestion road section, extracting the most initial congestion time point and the time point of ending the congestion from the recorded large amount of congestion time points, namely extracting the maximum value and the minimum value, and constructing a non-working day congestion time interval by the first congestion time point and the time point of ending the congestion;
specifically, according to specific route data, determining a corresponding congestion road section and a corresponding congestion time point, subsequently, confirming a departure time point of a corresponding vehicle, analyzing a specific time point when the vehicle arrives at the congestion road section in a normal running state according to the normal speed of the vehicle, and when the specific time point arrives is determined to belong to the corresponding congestion time point, if the congestion time point belongs to the corresponding point, adjusting the departure point to avoid the congestion time point, wherein in the way, time delay caused by external factors can be reduced in the logistics dispatching process, the logistics dispatching efficiency is improved, and the overall effect in the logistics dispatching process is improved;
confirming a departure time point of a logistics distribution order, analyzing a specific time point when a corresponding vehicle arrives at a congestion road section according to a normal vehicle speed, and setting the time point as a time point to be changed to confirm whether a departure day is a working day or not:
if the time point is a working day, analyzing whether the time point to be changed is located in a working day congestion time interval, if the time point is a working day congestion time interval, generating an adjusting signal, transmitting the adjusting signal into an adjusting unit, and if the time point is not the working day congestion time interval, not performing any processing;
if the time point does not belong to the working day, whether the time point to be changed is located in the congestion time interval of the non-working day is analyzed, if the time point belongs to the interval, an adjusting signal is generated and transmitted to an adjusting unit, and if the time point does not belong to the interval, no processing is performed.
The adjusting unit receives the time point to be changed and the adjusting signal, and is used for an external operator to adjust the time point to be changed and the adjusting signal by himself, and the adjusting unit is used for trimming the departure time point of the vehicle to avoid the congestion time interval as far as possible.
Example two
In the implementation process of this embodiment, compared to the first embodiment, the embodiment includes the first embodiment, which is specifically different in that:
the destination confirming unit confirms a plurality of logistics express belonging to the same park, and transmits the confirmed logistics express information into the self-adaptive planning unit;
the self-adaptive planning unit is used for carrying out self-adaptive planning on the dispatch mode of the distributed objects according to the confirmed logistics express information and acquiring a destination warehouse layout corresponding to the park from the park, wherein the specific mode for carrying out self-adaptive planning is as follows:
confirming a designated park from the logistics express information, and acquiring a destination warehouse layout of the park from the cloud;
according to the destination warehouse layout, taking a park entrance as an initial point, confirming position information of different dispatch objects from a plurality of logistics express information, confirming a group of dispatch objects closest to the initial point according to the position information, searching a group of dispatch objects closest to the next group by taking the confirmed dispatch objects as the initial point, and so on, and constructing a group of dispatch tables;
and transmitting the constructed dispatch table to a display terminal for display, so that a logistics dispatcher can complete logistics dispatch in the shortest time.
Specifically, when the logistics dispatcher in the corresponding area performs logistics dispatching, the logistics dispatcher needs to dispatch the logistics to the designated place according to the position information of the logistics, although the logistics dispatcher is familiar with the area, in the designated park, the arrangement of the destination warehouse belongs to a chaotic state and is not in a regular state, so that the logistics dispatching efficiency is affected, if the dispatching is sequentially performed in a mode of generating a dispatching table, the situation of chaotic dispatching is avoided, so that the dispatching efficiency can be improved, and the dispatching time is reduced.
The partial data in the formula are all obtained by removing dimension and taking the numerical value for calculation, and the formula is a formula closest to the real situation obtained by simulating a large amount of collected data through software; the preset parameters and the preset threshold values in the formula are set by those skilled in the art according to actual conditions or are obtained through mass data simulation.
The working principle of the invention is as follows: determining a corresponding congestion road section and a corresponding congestion time point according to specific route data, subsequently confirming a departure time point of a corresponding vehicle, analyzing the specific time point of the congestion road section when the vehicle arrives in a normal running state according to the normal speed of the vehicle, and when the specific time point arrives is determined to belong to the corresponding congestion time point, if the congestion time point belongs to the corresponding point, adjusting the departure point to avoid the congestion time point;
according to the position information of the logistics and the destination warehouse layout diagram, and the dispatch table is generated, dispatch is performed sequentially, so that the situation of disordered dispatch is avoided, dispatch efficiency can be improved, and dispatch time is reduced.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (6)
1. The logistics rapid distribution analysis system based on the intelligent logistics is characterized by comprising an order center, a display terminal, a logistics distribution center and a cloud;
the logistics distribution center comprises a distribution route confirmation unit, an adjustment unit, a route data analysis unit, a destination confirmation unit and a self-adaptive planning unit;
the order center is used for operating by external operators and transmitting the confirmed logistics distribution order to the logistics distribution center;
the delivery route confirmation unit is used for receiving the confirmed logistics delivery order, confirming a departure point and a destination point from the logistics delivery order, confirming a delivery route according to the departure point and the destination point, and transmitting the confirmed delivery route to the route data analysis unit;
the route data analysis unit acquires route data of the delivery route from the cloud according to the confirmed delivery route, analyzes the route data, confirms a congestion period, confirms an optimal fit delivery point by combining and analyzing a departure time point of a logistics delivery order and the congestion period, and transmits the confirmed optimal fit delivery point to the adjustment unit.
2. The rapid logistics distribution analysis system based on intelligent logistics according to claim 1, wherein the route data analysis unit analyzes route data in the following specific ways:
acquiring a large amount of route data belonging to the distribution route from the cloud, marking the route data belonging to the working day as one type of route data, and marking the route data not belonging to the working day as two types of route data;
from a large amount of route data, confirming the congestion road section in the route data, wherein the congestion road section is a certain road section in the route data, and the confirmation mode is as follows: recording the occurrence times of the same congestion road section, marking the same congestion road section as CS, obtaining the total recording times of route data, marking the same as SS, obtaining a comparison parameter BD by CS/SS=BD, comparing the comparison parameter BD with a preset value Y1, and when BD is less than Y1, not confirming, otherwise, marking the corresponding road section as the congestion road section, recording the specific congestion time point of the congestion road section, extracting the time point of the initial congestion time point and the time point of the congestion ending from a large number of recorded congestion time points, which is equivalent to extracting the maximum value and the minimum value, and constructing a working day congestion time interval by the time point of the initial congestion time point and the time point of the congestion ending;
confirming a congestion road section appearing in the route data from a large amount of second-class route data, recording specific congestion time points of the congestion road section, extracting the most initial congestion time point and the time point of ending the congestion from the recorded large amount of congestion time points, namely extracting the maximum value and the minimum value, and constructing a non-working day congestion time interval by the first congestion time point and the time point of ending the congestion;
confirming a departure time point of a logistics distribution order, analyzing a specific time point when a corresponding vehicle arrives at a congestion road section according to a normal vehicle speed, and setting the time point as a time point to be changed to confirm whether a departure day is a working day or not:
if the time point is a working day, analyzing whether the time point to be changed is located in a working day congestion time interval, if the time point is a working day congestion time interval, generating an adjusting signal, transmitting the adjusting signal into an adjusting unit, and if the time point is not the working day congestion time interval, not performing any processing;
if the time point does not belong to the working day, whether the time point to be changed is located in the congestion time interval of the non-working day is analyzed, if the time point belongs to the interval, an adjusting signal is generated and transmitted to an adjusting unit, and if the time point does not belong to the interval, no processing is performed.
3. The rapid logistics distribution analysis system based on intelligent logistics according to claim 2, wherein the adjusting unit receives the point in time to be changed and the adjusting signal, and allows an external operator to adjust the point in time to be changed and the point in time to be set up.
4. The intelligent logistics rapid distribution analysis system based on logistics according to claim 1, wherein the destination confirmation unit confirms a plurality of logistics rapid progression belonging to the same campus, and transmits the confirmed logistics express information to the self-adaptive planning unit.
5. The intelligent logistics rapid distribution analysis system based on logistics according to claim 4, wherein the self-adaptive planning unit performs self-adaptive planning on the distribution mode of the distributed objects according to the confirmed logistics express information and obtains the destination warehouse distribution pattern of the corresponding park from the park.
6. The rapid logistics distribution analysis system based on intelligent logistics according to claim 5, wherein the self-adaptive planning unit performs self-adaptive planning on the distributed objects in the following specific ways:
confirming a designated park from the logistics express information, and acquiring a destination warehouse layout of the park from the cloud;
according to the destination warehouse layout, taking a park entrance as an initial point, confirming position information of different dispatch objects from a plurality of logistics express information, confirming a group of dispatch objects closest to the initial point according to the position information, searching a group of dispatch objects closest to the next group by taking the confirmed dispatch objects as the initial point, and so on, and constructing a group of dispatch tables;
and transmitting the constructed dispatch table to a display terminal for display, so that a logistics dispatcher can complete logistics dispatch in the shortest time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310534938.0A CN116485304A (en) | 2023-05-12 | 2023-05-12 | Logistics rapid distribution analysis system based on intelligent logistics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310534938.0A CN116485304A (en) | 2023-05-12 | 2023-05-12 | Logistics rapid distribution analysis system based on intelligent logistics |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116485304A true CN116485304A (en) | 2023-07-25 |
Family
ID=87216297
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310534938.0A Pending CN116485304A (en) | 2023-05-12 | 2023-05-12 | Logistics rapid distribution analysis system based on intelligent logistics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116485304A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252322A (en) * | 2023-11-10 | 2023-12-19 | 青岛冠成软件有限公司 | Logistics supply chain management method |
-
2023
- 2023-05-12 CN CN202310534938.0A patent/CN116485304A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252322A (en) * | 2023-11-10 | 2023-12-19 | 青岛冠成软件有限公司 | Logistics supply chain management method |
| CN117252322B (en) * | 2023-11-10 | 2024-02-02 | 青岛冠成软件有限公司 | Logistics supply chain management method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103763740B (en) | Method and device for balancing loads of single boards | |
| CN105808700A (en) | Game information recommendation method, and server | |
| CN116485304A (en) | Logistics rapid distribution analysis system based on intelligent logistics | |
| CN107403156B (en) | Intelligent supervision method and system for rail transit | |
| CN108964960A (en) | A kind of processing method and processing device of alarm event | |
| CN112130168B (en) | Train position state detection method and system for turn-back control | |
| CN103878184A (en) | Hot rolling line material position remote tracking method | |
| CN109034181A (en) | The classification method and device of motion track, equipment, storage medium | |
| CN111126807B (en) | Stroke segmentation method and device, storage medium and electronic device | |
| CN111352799A (en) | Inspection method and device | |
| CN115311603A (en) | Cargo damage risk judgment method and device, electronic equipment and storage medium | |
| CN115116224B (en) | Edge end data acquisition and transmission system and method | |
| CN104891284A (en) | Elevator group management system | |
| CN112455500B (en) | Initial station jump stop query method under line crossing condition and local line management system | |
| CN110689706A (en) | Method, device and system for monitoring large construction vehicle under overhead line | |
| CN104759471B (en) | Method for remotely capturing hot-rolled strip steel tracking signal | |
| CN108941496B (en) | Real-time tracking and controlling system and method for quality of steelmaking continuous casting process | |
| CN111191904B (en) | Intelligent vehicle formation method and device, electronic equipment and storage medium | |
| CN110913418A (en) | Method and system for early warning and positioning of rail transit communication fault | |
| CN116029799B (en) | Micro-service architecture management platform based on intelligent decision | |
| CN112712002A (en) | CGAN-based environment monitoring method, device, system and storage medium | |
| CN114662912B (en) | Intelligent public transport operation service platform based on digital transformation of public transport | |
| CN110535745B (en) | Online game acceleration method and device, electronic equipment and computer readable medium | |
| CN108269010A (en) | A kind of transport project automatic monitoring method | |
| CN113676918A (en) | Traffic hub crowd migration analysis method and device based on 5G network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |