CN-121981629-A - Big commodity circulation is cognitive to cooperate management system

CN121981629ACN 121981629 ACN121981629 ACN 121981629ACN-121981629-A

Abstract

The invention relates to the technical field of logistics intelligent management, and particularly discloses a large logistics cognition collaborative management system which is constructed based on an AI and an industrial Internet platform and comprises an edge layer, a platform layer, an engine layer and an application layer, wherein the edge layer is constructed based on an IT system, OT equipment and manual filling in the logistics transportation industry, the edge layer activates corresponding data acquisition capacity according to received data requests, the platform layer starts corresponding data processing flow according to received task instructions, the engine layer analyzes, identifies and plans the tasks of the received requests and intelligently analyzes the received data, and the application layer analyzes the received user requests and outputs the received data results. The invention integrates the IT system and OT equipment in the logistics transportation industry, can form visual and efficient cognitive collaborative management for large logistics, and provides a timely, comprehensive and accurate data support basis for business and technical decisions of enterprises.

Inventors

CHEN MINGREN
Hu Ruofan
YANG QIYUAN
Xiong Fangrui
LI YANG
Zou Wanxiong

Assignees

东方电气集团数字科技有限公司

Dates

Publication Date: 20260505
Application Date: 20251229

Claims (10)

1. A large logistics cognition collaborative management system is characterized in that: The management system is constructed based on an AI and an industrial Internet platform and is provided with an edge layer, a platform layer, an engine layer and an application layer; The edge layer is constructed based on an IT system, OT equipment and manual filling in the logistics transportation industry, activates corresponding data acquisition capacity by a data request issued by the platform layer, and uploads acquired data to the platform layer after packaging; the platform layer starts a corresponding data processing flow by a task instruction issued by the engine layer, and comprises the steps of issuing a data request to the edge layer, processing data uploaded by the edge layer, and ensuring that an intelligent engine can be directly used and uploaded; the engine layer is used for receiving an application request issued by the application layer, analyzing, identifying and planning tasks, intelligently analyzing the data uploaded by the platform layer, generating a structural result and uploading the structural result; The application layer is used for receiving a request input by a user, analyzing and issuing the request, and receiving an uploaded structured result to generate and output direct user identification information.
2. The large logistics cognitive collaborative management system of claim 1, wherein: The application layer receives a request input by a user in a multi-mode interaction mode and/or outputs directly identifiable information to the user in the multi-mode interaction mode.
3. The large logistics cognitive collaborative management system of claim 1 or 2, wherein: the application layer is provided with a demand input module, a response output module and an abnormal output module; The demand input module is used for receiving a request input by a user and analyzing the request into a structural instruction; the response output module generates a visual chart and/or broadcast voice which can be directly identified by a user according to the received analysis and synthesis result; And when the abnormal condition is found, the abnormal input module starts an early warning mechanism, informs and reminds a user.
4. A large logistics cognitive collaborative management system according to claim 3, wherein: the demand input module establishes a session context in the process of receiving a request input by a user.
5. The large logistics cognitive collaborative management system of claim 1, wherein: The engine layer is provided with a natural language processing engine module, a task planning engine module and an industry knowledge base module; the natural language processing engine module is used for carrying out deep semantic analysis on the received structured instruction, identifying key business entities and user intentions, and carrying out synthesis processing on a structured result generated by intelligent analysis; the task planning engine module disassembles the results generated by the natural language processing engine module into executable data query and analysis tasks, invokes a calculation model, and in the process, the industry knowledge base module provides domain rule support for task planning, ensures that an analysis scheme accords with service logic, and intelligently analyzes received intermediate result data and/or final result data by the calculation model to generate a structured result.
6. The large logistics cognitive collaborative management system of claim 5, wherein: The engine layer is also provided with an agile development engine module; the agile development engine module is used as a software development scaffold to perfect the engine layer function according to the technical requirement.
7. The large logistics cognitive collaborative management system of claim 1, wherein: when receiving a task instruction issued by the engine layer, the platform layer performs authority verification and resource check to ensure that the query request accords with a safety specification, evaluates the current load capacity of the system and allocates corresponding computing resources; after the verification is passed, the corresponding data processing flow is started.
8. The large logistics cognitive collaborative management system of claim 1 or 7, wherein: the platform layer is provided with a data management module, a data processing module, a data storage module and a data acquisition module; the data acquisition module is used for dispatching the required data from the edge layer; the data management module is used for cleaning, converting and fusing the scheduled multi-source heterogeneous data; The data processing module is used for executing specific calculation and analysis processes on the treated data to generate intermediate result data/final result data; The data storage module is used for respectively carrying out persistence processing on the intermediate result data and the final result data generated by the data processing module.
9. The large logistics cognitive collaborative management system of claim 1, wherein: the edge layer is also used for receiving a control instruction from an upper layer so as to dynamically adjust the acquisition frequency and the acquisition range.
10. The large logistics cognitive collaborative management system of claim 1 or 9, wherein: the edge layer is provided with an IT system module, an OT equipment module and a manual reporting module; The IT system module is used for connecting the TMS system, the WMS system and the ERP system in a communication way; The OT equipment module is used for being in communication connection with a vehicle CAN bus, a GPS sensor and a warehouse PLC controller; The manual filling module is used for manually filling and supplementing site observation information.

Description

Big commodity circulation is cognitive to cooperate management system Technical Field The invention relates to the technical field of logistics intelligent management, in particular to a large logistics cognitive collaborative management system. Background The large logistics is taken as an important component in a modern logistics system and is frequently generated in business/trade operation processes among enterprises, so that the large logistics data are timely and comprehensively mastered, the large logistics is very important to scientific and efficient operation of the enterprises, and in particular, objective, scientific and strict powerful support can be provided for macroscopic decisions of decision-making layers of the enterprises. However, the large logistics has the technical characteristics of large cargo volume, heavy weight, complex transportation path, special storage requirement, multiple supply chain links, high safety standard and the like, so that huge heterogeneous data including multi-dimensional information such as real-time transportation data, storage state information, equipment operation parameters, environmental factors and the like exists in the large logistics process. The data are mastered, the technical difficulty is increased, and particularly, the traditional manual mode is difficult to master the data timely and comprehensively. With the rapid development of modern logistics systems, various IT systems for logistics transportation, such as TMS systems, WMS systems, ERP systems and the like, and OT operation monitoring technologies are generated. However, even if these technologies exist, for the data management of large logistics, the relative discretization and the data island formation are still presented, and the cognitive collaborative management cannot be intuitively formed by technical means, so that the visual and effective support cannot be provided for the macroscopic decision of the enterprise decision-making layer. Disclosure of Invention Aiming at the particularity of the large logistics, the technical requirements for grasping logistics data of the large logistics and the defects of the prior art, the technical aim of the invention is to provide the large logistics cognition collaborative management system which is based on an AI combined industrial Internet platform and can form cognition collaborative interaction and output logistics information and decision reference information in real time. The technical aim of the invention is achieved by the following technical scheme, namely a large logistics cognition collaborative management system, which is constructed based on an AI and an industrial Internet platform and comprises an edge layer, a platform layer, an engine layer and an application layer; The edge layer is constructed based on an IT system, OT equipment and manual filling in the logistics transportation industry, activates corresponding data acquisition capacity by a data request issued by the platform layer, and uploads acquired data to the platform layer after packaging; the platform layer starts a corresponding data processing flow by a task instruction issued by the engine layer, and comprises the steps of issuing a data request to the edge layer, processing data uploaded by the edge layer, and ensuring that an intelligent engine can be directly used and uploaded; the engine layer is used for receiving an application request issued by the application layer, analyzing, identifying and planning tasks, intelligently analyzing the data uploaded by the platform layer, generating a structural result and uploading the structural result; The application layer is used for receiving a request input by a user, analyzing and issuing the request, and receiving an uploaded structured result to generate and output direct user identification information. Further, the application layer receives a request input by a user in a multi-mode interaction mode and/or outputs directly identifiable information to the user in a multi-mode interaction mode. Further, the application layer is provided with a demand input module, a response output module and an abnormal output module; The demand input module is used for receiving a request input by a user and analyzing the request into a structural instruction; the response output module generates a visual chart and/or broadcast voice which can be directly identified by a user according to the received analysis and synthesis result; And when the abnormal condition is found, the abnormal input module starts an early warning mechanism, informs and reminds a user. Further, the demand input module establishes a session context in the process of receiving a request input by a user. Further, the engine layer is provided with a natural language processing engine module, a task planning engine module and an industry knowledge base module; the natural language processing engine module is used for carrying out deep semantic analysis o