Business scene digital transformation method, device and equipment and storage medium

Abstract

The embodiment of the invention discloses a business scene digital transformation method and device, equipment and a storage medium, and relates to the technical field of business scene digital transformation information. According to the scheme, digital plans of business scenes with different granularities are aggregated, features and resources of the business scenes are fused, multi-modal data are associated, key features are extracted, and the semantic comprehension ability of the digital plans and a large language model is intelligently matched; the neural network of the service scene is calculated according to the service scene attribution, the associated data and the positioning information, and the disposal scheme corresponding to the service scene is generated, so that subjective deviation of a traditional manual compiling solution is avoided, sudden working conditions and various service scenes are flexibly adapted, and the adaptability of complex scenes is enhanced.

Description

Technical Field

[0001] The present application relates to the field of information technology for digital transformation of business scenarios, and in particular to a method, apparatus, device and storage medium for digital transformation of business scenarios. Background Art

[0002] When faced with various scenarios, enterprises, government agencies, etc. need to promptly provide corresponding handling methods. For example, when faced with emergencies such as fires, enterprises and government agencies need to provide specific response measures based on the emergencies in order to minimize the losses caused by the emergencies.

[0003] In related technologies, taking enterprises as an example, they rely on manual experience to formulate response plans for various scenarios encountered, such as order production, fire, etc., which have subjective biases and lack dynamic adjustment capabilities, making it difficult to cope with market fluctuations or emergencies. Summary of the Invention

[0004] The embodiments of this specification provide a method for digital transformation of business scenarios to solve the problems existing in the prior art of relying on manual experience to formulate disposal plans, lacking dynamic adjustment capabilities, and being difficult to cope with market fluctuations or emergencies.

[0005] To solve the above technical problems, the embodiments of this specification are implemented as follows:

[0006] In a first aspect, embodiments of this specification provide a method for digital transformation of a business scenario, including:

[0007] Integrate industry-specific data and real-time production data, compile digital emergency plans based on digital emergency plan models, and build a digital emergency plan library;

[0008] Pre-set digital plans associated with fixed business scenarios and configure production characteristics and production resources for the business scenarios;

[0009] Obtaining a business scenario, automatically calculating and setting a neural network scenario associated with the business scenario;

[0010] respectively acquiring multimodal data of the business scenario and the neural network scenario;

[0011] The business scenario, the neural network scenario, the multimodal data of the business scenario and the multimodal data of the neural network scenario are input into the digital plan management system platform, and feature extraction and association analysis are performed in combination with the digital plan library and the large language model to generate a disposal plan corresponding to the business scenario.

[0012] In a second aspect, an embodiment of this specification provides a business scenario digital transformation device, including:

[0013] Building modules for integrating industry-specific data and real-time production data, compiling digital emergency plans based on digital emergency plan models, and building a digital emergency plan library;

[0014] The settings module is used to pre-set digital plans associated with fixed business scenarios and configure the production characteristics and production resources of the business scenarios;

[0015] A first acquisition module is used to acquire a business scenario, automatically calculate and set a neural network scenario associated with the business scenario;

[0016] A second acquisition module is used to respectively acquire multimodal data of the business scenario and the neural network scenario;

[0017] A generation module is used to input the business scenario, the neural network scenario, the multimodal data of the business scenario and the multimodal data of the neural network scenario into a digital plan management system platform, combine the digital plan library with the large language model to perform feature extraction and association analysis, and generate a disposal plan corresponding to the business scenario.

[0018] On the third aspect, an embodiment of this specification provides a business scenario digital transformation device, including a memory, a processor and a computer program stored on the memory, and the processor executes the computer program to implement the business scenario digital transformation method in solution one.

[0019] Fourthly, an embodiment of this specification provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the digital transformation method of the business scenario in Solution 1.

[0020] An embodiment of the present specification achieves the following beneficial effects: by aggregating digital plans for business scenarios of different granularities, integrating the characteristics and resources of business scenarios, combining related multimodal data, extracting key features, intelligently matching digital plans with the semantic understanding capabilities of large language models, calculating the neural network of business scenarios based on business scenario attribution, related data, and positioning information, and generating disposal plans corresponding to the business scenarios, avoiding the subjective bias of traditional manually compiled solutions, flexibly adapting to sudden working conditions and diverse business scenarios, and enhancing the adaptability of complex scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0022] Figure 1 A flowchart of a business scenario digital transformation method provided in an embodiment of this specification;

[0023] Figure 2 A schematic diagram of an application scenario of a business scenario digital transformation method provided in an embodiment of this specification;

[0024] Figure 3 A schematic diagram of the framework of the digital plan model provided in the embodiments of this specification;

[0025] Figure 4 A schematic diagram of another application scenario of a business scenario digital transformation method provided in an embodiment of this specification;

[0026] Figure 5 A schematic diagram of the structure of a business scenario digital transformation device provided in an embodiment of this specification;

[0027] Figure 6 This is a schematic diagram of the structure of a business scenario digital transformation device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0028] To make the purpose, technical solutions, and advantages of one or more embodiments of this specification more clear, the technical solutions of one or more embodiments of this specification will be clearly and completely described below in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of one or more embodiments of this specification.

[0029] The current production system faces a weak foundation, a disorganized production system, an incomplete production model, an irrational production development structure, and a fragmented industrial layout. Most manufacturing companies are small and medium-sized enterprises. Lack of capital, technology, and talent hinders their development, making it difficult to achieve economies of scale. Enterprises face numerous challenges, including internal management, talent shortages, and tight funding, as well as volatile external market demand, fierce competition, and an unstable macroeconomic environment. Employees also lack a strong sense of professional belonging and a lack of job responsibility. These factors place enterprises on a precarious path to development, requiring enormous effort and wisdom to overcome numerous obstacles and achieve sustainable development. With such a production system and environment, even the slightest fluctuation can be a life-or-death crisis for some enterprises.

[0030] From the perspective of the company's own production management, its production line design lacked holistic design capabilities, its functional combinations were inflexible, and its business implementation capabilities were limited, making it impossible to fully realize the investment value. In the face of market shifts, it was left with only scrap metal and poor market value retention. Production planning and management lacked scientific rigor, production stability was poor, standardization was low, violations were rampant, production tools were rudimentary, and production accidents were common. Production informatization was backward, and the production management methods used were rudimentary and unable to support a modern, discrete production model.

[0031] These problems are caused by the lack of top-level design and technical management capabilities in my country's production model, which seriously hinder the expansion of corporate production scale and the in-depth upgrading of product quality.

[0032] The complexity of the world is precisely composed of countless dynamically interwoven scenarios, each with its own unique rules, risks, and response logic. Scenario-based thinking is a new perspective in our pursuit of digital transformation in business scenarios. It can help us move from abstract theoretical frameworks to concrete practices, achieving precise and adaptable security management.

[0033] Using the Digitalization Plan (DP) as a foundational scientific element, we will establish a comprehensive infrastructure for productivity management. This architecture will enhance the government or enterprise's top-level design capabilities, fault tolerance, technical management capabilities, and production resource integration capabilities, ultimately promoting sustainable development.

[0034] The technical solutions provided by the embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0035] A digital transformation method for a business scenario provided in an embodiment of the specification is described in detail with reference to the accompanying drawings.

[0036] Figure 1 This is a flowchart of a method for digital transformation of a business scenario provided in an embodiment of this specification. From a program perspective, the execution entity of the process can be a program or application client installed on an application server. On the other hand, from a hardware perspective, the execution entity of the process can be a terminal device, etc., which is not specifically limited in this embodiment.

[0037] like Figure 1 As shown, the process may include the following steps:

[0038] Step 110: Integrate industry-specific data and real-time production data, prepare digital emergency plans based on the digital emergency plan model, and build a digital emergency plan library.

[0039] In the embodiments of this specification, industry-specific data may include industry standards, specifications, best practices, historical cases, etc. Real-time production data can come from real-time monitoring and feedback during the production process, such as equipment status, production progress, quality data, etc. The digital emergency plan model can be based on a knowledge graph, rule engine, or machine learning model to convert data into structured emergency plan templates to form a reusable emergency plan library.

[0040] By integrating industry-specific data and real-time production data, a dynamically updated digital plan library is built to ensure that the plan content is highly matched with the actual needs of the industry.

[0041] Step 120: Pre-set a digital plan associated with a fixed business scenario and configure the production characteristics and production resources of the business scenario.

[0042] In the embodiments of this specification, the production features and production resources of the business scenario are pre-configured, and the dynamic modeling of the neural network scenario is combined to achieve multi-dimensional feature fusion.

[0043] Step 130: Acquire a business scenario, and automatically calculate and set a neural network scenario associated with the business scenario.

[0044] In the embodiments of this specification, the neural network scenario can be a dynamic model trained through simulation or historical data to simulate the scenario evolution path. The neural network scenario associated with the business scenario is automatically calculated, and through the parallel processing of multimodal data, it supports risk identification and plan matching within seconds.

[0045] Step 140: Acquire multimodal data of the business scenario and the neural network scenario respectively.

[0046] In the embodiments of this specification, the business scenarios can be the daily work mechanisms of a department, emergencies, key locations, key equipment, key enterprises, key production lines, key warehouses, special materials, special groups of people, work sites, smart cities, future factories, future communities, etc., or other complex systems that need to be managed and monitored.

[0047] Multimodal data includes various types of data from business scenarios, such as images, videos, text, audio, and possible other forms of data, which can describe key information such as the status, events, participants, etc. of the business scenario.

[0048] Step 150: Input the business scenario, the neural network scenario, the multimodal data of the business scenario, and the multimodal data of the neural network scenario into the digital plan management system platform, combine the digital plan library with the large language model to perform feature extraction and association analysis, and generate a disposal plan corresponding to the business scenario.

[0049] In the embodiments of this specification, a large language model is combined with a digital emergency plan model to process text and other natural language data. The large language model can provide capabilities such as contextual understanding and semantic analysis, thereby enhancing the model's ability to process multimodal data. The large language model can be a general-purpose large language model such as DeepSeek.

[0050] The digital contingency plan model extracts features from the input multimodal data, identifying key information, anomalies, and patterns. It then performs correlation analysis on the extracted features using the digital contingency plan library and a large language model. Based on the results of feature extraction and correlation analysis, it generates a response plan tailored to the business scenario. This response plan can include countermeasures, action plans, and resource allocation, and can be used to guide the management, monitoring, and response of the business scenario.

[0051] It should be understood that the order of some steps in the methods described in one or more embodiments of this specification can be interchanged according to actual needs, or some steps can be omitted or deleted.

[0052] In the embodiments of this specification, by aggregating digital plans for business scenarios of different granularities, integrating the characteristics and resources of the business scenarios, combining related multimodal data, extracting key features, and intelligently matching the digital plans with the semantic understanding capabilities of the large language model, the neural network of the business scenario is calculated based on the business scenario attribution, related data, and positioning information, and a disposal plan corresponding to the business scenario is generated, thereby avoiding the subjective bias of traditional manually compiled solutions, flexibly adapting to sudden working conditions and diverse business scenarios, and enhancing the adaptability of complex scenarios.

[0053] based on Figure 1 The method in this specification also provides some specific implementation plans of the method, which are described below.

[0054] Optionally, the digital plan model described in the embodiments of this specification is a computer language for describing digital management of business scenarios, and the digital plan model includes a management structured module and a technical standardization module; wherein the management structured module includes an organizational structured unit, a resource standardization unit, an assessment standardization unit, a stage structured unit, and an algorithm structured unit; and the technical standardization module includes a standardized process unit and a differentiated process unit.

[0055] The organizational structure unit is used to define positions, responsibilities and work groups;

[0056] The resource standardization unit is used to uniformly classify and match production resources;

[0057] The assessment standardization unit is used to set unified assessment indicators and evaluation mechanisms;

[0058] The stage structured unit is used to divide the daily stage, early warning stage, emergency response stage and post-event handling stage;

[0059] The algorithm structuring unit is used to integrate various data and algorithm resources;

[0060] The standardized process unit is used to set basic operating procedures and safety requirements;

[0061] The differentiated process unit is used to adapt to personalized business processes in different scenarios.

[0062] Figure 2 A schematic diagram of an application scenario of a business scenario digital transformation method provided in an embodiment of this specification.

[0063] In the embodiments of this specification, Figure 2 As shown, the digital plan model can include a management structured module and a technical standardization module. The management structured module is responsible for the structured management of organization, resources, assessment, stages and algorithms, and the technical standardization module is responsible for the standardized management of processes and technologies.

[0064] Organizational structure units can be used to set up positions, define positions, responsibilities and work groups, clarify the responsibilities of each position and the work team to which it belongs, and achieve orderly management and efficient collaboration of the organization.

[0065] The resource standardization unit can uniformly classify and match production resources, including team resources, material resources, equipment resources, smart devices, vehicle resources, etc., which can improve resource utilization efficiency and management convenience.

[0066] The assessment standardization unit can set unified assessment indicators and evaluation mechanisms, including statistical summary table settings, data reporting settings, real-time risk assessment settings, etc., to ensure the fairness and accuracy of the assessment and provide a basis for management decisions.

[0067] The stage-structured unit can be divided into daily stage, early warning stage, emergency response stage and post-event disposal stage, clarifying the tasks and goals of each stage, and realizing the whole-process management and effective response of the incident.

[0068] The algorithm structured unit can integrate a variety of data and algorithm resources, including AI algorithms, industry big models, data mining, etc., support the application of multimodal algorithms, and improve the efficiency and accuracy of data processing and analysis.

[0069] Standardized process units can set basic operating procedures and safety requirements, including basic information settings, standard operation card settings, safety requirements settings, business process diagrams, etc., to ensure the safety and standardization of the operating process.

[0070] Differentiated process units can adapt to personalized business processes in different scenarios, allowing the definition of the unit's business process diagram and other grassroots standardized process information. Through business process diagrams and basic information settings, responsibilities can be defined to meet business needs in specific scenarios and improve the flexibility and adaptability of the process.

[0071] Optionally, the method described in the embodiments of this specification may further include:

[0072] Based on the digital plan model, an information specification for transforming the physical space of a business scenario into a digital virtual space is constructed. The business scenario is decomposed and described through the digital plan model to form a data packet for data calculation, supporting data interaction and business superposition between the business scenario and the neural network scenario.

[0073] Optionally, the method described in the embodiments of this specification may further include:

[0074] Construct a digital plan management system platform, which is used for the superposition management of multiple scenarios and code-free generation of application software services; through the digital plan management system platform, the business scenarios are managed and controlled in real time, resources are allocated, and the disposal plans are executed, forming a digital cockpit and console for the business scenarios.

[0075] In the embodiments of this specification, based on the digital plan model, a digital plan management system platform, namely a production PaaS platform, can be constructed. The production PaaS platform supports the superimposed management of multiple production scenarios, and can simultaneously manage and monitor multiple different production scenarios on the same platform, realize cross-scenario resource integration and coordination, and improve overall production efficiency and resource utilization.

[0076] By producing a PaaS platform, you can generate code-free application software services for specific scenarios, that is, generate SaaS applications to meet business needs in different scenarios.

[0077] Figure 3 This is a schematic diagram of the framework of the digital plan model provided in the embodiments of this specification.

[0078] like Figure 3 As shown, the scenario ledger registration is realized through basic information setting, personnel resource setting, and production management setting. The digital plan model can include overall plans and special disposal plans. Based on information IaaS, production DaaS, and internally shared or socially shared production resources, a digital plan model is constructed. The production PaaS platform generates SaaS applications for each scenario. The scenario management application includes the scenario console, scenario background configuration management, scenario APP management, etc., which can realize the digital transformation of the scenario.

[0079] Optionally, the digital emergency plan management system platform described in the embodiment of this specification includes a digital intelligence element module, a digital intelligence core module and a digital intelligence communication module;

[0080] The digital intelligence module is used for emergency plan preparation and scenario management;

[0081] The digital intelligence core module is used to centrally manage the operational status of the production system;

[0082] The digital intelligence module is used to build a console for the scene.

[0083] In the embodiments of this specification, the traditional software service form is a service structure of IaaS+PaaS+SaaS, among which IaaS is infrastructure service, and its full name in English is Infrastructure as a server, which means helping customers build the infrastructure for running services, preparing computer rooms or machines offline, forming an environment to run projects that can provide services, and deploying the projects to provide services; PaaS-Platform as a Service, its full name in English is Platform as a Server, which means using the cloud to build operating systems or software layers such as databases, middleware, etc. for users to use, so that users do not need to pay attention to the underlying infrastructure and operating environment, but only need to use these environments to run their own applications and data; SaaS-Software as a Service, its full name in English is Software as a Server, which means that the cloud has already built everything from the operating system to the operating environment to the software client, and the user does not need to install any environment or software, but only needs to access the client to use it directly.

[0084] Figure 4 A schematic diagram of another application scenario of a business scenario digital transformation method provided in an embodiment of this specification.

[0085] like Figure 4 As shown in the figure, by enriching the PaaS platform's functionality and replacing traditional SaaS software development with digital plans, a new software service model combining IaaS, PaaS, and digital plans is being built. The digital transformation of business scenarios simply requires the development of digital plans and the configuration of relevant resources. This allows professional business personnel to participate in application software development without coding. Replacing software development with digital plan development significantly shortens the software development and debugging cycle, rapidly achieving digital transformation of application scenarios and enabling the rapid definition of application scenarios using plans.

[0086] The digital plan management system platform, namely the production PaaS platform, can include the digital intelligence element module, digital intelligence core module, digital intelligence communication module, digital intelligence help module and digital intelligence Runde module.

[0087] The Digital Intelligence Meta Module can be used for emergency plan preparation and scenario management, supporting the preparation and release of digital emergency plans. Users can define and edit various emergency plans in the Digital Intelligence Meta Module, including overall plans and specific disposal plans. Digital plans can also be edited by experts. The Digital Intelligence Meta Module also provides management functions for production scenarios. Users can set basic scenario information, personnel resources, production management, and other content, enabling scenario registration and digital management.

[0088] The Digital Intelligence Core module centrally manages the operational status of the production system and serves as the centralized control center for the Production PaaS platform. It monitors and analyzes the operational status of the production system in real time, including equipment status, production progress, and resource utilization. Based on real-time data, the Digital Intelligence Core module conducts operational analysis, identifies potential issues and risks, and provides corresponding warnings and recommendations for coordinated supervision and scheduling.

[0089] The Digital Intelligence module can be used to build scenario consoles, including enterprise, emergency, location, and on-site versions, providing a dedicated console for each production scenario. Tasks can be generated to the Digital Intelligence Helper app on a scheduled or manual basis, inheriting the Digital Intelligence Runde e-commerce functionality. Through the application scenario-specific management terminal, users can view the real-time status of the scenario, monitor key indicators, execute plans, and perform other operations in the console. The Digital Intelligence module also supports the overlay management of multiple scenarios. Users can manage and monitor multiple scenarios simultaneously in the same console, improving management efficiency and response speed.

[0090] The Digital Intelligence Helper is the terminal that receives, distributes and executes various tasks. It receives task instructions from the Digital Intelligence Core Module or the Digital Intelligence Communication Module through various forms of service business.

[0091] Shuzhi Runde is an e-commerce platform and personal self-service platform for the procurement of various materials. It provides a convenient material procurement channel for the production system through multi-mode product commerce.

[0092] Optionally, the embodiment of this specification combines the digital plan library with the large language model to perform feature extraction and association analysis to generate a disposal plan corresponding to the business scenario, specifically including:

[0093] Calling a digital plan that matches the business scenario from the digital plan library and extracting business scenario rules and features;

[0094] Perform feature extraction and correlation analysis on the business scenario rules and features and the large language model;

[0095] Calculating a neural network scenario associated with the business scenario based on the features and the association analysis results;

[0096] The production characteristics and resources of the business scenario and the neural network scenario are integrated, and a disposal plan is generated in combination with the digital plan library.

[0097] In the embodiments of this specification, based on the input information of the business scenario, a semantic retrieval algorithm is used to screen the most relevant historical plans from the digital plan library. The text description of the business scenario is input into the large language model to generate a high-dimensional semantic vector, which is spatially aligned with the entity vectors in the plan library. By analyzing and processing the input text, the large language model can output a series of feature vectors that can reflect the linguistic characteristics, semantic information, and contextual relationships of the input text.

[0098] Align the features of the neural network scenario with the historical scenarios in the plan library, identify the differences, call the optimization model in the algorithm structured unit, calculate the optimal resource scheduling plan, and combine the digital plan library to generate a disposal plan corresponding to the business scenario.

[0099] In the embodiments of this specification, the execution of the plan can be simulated in a virtual environment, key indicators can be evaluated, the simulation results can be sent back to the plan library, and the model parameters can be updated through reinforcement learning to optimize the accuracy of subsequent plan generation.

[0100] In actual applications, standardized management of business scenarios is the physical basis of digital transformation, digital plans are the computer language of digital transformation of business scenarios, and business scenario digital cockpits, digital twins and centralized control platforms are the manifestations of digital transformation.

[0101] Specifically, based on the requirements of emergency rescue work, the government or enterprises will carry out planning and design of business scenarios based on their own actual conditions, including standardized construction of scenarios, daily operation and maintenance methods, resource reserve methods, and identification and disposal of hidden risks in continuous operations, etc., to systematically ensure the normal operation and update iteration of business scenarios.

[0102] Based on general large language models such as DeepSeek, we deeply develop production scenario applications of digital plans, quickly build the disaster prevention capabilities of governments or enterprises in business scenarios to identify hidden risks, and combine production systems and production resources to quickly match professional handling plans for production anomalies with 1-minute response, 3-minute on-site arrival, and 5-minute handling plans to enhance the fault tolerance capabilities of governments or enterprises.

[0103] Carry out technical management based on production scenarios to ensure that technological research and development is targeted, practical, and market-oriented, safeguard technological interests, and build a stable and orderly professional production service system for the continuous improvement and deepening of technological research and development to achieve high-quality development.

[0104] Implementing standardized management of production resources based on production scenarios, selecting production resources based on actual production practices, optimizing resource standards, improving the quality and reliability of production resources, and establishing interactive methods for acquiring production resources effectively achieves production resource integration. This not only improves the ability to address production risks but also reduces uncertainty in project and technology R&D, enabling rapid innovation. Standardized management of production resources enriches market management tools and fully protects the rights of producers and consumers.

[0105] Experts are empowered with knowledge based on production scenarios. By binding production scenarios with digital plans and setting relevant production resources according to specifications, pre-plan management of production scenarios can be achieved. At the same time, production scenarios are bound to experts to achieve real-time interaction between experts and grassroots production personnel, improve the operational capabilities of grassroots employees and their ability to respond to abnormal working conditions, and create more learning and training opportunities.

[0106] In the embodiments of this specification, through the preparation of digital plans, leaders and senior experts are provided with code-free and low-code development tools for production SAAS service applications, which can quickly realize the digital transformation of knowledge and production capabilities. Through the overall planning of digital plans, the job responsibilities of production scenarios are clarified, production plans are carried out in an orderly manner, and the operation of the production system is intensively supervised. Through the management of digital plans, multi-enterprise, multi-role and full ecological management of discrete production systems is realized, and the production relationship between management and technology, production and experts, and production and equipment is loosely coupled and reconstructed, the utilization rate of production resources is improved, and new quality productivity is created. Through large language models, combined with standardized production resources and standardized data algorithm resources, a production PAAS intelligent body is constructed to fully realize the intelligent assessment of hidden risks in production scenarios and the automatic generation of emergency plans for handling sudden working conditions.

[0107] Figure 5 This is a schematic diagram of the structure of a business scenario digital transformation device provided in an embodiment of this specification.

[0108] Corresponding to the method embodiment, this embodiment also provides a business scenario digital transformation device, which may include:

[0109] Construction module 502 is used to integrate industry-specific data and real-time production data, compile digital emergency plans based on the digital emergency plan model, and build a digital emergency plan library;

[0110] The setting module 504 is used to pre-set the digital plan associated with the fixed business scenario and configure the production characteristics and production resources of the business scenario;

[0111] A first acquisition module 506 is used to acquire a business scenario, automatically calculate and set a neural network scenario associated with the business scenario;

[0112] A second acquisition module 508 is used to respectively acquire multimodal data of the business scenario and the neural network scenario;

[0113] Generation module 510 is used to input the business scenario, the neural network scenario, the multimodal data of the business scenario and the multimodal data of the neural network scenario into the digital plan management system platform, combine the digital plan library with the large language model to perform feature extraction and association analysis, and generate a disposal plan corresponding to the business scenario.

[0114] Optionally, the digital plan model described in the embodiments of this specification is a computer language for describing digital management of business scenarios, and the digital plan model includes a management structured module and a technical standardization module; wherein the management structured module includes an organizational structured unit, a resource standardization unit, an assessment standardization unit, a stage structured unit, and an algorithm structured unit; and the technical standardization module includes a standardized process unit and a differentiated process unit.

[0115] The organizational structure unit is used to define positions, responsibilities and work groups;

[0116] The resource standardization unit is used to uniformly classify and match production resources;

[0117] The assessment standardization unit is used to set unified assessment indicators and evaluation mechanisms;

[0118] The stage structured unit is used to divide the daily stage, early warning stage, emergency response stage and post-event handling stage;

[0119] The algorithm structuring unit is used to integrate various data and algorithm resources;

[0120] The standardized process unit is used to set basic operating procedures and safety requirements;

[0121] The differentiated process unit is used to adapt to personalized business processes in different scenarios.

[0122] Optionally, the apparatus described in the embodiments of this specification may further include:

[0123] Based on the digital plan model, an information specification for transforming the physical space of a business scenario into a digital virtual space is constructed. The business scenario is decomposed and described through the digital plan model to form a data packet for data calculation, supporting data interaction and business superposition between the business scenario and the neural network scenario.

[0124] Based on the same idea, the embodiments of this specification also provide devices corresponding to the above methods.

[0125] Figure 6This is a schematic diagram of the structure of a business scenario digital transformation device provided in the embodiment of this specification. Figure 6 As shown, an embodiment of this specification provides a business scenario digital transformation device 600, including a memory 630, a processor 610 and a computer program 620 stored in the memory. The processor 610 executes the computer program 620 to implement the business scenario digital transformation method described in any of the above embodiments.

[0126] A business scenario digital transformation device provided in an embodiment of this specification may include a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the business scenario digital transformation method described in any of the above embodiments.

[0127] An embodiment of this specification provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for digital transformation of business scenarios described in any of the above embodiments can be implemented.

[0128] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. Figure 6 As for the device shown, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0129] In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures like diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements today can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using a hardware module. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can "integrate" a digital system on a PLD through their own programming, eliminating the need for a chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly done using "logic compiler" software. This is similar to the software compiler used when developing programs. Before compilation, the original code must also be written in a specific programming language, called a hardware description language (HDL). There is not just one HDL, but many, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art will also understand that by simply programming the method flow in one of these hardware description languages ​​and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

[0130] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also understand that in addition to implementing the controller in pure computer-readable program code, the controller can also be implemented in the form of logic gates, switches, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0131] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0132] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0133] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0135] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0136] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0137] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0138] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0139] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0140] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0141] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0143] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A business scenario digital transformation method, characterized by: include: Integrate industry-specific data and real-time production data, compile digital emergency plans based on digital emergency plan models, and build a digital emergency plan library; Pre-set digital plans associated with fixed business scenarios and configure production characteristics and production resources for the business scenarios; Obtaining a business scenario, automatically calculating and setting a neural network scenario associated with the business scenario; respectively acquiring multimodal data of the business scenario and the neural network scenario; The business scenario, the neural network scenario, the multimodal data of the business scenario and the multimodal data of the neural network scenario are input into the digital plan management system platform, and feature extraction and association analysis are performed in combination with the digital plan library and the large language model to generate a disposal plan corresponding to the business scenario.

2. The method according to claim 1, characterized in that The digital plan model is a computer language that describes the digital management of business scenarios. The digital plan model includes a management structured module and a technical standardization module. The management structured module includes an organizational structured unit, a resource standardization unit, an assessment standardization unit, a stage structured unit, and an algorithm structured unit. The technical standardization module includes a standardized process unit and a differentiated process unit. The organizational structure unit is used to define positions, responsibilities and work groups; The resource standardization unit is used to uniformly classify and match production resources; The assessment standardization unit is used to set unified assessment indicators and evaluation mechanisms; The stage structured unit is used to divide the daily stage, early warning stage, emergency response stage and post-event handling stage; The algorithm structuring unit is used to integrate various data and algorithm resources; The standardized process unit is used to set basic operating procedures and safety requirements; The differentiated process unit is used to adapt to personalized business processes in different scenarios.

3. The method according to claim 1, characterized in that The method further comprises: Based on the digital plan model, an information specification for transforming the physical space of a business scenario into a digital virtual space is constructed. The business scenario is decomposed and described through the digital plan model to form a data packet for data calculation, supporting data interaction and business superposition between the business scenario and the neural network scenario.

4. The method according to claim 1, wherein The method further comprises: Construct a digital plan management system platform, which is used for the superposition management of multiple scenarios and code-free generation of application software services; through the digital plan management system platform, the business scenarios are managed and controlled in real time, resources are allocated, and the disposal plans are executed, forming a digital cockpit and console for the business scenarios.

5. The method according to claim 1, wherein The digital emergency plan management system platform includes a digital intelligence element module, a digital intelligence core module and a digital intelligence communication module; The digital intelligence module is used for emergency plan preparation and scenario management; The digital intelligence core module is used to centrally manage the operational status of the production system; The digital intelligence module is used to build a console for the scene.

6. The method according to claim 1, wherein The combining of the digital plan library and the large language model to perform feature extraction and association analysis to generate a disposal plan corresponding to the business scenario specifically includes: Calling a digital plan that matches the business scenario from the digital plan library and extracting business scenario rules and features; Perform feature extraction and correlation analysis on the business scenario rules and features and the large language model; Calculating a neural network scenario associated with the business scenario based on the features and the association analysis results; The production characteristics and resources of the business scenario and the neural network scenario are integrated, and a disposal plan is generated in combination with the digital plan library.

7. A business scenario digital transformation device, characterized in that: include: Building modules for integrating industry-specific data and real-time production data, compiling digital emergency plans based on digital emergency plan models, and building a digital emergency plan library; The settings module is used to pre-set digital plans associated with fixed business scenarios and configure the production characteristics and production resources of the business scenarios; A first acquisition module is used to acquire a business scenario, automatically calculate and set a neural network scenario associated with the business scenario; A second acquisition module is used to respectively acquire multimodal data of the business scenario and the neural network scenario; A generation module is used to input the business scenario, the neural network scenario, the multimodal data of the business scenario and the multimodal data of the neural network scenario into a digital plan management system platform, combine the digital plan library with the large language model to perform feature extraction and association analysis, and generate a disposal plan corresponding to the business scenario.

8. The device according to claim 7, characterized in that The digital plan model is a computer language that describes the digital management of business scenarios. The digital plan model includes a management structured module and a technical standardization module. The management structured module includes an organizational structured unit, a resource standardization unit, an assessment standardization unit, a stage structured unit, and an algorithm structured unit. The technical standardization module includes a standardized process unit and a differentiated process unit. The organizational structure unit is used to define positions, responsibilities and work groups; The resource standardization unit is used to uniformly classify and match production resources; The assessment standardization unit is used to set unified assessment indicators and evaluation mechanisms; The stage structured unit is used to divide the daily stage, early warning stage, emergency response stage and post-event handling stage; The algorithm structuring unit is used to integrate various data and algorithm resources; The standardized process unit is used to set basic operating procedures and safety requirements; The differentiated process unit is used to adapt to personalized business processes in different scenarios.

9. The device according to claim 7, characterized in that The device further comprises: Based on the digital plan model, an information specification for transforming the physical space of a business scenario into a digital virtual space is constructed. The business scenario is decomposed and described through the digital plan model to form a data packet for data calculation, supporting data interaction and business superposition between the business scenario and the neural network scenario.

10. A business scenario digital transformation device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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