Research On Industrial Collaborative Emergency Smart Intelligence Service Model Driven By Multiple Source Data

Against the backdrop of a complex international situation,many industries in China are gradually falling into development traps caused by external unfair international competition,with frequent industrial crisis events and key core industries repeatedly suffering from external suppression.Under the multiple factors of promoting industrial digital transformation,releasing the value of industrial data elements,and complex information environment,multi-source industrial data has become the foundation of sustainable development and the source of smooth development.It is the key to promoting the multi form and multi path docking of subjects,knowledge,and resources,and also an important foundation for industrial intelligence services.Faced with the unpredictable international situation and the complex and sensitive industrial competition situation,China’s industrial development is full of crises,and the ability of industrial collaborative emergency response is being tested.There is an urgent need for smart intelligence services.Starting from the prevention,preparation,response,and recovery stages of the emergency management process,guided by the actual needs of industrial collaborative emergency response,timely,accurate,and efficient emergency response to industrial crisis events can be completed,Effectively implementing an industrial collaborative emergency intelligent service model that includes intelligent warning,intelligent inquiry,collaborative linkage,and crisis recovery,in order to enhance the industry’s ability to respond to emergencies,and to achieve accurate analysis,rapid response,timely disposal,and recovery of industrial crisis events under the drive of multi-source data integration and collaborative governance of multiple entities.This provides collaborative,customized,and convenient solutions for the prevention,preparation,response,and recovery stages of industrial crisis events Efficient and precise intelligence services attempt to use the power of smart intelligence services to assist industry development in overcoming the adverse effects of crisis events.This article is based on theories such as emergency management process,information collaboration,ternary world,CPSS modeling ideas,deconstruction and restructuring,and resilient governance in complex information environments,industrial crisis situations,and multi-source data-driven backgrounds.Focusing on the core issue of industrial collaborative emergency smart intelligence services,semi-structured interviews,expert consultations,prototype system development,intelligent technology integration applications,and empirical research methods are used.Using multi-source data fusion,alliance blockchain,data lake storage,natural language processing,big language model fine-tuning,and system dynamics simulation,the smart intelligence service model for industrial collaborative emergency prevention,preparation,response,and recovery stages is developed under the support of the industrial collaborative emergency smart intelligence service platform driven by multi-source data.The smart intelligence service model for industrial collaborative emergency prevention,preparation,response,and recovery stages is also developed.Taking the shutdown crisis caused by power restrictions as an example,this article explains the operational process of smart intelligence services in various stages of industrial collaborative emergency response and verifies the value and effectiveness of the smart intelligence service model in the national semiconductor industry.Chapter 3 of this article clarifies the intelligence service needs based on the research results of the current situation of industrial collaborative emergency intelligence services,clarifies the correlation between multi-source data-driven,industrial collaborative emergency,and smart intelligence services,elaborates on the process of smart intelligence services in the prevention,preparation,response,and recovery stages,deconstructs basic elements,and constructs an industrial collaborative emergency smart intelligence service platform based on the triad world,CPSS modeling ideas,and deconstruction and restructuring theory,Finally,a mechanism model for industrial collaborative emergency smart intelligence services driven by multi-source data is proposed,providing research ideas,theoretical basis,and platform support for subsequent chapters.Based on the four stages of prevention,preparation,response,and recovery in the theory of emergency management process,the construction of smart intelligence service models for each stage of Chapter 4,5,6,and 7 is carried out.The semiconductor industry is selected as a case study in the face of shutdown crisis events,and empirical analysis is conducted from different intelligence needs in the four stages of emergency management to verify the effectiveness of smart intelligence service models in each stage.Based on the previous chapters,Chapter 8 proposes a guarantee mechanism for industrial collaborative emergency intelligence services from the perspectives of industrial policies,talent cultivation,and scenario traction,combined with the constraints of Chapter 3 on industrial collaborative emergency intelligence services.Then,from the perspectives of data,technology,service,and scenario,the guarantee strategy and scenario extension for industrial collaborative emergency intelligence services are proposed.The main research content is as follows:Firstly,research on the mechanism of industrial collaborative emergency smart intelligence services driven by multi-source data.Firstly,semi-structured interviews and expert interviews were used to investigate the current situation of industrial collaborative emergency intelligence services,clarify the pain points and needs of industrial collaborative emergency intelligence services,analyze the limiting factors that affect the quality of industrial collaborative emergency intelligence services,and deeply analyze the relationship between "multi-source data-driven","industrial collaborative emergency",and "smart intelligence services",clarifying prevention,preparation,and The content and entire process of industrial collaborative emergency smart intelligence services during the response and recovery phase.Then,starting from the perspectives of environment,data,subject and object,technology,needs and services,analyze the constituent elements of industrial collaborative emergency smart intelligence services driven by multi-source data,and complete the deconstruction.Once again,based on the deconstruction of the elements of industrial collaborative emergency smart intelligence services,the three element world theory and CPSS modeling ideas are utilized to restructure the elements and achieve the construction of a smart intelligence service platform for industrial collaborative emergency scenarios.Finally,based on the above research content,a mechanism model for industrial collaborative emergency smart intelligence services driven by multi-source data is constructed,providing platform support,theoretical basis,and reference basis for the construction of smart intelligence service models in various stages.Secondly,establish a smart intelligence service model for industrial collaborative emergency prevention stage.The smart intelligence service model in the prevention stage will leverage blockchain technology and intelligence flow ideas,first clarifying the priorities of the industrial collaborative emergency prevention stage,and exploring the specific needs of industrial collaborative emergency prevention smart intelligence services;Then,based on blockchain,we construct the underlying architecture and operational mechanism of industrial collaborative emergency prevention,and form an industrial collaborative emergency prevention smart intelligence service model that integrates blockchain and intelligence flow.We also sort out the process of industrial collaborative emergency prevention smart intelligence service driven by multi-source data;Finally,taking the semiconductor industry shutdown crisis event as an example,experiments and effect analysis are conducted to verify the advantages of the industry collaborative emergency prevention smart intelligence service model that integrates blockchain and intelligence flow.The prevention stage smart intelligence service constructed in this chapter provides forward-looking,linked,timely,collaborative,and accurate smart intelligence service support for the prevention of industrial crisis events,forming an industrial collaborative emergency prevention smart intelligence service model,and taking the lead in the prevention of industrial crisis events.Thirdly,establish a smart intelligence service model for the emergency preparedness stage of industrial collaboration.Chapter 4 provides intelligent warning and intelligence services during the prevention phase,while Chapter 5 will construct a smart intelligence service model for the industrial crisis event preparation phase based on the warning results.Specifically,this section conducts research on industry crisis event Q&A consulting based on fine-tuning the big language model.Firstly,it attempts to clarify the demand for smart intelligence services in the emergency preparedness stage of industry collaboration and clarify the importance of intelligent Q&A consulting in the preparation stage;Then analyze the feasibility of the big language model in the process of industrial collaborative emergency preparedness,use the P-Tuning method to fine tune the model,construct a local knowledge base based on industry crisis event related question and answer data,standardize the content generated by the model,and use the Lang Chain architecture to build an industrial collaborative emergency question and answer system;Secondly,we will construct a technology architecture and operational mechanism for industrial collaborative emergency preparedness based on big model fine-tuning,forming a smart intelligence service model for industrial collaborative emergency preparedness based on big model fine-tuning,and sorting out the smart intelligence service process for industrial collaborative emergency preparedness driven by multi-source data;Finally,through case analysis of semiconductor industry crisis events,the effectiveness of smart consulting Q&A in the collaborative emergency preparedness stage of the large model industry is verified,and the value of the smart intelligence service model in the preparation stage is explained.Fourthly,establish a smart intelligence service model for industrial collaborative emergency response stage.After completing the construction of the smart intelligence service model in the prevention stage of Chapter 4 and the preparation stage of Chapter 5,this section takes collaboration theory as guidance,adopts alliance blockchain technology to construct the technical architecture of industrial collaborative emergency response smart intelligence service,elaborates on the operational mechanism of industrial collaborative emergency response,and sorts out the process of industrial collaborative emergency response smart intelligence service driven by multi-source data,In order to achieve the rapid and efficient flow of early warning information and emergency plans in the prevention and preparation stages among multiple entities in the industry,and to improve the timeliness,safety, sensitivity,accuracy,and sustainability of early warning information and various preparation plans under the collaborative governance of multiple entities.Taking the emergency intelligence collaborative sharing of the semiconductor industry in the face of the "Sichuan power rationing" emergency event as an example,this paper explains the effectiveness of the alliance chain in the smart intelligence service of industrial collaborative emergency response.Based on the Hyperledger Caliper platform,the performance of the industrial emergency intelligence alliance chain is tested,and the value of the smart intelligence service model of industrial collaborative emergency response driven by multi-source data is finally verified.The smart intelligence service model in the response phase aims to achieve multi subject collaboration and intelligence data collaboration in industrial emergency intelligence,break down data barriers,improve the security,credibility,and traceability of industrial emergency intelligence data,accelerate the speed of industrial emergency response and disposal,and provide stable and reliable smart intelligence service guarantees for industrial development in the response phase.Fifthly,build a smart intelligence service model for industrial collaborative emergency recovery stage.In the final recovery stage of emergency management,efficient,convenient,and smart intelligence services are still needed to intervene in the post crisis recovery process of industrial crisis situations.This section uses the theory of resilience governance to first clarify the specific needs of smart intelligence services in the emergency recovery stage of industrial collaboration,and find the connection between resilience governance theory and smart intelligence services in the recovery stage;Then,the construction of a smart intelligence service model for industrial collaborative emergency recovery based on resilience governance theory is completed from two aspects: technical architecture and operational mechanism;Finally,taking the recovery of semiconductor industry crisis events as an example,this paper elaborates on the operational process of smart intelligence services during the recovery phase,constructs a dynamic model of the industry collaborative emergency recovery smart intelligence service system driven by multi-source data,conducts model simulation and sensitivity analysis,and finally analyzes the value of the smart intelligence service model during the recovery phase.The industrial collaborative emergency recovery smart intelligence service system constructed in this section not only serves the post crisis recovery in crisis situations,but also serves as the "foundation project" of the entire multi-source data-driven industrial collaborative emergency smart intelligence service model,"filling in gaps" for various stages of smart intelligence services,while assisting in the post crisis recovery of industrial crises,It can also ensure the smooth implementation of the industrial collaborative emergency smart intelligence service model driven by multi-source data.Sixth,propose a mechanism and strategy for ensuring industrial collaborative emergency smart intelligence services driven by multi-source data.In the face of practical demand scenarios such as the handling of industrial crisis events in China,the integration of innovation and industrial chains,technological self-reliance and self-improvement,and the breakthrough of external international competitive environment blockades,combined with the research results in Chapter 3 of this article and the constraints of industrial collaborative emergency intelligence services,this section proposes a guarantee mechanism for industrial collaborative emergency smart intelligence services driven by multi-source data from three perspectives: industrial policy,talent cultivation,and scenario traction,Establish a guarantee mechanism system of "industrial policy guidance and incentives-new era intelligence talent assistance-scenario traction and platform empowerment",then propose specific guarantee strategies for industrial collaborative emergency smart intelligence services from the data,technical,and service levels,and finally elaborate on the scenario extension of industrial collaborative emergency smart intelligence services in the implementation of major national strategies,Attempting to empower the implementation of major national strategies with the power of smart intelligence services.This study attempts to enrich the research system of smart intelligence services from a theoretical perspective,expand the application of smart intelligence services in the field of emergency response to industrial crisis events,and deepen the integration and application of industrial data organization and emergency intelligence collaborative sharing driven by multi-source data in industrial collaborative emergency scenarios;At the practical level,this study takes the response of China’s semiconductor industry to power rationing and production stoppage crises as a case study,and uses industry emergency collaborative smart intelligence services as a tool to assist China’s key core industries in breaking through crisis shackles and development barriers,empowering the healthy and orderly development of industries in the complex international situation.This study ultimately developed an overall model of industrial collaborative emergency smart intelligence services,which includes "multi-source data-driven-smart intelligence service platform support-industrial crisis event prevention-big model intelligent consultation Q&A-alliance blockchain industry emergency intelligence collaboration-multi subject collaborative response-post disaster recovery and security strategy".The aim is to maximize the role of this model in crisis event handling scenarios for countries,industries,and enterprises.