Intelligent campus operating system fused intelligent technology architecture

Abstract

The invention discloses an intelligent campus operating system fused intelligent technology architecture. The architecture comprises an infrastructure layer, a system access layer, a system core layer and an application service layer, the system access layer comprises a third-party data source layer, a data preprocessing layer and a data storage layer; the system core layer comprises a platform component layer, a universal capability platform layer and a service encapsulation layer; the universal capability platform layer is used for performing function reconstruction and integration on the public technology component; the business packaging layer is used for packaging different business program libraries; the application service layer comprises an application presentation layer and a service access layer, and provides personalized applications and access of multiple service channels for users. According to the technical framework, through data sharing, equipment interconnection and user management optimization, the user experience is improved, an open, compatible, general enabling, safe and reliable comprehensive basic environment is constructed, and a smart campus operation and management intelligent center with unified planning, unified framework, unified standard and unified operation and maintenance is formed.

Description

Technical Field

[0001] The present invention relates to the field of computer and communication technology, and in particular to a smart campus operating system integrating intelligent technology architecture. Background Art

[0002] In the process of digital transformation of education today, the construction of smart campus has become an important development direction for major universities, secondary vocational schools and some large-scale primary and secondary schools. However, the current construction of smart campus faces many difficulties.

[0003] 1. Lack of coordination between planning and construction Although each school has a plan when building a smart campus, it is difficult to use it as the only standard throughout. Different departments have their own needs at different times, and it is difficult for the information department to coordinate the business function needs of the whole school, causing each department to build on its own according to plans with poor coordination, standardization and low correlation. This has led to the dispersion of information system architecture, data models, and technical standards on campus, forming serious "information islands" and "equipment application islands" phenomena.

[0004] 2. IoT devices and data issues The interfaces and protocols of IoT devices are complex: There are many types of IoT devices in smart campuses. Devices produced by different manufacturers have different interfaces and protocols, which makes it difficult for devices to interconnect and form a unified intelligent perception network.

[0005] Data sources are diverse and heterogeneous: Data sources are rich and varied, including structured business data, semi-structured log data, and unstructured audio, video, and image data, and the data formats and structures vary, posing huge challenges to data integration and sharing.

[0006] Low standardization of data governance: There is a lack of unified data governance standards, and data quality varies, making it difficult to effectively manage and mine data. At the same time, there is a contradiction between data sharing and data security, and departmental interest barriers also hinder the full sharing of data.

[0007] 3. Problems in campus user management There are many user roles on campus, including school leaders, teachers and students, family members of faculty and staff, parents, temporary employees and external visitors, and one person may hold multiple positions, which leads to complex identity and authority management and prone to problems such as authority mismatch, affecting the efficiency and quality of campus management and services. Summary of the invention

[0008] The technical purpose of this invention is to propose a smart campus operating system that integrates intelligent technology architecture, with the construction of a structured, universal, data- and user-operation-standard-based smart campus operating system architecture as the core, and to achieve data sharing and collaboration, improve user experience, optimize business application development, and promote the efficient construction and sustainable development of smart campuses by solving problems such as data management, device interconnection, and user management.

[0009] The technical solution adopted by the present invention to solve its technical problem is: A smart campus operating system integrates intelligent technology architecture, including infrastructure layer, system access layer, system core layer and application service layer; The infrastructure layer is connected to the system access layer and collects the collected data into the system access layer; the system access layer is connected to the system core layer and provides data support for it; the system core layer is connected to the application service layer and provides it with a unified service platform capability, and also provides data storage and management for it; The infrastructure layer includes an information infrastructure unit and an infrastructure intelligence unit, which are used to provide a physical basis and activity carrier for the operation of the smart campus operating system and support the access of intelligent equipment and new generation information technology; The system access layer includes a third-party data source layer, a data preprocessing layer and a data storage layer; the data collected by the infrastructure layer is imported into the third-party data source layer; The third-party data source layer is used to manage third-party data generated by subsystems running independently of the operating system, and the third-party data is stored in different types of databases; Among them, the source data of the third-party data source layer includes structured data, semi-structured data and unstructured data; the structured data comes from the business data generated by the application software in the process of business digitization of various functional departments on campus and the status data of the operation of Internet of Things devices on campus; the semi-structured data comes from the log data generated by the application system; the specific sources of the log data include but are not limited to: network log system, Internet behavior system; the unstructured data comes from audio and video data and image data in actual scenarios, and the actual scenarios at least include: video surveillance of the teaching process and a safe campus.

[0010] The data preprocessing layer is used to translate various data in the third-party data source layer into standard data sources, including unifying data formats and setting mapping relationships to track sources and flows; at the same time, the different communication protocols of intelligent networked devices are translated into standardized communication protocols recognized by the smart campus operating system to ensure interoperability between devices; finally, the translated data is stored in the data storage layer; The data storage layer, including the data source layer, the data warehouse layer and the data application layer, adopts a data storage architecture that complies with national general standards, and is used to centrally manage, store and share various types of campus data, eliminate information islands, realize data interoperability, and provide data support for application services; The data generated in the application service layer is fed back to the data storage layer; Furthermore, the data warehouse layer is further divided into: data detail layer, dimension table layer, data middle layer and data service layer.

[0011] The system core layer includes a platform component layer, a general capability platform layer and a business encapsulation layer; The platform component layer is used to provide a variety of public technical components for the smart campus operating system, which are used to aggregate, clean, govern, store, manage, analyze and mine the standardized source data in the data storage layer, and are also used to standardize data input and output, standardize reusable technical component calls, smart IoT device access and AI calls; The platform component layer includes at least one of the following public technology components: data middle platform component, technology middle platform component, IoT middle platform component, and AI middle platform component; Furthermore, the data middle platform component is based on the data storage layer and combines the international mainstream data governance implementation principles to manage data entry into the lake, data cleaning, data warehousing, data sharing, historical data storage and management, and data application. At the same time, it is equipped with a data security mechanism and combined with metadata management to achieve data traceability and lineage analysis.

[0012] Furthermore, the technical middle-office component is used to provide a public service component for the smart campus, and the public service component is used to provide one or any combination of the following functions: single sign-on, real-name verification, aggregated authentication, aggregated payment, process engine, unified search, message center, digital twin engine, personalized homepage application, and mobile application service management platform.

[0013] Furthermore, the IoT middle platform component is used to software-ize IoT devices, build a digitized physical model, provide unified management of physical models, provide unified management of IoT device status data and business data, and provide a unified calling interface standard for physical models.

[0014] Furthermore, the AI ​​middle-office component is used in the smart campus operating system. In the process of using AI technology, a general access mode is adopted, and based on the large model algorithm library with hybrid deployment of public cloud and private cloud, a series of components of the AI ​​middle-office component are constructed to realize self-training and self-evolution in the smart campus system, and at the same time, the general intelligent algorithm library and general knowledge base are uniformly and effectively managed and operated.

[0015] Among them, the general capability platform layer is used to unify and effectively manage the core elements of the smart campus, including users, physical assets, data, equipment, computing resources and finance, and combine the operating system design concept to build a general smart campus support platform. At the same time, it is used to comprehensively deconstruct the core functions of the public technical components contained in the platform component layer, combine the first principles, recombinant core functional technical components into the smart campus support platform, and comprehensively integrate the various technical requirements of the smart campus operating system to build multiple functional modules and provide general development capabilities to support the integrated management and services of the smart campus operating system.

[0016] Furthermore, the multiple functional modules constructed by the general capability platform layer include at least: user center, data standard center, basic data center, data management center, API application management center, intelligent networked equipment management center, financial center, application security center, credit center, AI training and application center, data visualization center and AI help center.

[0017] Furthermore, the user center is used to manage all types of users in the smart campus, including faculty, students, parents, visitors, etc., and allocate them according to positions and permissions, support one person with multiple positions, and uniformly manage all types of personnel in the school, establish a flexible and scalable unified identity standard, realize user identity standardization, and realize unified authentication and authorization.

[0018] The data standards center is responsible for managing and maintaining the data standards required for the smart campus, such as storage standards, metadata standards, etc., to ensure the intensiveness and standardization of the data structure.

[0019] The basic data center is used to manage the school-level application basic data of the smart campus operating system, including basic school information data, national standard data, user identity biometric database, and other types of general data. The basic data can support the basic functions of the operating system and general functions for all businesses.

[0020] The data management center manages the data warehouse of the data storage layer, provides data display, query, asset catalog management, data channel display and alarm analysis, and supports data operations of the three-list operation system.

[0021] The API application management center is used to manage the basic technical components of the smart campus, provide standardized interfaces such as single sign-on, message push, identity authentication, etc., and simplify third-party system access.

[0022] The financial center is used to uniformly manage the financial and related interfaces of the smart campus, including online payment, aggregated payment, overdue payment alarm and credit evaluation.

[0023] The intelligent networked device management center is used to manage and maintain the intelligent networked devices of the smart campus, support standardized access of devices from different manufacturers, monitor device status and implement a unified control mode.

[0024] The AI ​​training and management center is used to manage AI training modes, integrate AI sample data from different manufacturers, and provide a unified training and calling interface.

[0025] The AI ​​Help Center is used to build a comprehensive user operation question and answer help system, integrate the operation manuals and frequently asked questions of various business systems, and provide real-time help support through AI technology.

[0026] Among them, the business encapsulation layer is used to classify and encapsulate the technical components in the general capability platform layer after comprehensive deconstruction and recombination, and classify and encapsulate the functional applications according to various business scenarios to obtain multiple business model libraries; the various business scenarios include at least management-type business, teaching-type business, resource-type business, and various data analysis and reporting business scenarios.

[0027] Furthermore, the multiple business model libraries include one of the following or any combination: subject data model library, business application model library, object model library, data filling form library, teaching model library, data analysis model library, data report model library, microservice program library, early warning analysis model library, and data element application library.

[0028] The application service layer includes an application presentation layer and a service access layer; Among them, the application presentation layer can be oriented to different user roles, and can automatically match the existing data sources in the data storage layer according to the various business model libraries obtained in the business encapsulation layer, automatically generate actual services, and enable users to filter out the application list according to actual scenario needs and present it in the form of a service collection.

[0029] Furthermore, the specific presentation methods of the application presentation layer include one of the following or any combination: one-stop service, AI human-computer interaction center, one-network management, one-network learning, and campus brain.

[0030] Furthermore, the one-stop service will integrate management business applications through microservices, and display them by category in a unified interface, making it convenient for all teachers and students to handle various work, study and other related businesses while on campus.

[0031] The AI ​​human-computer interaction center is a quick access center that provides problem consultation and application services in the smart campus operating system. It continuously improves and optimizes through AI technology to achieve automated operations, help teachers and students quickly solve problems, and provide a portal for quick access to application services.

[0032] The one-stop online learning system is used to provide students with comprehensive online learning services and supports all-time and all-round smart campus applications. Based on AI technology, the system integrates AI teaching, AI supervision, and AI teaching evaluation functions to provide integrated teaching support.

[0033] The one-network unified management is the operation command center of the smart campus built based on digital twin technology, which is used to achieve unified management and monitoring of the operating status of software and hardware. At the same time, it also has automatic fault detection and repair functions to ensure the smooth operation of the campus system. The campus brain is based on campus governance, combines the various functional modules of the system core layer, and builds a unified intelligent decision-making center and intelligent integrated application center for the smart campus based on the linkage and coordination mechanism of cross-departmental business within the campus. Combined with AI technology, it can support self-evolution and iterative upgrades.

[0034] Among them, the service access layer is used to provide an integrated service entrance to each application in the application presentation layer, and supports multiple service channels; the multiple service channels include but are not limited to PC, mobile, large screen, and tablet computer.

[0035] Furthermore, the smart campus operating system integrates the intelligent technology architecture and also includes a three-list operation system; during the data production and business adjustment process of the smart campus, the three-list operation system forms a responsibility list, a demand list and a negative list through self-coordination and constraints of suppliers, demanders and managers, thereby realizing the self-operation and iterative upgrade of the smart campus operating system.

[0036] Furthermore, the smart campus operating system integrates the intelligent technology architecture and also includes an AI operation center; the AI ​​operation center performs AI parameter annotation on functions at all levels of the smart campus operating system based on the AI ​​middle platform components, and realizes self-learning and training by introducing privately deployed large model algorithms, thereby continuously optimizing system functions and user experience.

[0037] Furthermore, the smart campus operating system integrates the intelligent technology architecture and also includes a security layer; the security layer is used to provide unified information security protection for the smart campus.

[0038] The beneficial effects of the present invention are: 1. Data and equipment management optimization It effectively integrates various data resources in the smart campus, solves the problem of non-standard and heterogeneous data through standardized preprocessing, realizes the standardization of data storage and management, as well as data sharing and interconnection. At the same time, it unifies the communication protocols and access standards of IoT devices, breaks the device application island, and improves the management efficiency and interconnection of devices.

[0039] 2. Efficient business application development and deployment Based on the design of the business encapsulation layer and the application service layer, microservice programs for different business scenarios can be quickly developed and deployed. By prefabricating application templates and configuring AI parameter identifiers, the cost of repeated development is reduced, the development efficiency of business applications is improved, and it can be flexibly customized and iteratively upgraded according to school needs, truly realizing the productization of the delivery process.

[0040] 3. Improved user experience The multi-channel access and AI human-computer interaction mode of the service access layer provide convenient service access methods for different user roles. Components such as the user center and AI help center in the general capability platform layer optimize user authority management and operation guidance, and improve the overall user experience.

[0041] 4. Intelligent system operation and management The three-checklist operation system realizes the self-operation iteration and upgrade of the smart campus, reduces mandatory intervention, and improves the system's adaptability to data production and business adjustments. The AI ​​operation center continuously optimizes system functions and improves the system's intelligence level by introducing large model algorithms for self-learning training.

[0042] 5. Data security and standardization guarantee The security mechanism and data governance process of the data middle-office components ensure data security. The data standard center of the general capability platform layer unifies data standards, ensures data quality and consistency, and lays a solid foundation for the long-term and stable development of smart campuses.

[0043] 6. Meeting diverse campus needs The overall architecture system is highly flexible and scalable, and can adapt to the diverse business needs of different vocational colleges and applied universities, providing strong technical support for the comprehensive construction of smart campuses. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is an overall schematic diagram of the smart campus operating system integrating intelligent technology architecture.

[0045] Figure 2 It is a schematic diagram of the smart campus operating system integrating intelligent technology architecture and functional modules.

[0046] Figure 3 It is a schematic diagram of the data storage layer structure in the technical framework of the present invention.

[0047] Figure 4 It is a diagram of the coordination relationship between various system levels in the technical framework of the present invention. DETAILED DESCRIPTION

[0048] like Figure 1-4 As shown, this embodiment provides a smart campus operating system integrated with intelligent technology architecture, which can provide powerful technical support for various application scenarios in the campus, including smart device access, data sharing and analysis, and intelligent business service management. The system architecture has a clear hierarchy and complete functional modules, which can effectively solve the problems of "information islands" and "device application islands" in the current smart campus construction, ensure data interoperability and collaborative work between departments, and realize the productization of the delivery process.

[0049] like Figure 1 As shown, the smart campus operating system integrates the intelligent technology architecture, including the infrastructure layer, system access layer, system core layer, application service layer, as well as the three-list operation system, AI operation center, and security assurance layer.

[0050] like Figure 2 As shown, the infrastructure layer is connected to the system access layer and imports the collected data into the system access layer; the system access layer is connected to the system core layer to provide data support for it; the system core layer is connected to the application service layer to provide it with a unified service platform capability, and also provides it with data storage and management.

[0051] Combination Figure 2 , expand the various parts of the system architecture for detailed explanation: 1. Infrastructure layer: The infrastructure layer includes information infrastructure units and infrastructure intelligence units, which are used to provide the physical basis and activity carriers for the operation of the smart campus operating system and support the access of intelligent equipment and new generation information technology.

[0052] Among them, there is a general computing resource management platform between the infrastructure layer and the operating system layer, which can unify the management and operation of the computing resources and network resources of the infrastructure, and provide the smart campus operating system with the ability to reallocate computing resources and network resources.

[0053] 2. System access layer: The system access layer includes a third-party data source layer, a data preprocessing layer and a data storage layer.

[0054] (2.1) Third-party data source layer The data collected by the infrastructure layer is fed into the third-party data source layer; the third-party data source layer is used to manage the third-party data produced by the subsystems running independently of the operating system, and the third-party data is stored in different types of databases.

[0055] The third-party data source layer is mainly in the process of smart campus construction. Because the top-level design principles are not followed, the business application subsystems built by the business departments at different times, as well as IoT devices from different manufacturers at different times, use different communication protocols, which naturally form data islands and device application islands. This service layer covers the third-party business subsystems and IoT application subsystems.

[0056] The source data of the third-party data source layer, including structured data, semi-structured data and unstructured data, is an independently operated business subsystem used to provide production data for the smart campus operating system.

[0057] Among them, structured data comes from the business data generated by the application software system during the digitalization of business of various functional departments on campus, and the status data of the operation of IoT devices on campus.

[0058] Among them, semi-structured data comes from log data generated by application systems such as network log systems and Internet behavior systems.

[0059] Among them, unstructured data comes from audio, video and image data in actual scenarios such as teaching processes and video surveillance of safe campuses.

[0060] (2.2) Data preprocessing layer The data preprocessing layer (IoT device data preprocessing layer) is mainly used for intelligent operation. The operating system can identify and process business data at any time, translate the business data generated by the third-party data source layer into a standard data structure, and convert the IoT device communication protocol into a standard communication method, similar to the principle of a hardware interface converter. The entire data preprocessing layer is the most critical application service layer that the operating system can meet for unified upgrades and iterations.

[0061] (2.3) Data storage layer like Figure 3 As shown, the data storage layer includes a data source layer, a data warehouse layer, and a data application layer, and adopts a data storage architecture that complies with national general standards.

[0062] Among them, the data source layer (also known as the data lake) mainly stores and manages various source data, including structured, semi-structured, and unstructured data; in the data warehouse layer and the data application layer, various data are stored and managed as structured data. From the data source layer to the data warehouse layer, semi-structured and unstructured data are processed by the relevant functional modules of the data governance tool. After structuring, they are written into the database of the corresponding level of the data warehouse, and then applied to the subsequent functional level, so as to realize the centralized management and sharing of data resources, eliminate information islands, realize the interoperability of data, and provide data support for application services.

[0063] Among them, the data warehouse layer is divided into: data detail layer, dimension table layer, data intermediate layer and data service layer.

[0064] The data generated in the application service layer is fed back to the data storage layer; 3. System core layer: The core layer of the system includes the platform component layer, the general capability platform layer and the business encapsulation layer.

[0065] (3.1) Platform component layer The platform component layer is used to provide a variety of public technical components for the smart campus operating system, which are used to aggregate, clean, govern, store, manage and analyze the standardized source data in the data storage layer. It is also used to standardize data input and output, standardize the call of reusable technical components, access smart IoT devices and AI calls.

[0066] The platform component layer includes data middle-office components, technical middle-office components, IoT middle-office components and AI middle-office components, which are used to standardize data input and output interfaces, technical component calling interfaces, smart IoT device access standards and AI calling interfaces.

[0067] Among them, the data middle platform component is mainly used to manage the processes of data entering the lake, data cleaning, data entering the warehouse, data sharing, historical data storage and management, data application, etc. At the same time, it is equipped with a data security mechanism, combined with metadata management, to achieve data traceability and lineage analysis, and based on the general data governance principles, complete the construction of the standardized data middle platform component of the smart campus. The architecture of data storage and management is completely based on the data storage structure requirements of the data storage layer. The algorithms for data exchange, data cleaning, and data lineage analysis are provided by different data middle platform component tools themselves, while the metadata standards and subject database structures are completely based on the standard center that comes with the smart campus operating system for management.

[0068] Among them, the technical middle platform component is used to provide public service components for the smart campus, and the public service components are used to provide one of the following functions or any combination: single sign-on, real-name verification, aggregate authentication, aggregate payment, process engine, unified search, message center, digital twin engine, personalized homepage application, mobile application service management platform. The technical middle platform component will uniformly manage and operate these functional components, and provide a unified external call method and a standard SDK library. For example, based on the single sign-on interface, users can directly enjoy all authorized and available smart campus application services after unified identity authentication.

[0069] Among them, the IoT middle platform component is used to manage and maintain IoT devices in the process of building a smart campus. At the same time, based on the construction concept of "software-defined IoT", the IoT devices are software-based, and a data-based physical model is constructed to provide unified management of the physical model, and provide unified management of IoT device status data and business data, as well as a unified calling interface standard for the physical model, and re-empower IoT devices according to the school's usage scenarios. For example, after the lighting fixtures in the classroom are software-based, the class mode, the get out of class mode, the evening self-study mode, etc. can be realized according to the class schedule, achieving energy saving and emission reduction effects.

[0070] Among them, the AI ​​middle-office component is used in the smart campus operating system. In the process of using AI technology, a general access mode is adopted, and based on the large model algorithm library deployed in a hybrid manner of public cloud and private cloud, a series of components of the AI ​​middle-office component are built to realize self-training and self-evolution in the smart campus system, while unified and effective management and operation of the general intelligent algorithm library and general knowledge base.

[0071] Among them, the general intelligent algorithm library mainly includes biometric recognition algorithm, speech recognition algorithm, semantic analysis algorithm, etc. These algorithm libraries can be open source or other third-party commercial algorithm libraries, and can support online upgrades and iterations.

[0072] (3.2) General capability platform layer The general capability platform layer manages the core elements of the smart campus, including users, physical assets, data, equipment, computing resources, and finance in a unified and effective manner. It combines the operating system design concept to build a general smart campus support platform. At the same time, it comprehensively deconstructs the core functions of public technical components such as data middle platform components, technical middle platform components, IoT middle platform components, and AI middle platform components. It combines the first principles to simplify and reorganize the core functional technical components into the smart campus support platform. It builds multiple functional modules based on the various technical requirements of the operating system and provides general development capabilities to support the integrated management and services of the smart campus operating system. Among them, public technical components such as data middle platform, technology middle platform, IoT middle platform, and AI middle platform can come from different third-party manufacturers with different technical routes, or they can be factory products of the same manufacturer with the same technical route. They fully adopt the loose coupling design concept to make professional and open technical components for a certain technical field. Among them, multiple functional modules include but are not limited to: user center, data standard center, basic data center, data management center, API application management center, intelligent networked equipment management center, financial center, application security center, credit center, AI training and application center, data visualization center and AI help center.

[0073] Among them, the user center is used to manage user data of all types of smart campus usage scenarios, and maintain corresponding permissions. The users include regular faculty and staff, non-regular contract personnel, temporary employees, students, parents, family members of faculty and staff, visitors, etc. Different permissions are assigned according to different job requirements. It is also suitable for one person in multiple positions, and unified management of various types of personnel in the school is carried out. A flexible and scalable unified identity standard is established to achieve user identity standardization, unified authentication, and unified authorization.

[0074] Among them, the Data Standards Center is used to manage and maintain the data standards involved in the smart campus operating system, including data storage standards, metadata standards, data standards for various subject domains, etc., to adopt an intensive and standardized data structure and a supporting data dictionary for the smart campus.

[0075] Among them, the basic data center is used to manage the school-level application basic data of the smart campus operating system, including school information basic data, national standard data, user identity biometric database, and other types of general data. This basic data can support the basic functions of the operating system and general functions for all businesses. For example, building a school-level unified face database platform to achieve unified standards, unified interfaces, and unified modeling for face databases can support the use of the same method to call face recognition functions in different scenarios such as apartment access control subsystems, supervision teaching subsystems, and canteen face-swiping consumption subsystems, truly realizing "one-face access".

[0076] Among them, the data management center is used to manage the data warehouse of the data storage layer, including data structured display, query, data asset catalog management, data channel display and alarm analysis, and the "three lists" model data operation center.

[0077] Among them, the API application management center is used to manage the basic technical components of the smart campus, and integrate the technical middle-end component tools of different manufacturers or different technical routes to realize a unified and standardized series of interfaces, including single sign-on interface, message push interface, identity authentication interface, process engine call interface, digital twin engine call interface, etc., so that third-party calls do not require writing redundant code.

[0078] For example: message push interface. There are many types of message push methods, such as mobile phone text messages, WeChat messages, emails, etc. No matter which operator channel is used, or whether Internet traffic is used to push messages to mobile terminals, standardized interfaces can be called uniformly and a unified message format can be used.

[0079] In addition, the API application management center can manage all interface calls in a unified classification, including call records, call exceptions, call permission verification and other call process management, and classify the content of the call interface. For example, the message interface can store, manage, query, and perform statistical analysis on the message content.

[0080] Among them, the Financial and Banking Center is used to uniformly manage the relevant financial and financial interfaces of the smart campus, including online payment, offline code scanning, payment records, aggregated payment interfaces, bank payment channels, overdue payment alarms, credit evaluation, etc.

[0081] In addition, the financial and banking center is used in various financial transaction scenarios such as payment and financial reimbursement, including prepaid smart water control, smart electric control, on-campus canteen consumption, on-campus public housing rent, on-campus parking payment, and various learning payments, such as CET-4 and CET-6 English test payment, make-up test payment, etc., as well as various subsidy distribution, faculty and staff reimbursement, etc. These application scenarios cover the important link of "finance" in the "people, finance, and materials" of the smart campus management system.

[0082] In addition, the Financial and Banking Center can also judge the creditworthiness of traders based on analysis of transaction data, such as analysis of arrears, and set the credit rating of traders.

[0083] Among them, the intelligent networked equipment management center is used to uniformly manage and maintain all intelligent networked equipment in the smart campus, realize a unified and standardized equipment access mode for the same type of equipment from different manufacturers, build a unified object model library, monitor equipment status in real time, display alarms, and unify the calling mode of equipment downlink control.

[0084] In addition, the function of the intelligent networked equipment management center is built on the data and equipment preprocessing layer. After the communication protocol of the equipment access is converted, the intelligent networked equipment management center can connect and communicate with the intelligent IoT devices in a standardized access method, realize equipment status monitoring and control, and obtain the status data and business data generated by the equipment.

[0085] The status data generated by the device refers to the current status of the device, such as switch status, fault alarm status, etc.

[0086] The business data generated by the device refers to the functional data generated when the device is running, such as the measurement data of a smart meter and the water flow data of an ultrasonic flow meter.

[0087] Among them, the AI ​​training and management center is used to uniformly manage and maintain the AI ​​training model, transform the AI ​​sample data training model from different manufacturers, implement a unified training model for users, and call the interface.

[0088] In addition, the AI ​​training and management center can uniformly manage and maintain the knowledge base used for training, uniformly manage and maintain the training models, and uniformly record and analyze the process of calling interfaces.

[0089] Among them, the AI ​​Help Center is used to build a comprehensive Q&A help center for users of the overall smart campus operating system. The operation manuals and frequently asked questions of different business systems and business applications are uniformly trained using AI middle-office component tools to realize a help center that can be called in real time during any user operation.

[0090] In addition, the AI ​​Help Center can be embedded in various functional points of the smart campus operating system and can be automatically awakened to provide users with a full range of user experience. For example, when a certain function of the device management center is required, the AI ​​Help Center can be awakened to directly guide users to perform step-by-step operations. At the same time, it supports hyperlinks to jump to the specified function interface for on-site operations.

[0091] Among them, modules such as the AI ​​Training and Management Center and the AI ​​Help Center, and the capabilities of self-training and deep learning are all based on AI middle-end component tools.

[0092] (3.3) Business encapsulation layer The business encapsulation layer, based on the general capability platform layer and the data storage layer, reconstructs data and business in a scenario-based manner, reduces repeated development costs, prefabricates application templates, forms an application template library, and effectively manages the application template library.

[0093] Among them, the application template library designs professional application service templates according to different usage scenarios and based on the understanding of the industry, and configures AI parameter identification, which can be quickly iterated and upgraded, and can be flexibly configured and used. The usage scenarios can be classified according to different roles, different administrative functions, etc. Each application service template has configured data support conditions, usage conditions, process nodes and other indicator parameters, providing unified support for the later realization of intelligent application matching.

[0094] Among them, the business encapsulation layer mainly classifies and encapsulates functions for management-type business, teaching-type business, resource-type business, and various data analysis and reporting business scenarios in the field of smart campuses to obtain multiple business model libraries.

[0095] The multiple business model libraries include one of the following or any combination: subject data model library, business application model library, object model library, data filling form library, teaching model library, data analysis model library, data report model library, microservice program library, early warning analysis model library, and data element application library.

[0096] For example: The subject data model library is an application service template for building various subject data during the operation of the smart campus, including data related to subjects such as personnel, teaching affairs, scientific research, and finance. These data are classified, counted, queried under certain conditions, and analyzed through modeling portraits. A collection of application models is formed for unified management and operation, which enables the addition, deletion, modification, and iterative upgrade of application service templates.

[0097] For example: the business application model library is based on common business application scenarios of smart campuses to build various application microservice templates, such as welcome services, personnel title evaluation, and contactless dormitory checks. These application scenarios can be fine-tuned and configured according to the actual application scenarios of different universities, and can be put into actual scene applications without repeated development.

[0098] In order to realize AI empowerment, each application service template has corresponding AI parameter annotations. For example, the personnel theme data application model has its corresponding AI parameter identification, including its corresponding user permissions, data field name, whether it is empty, application scenario description, etc., to provide the function of automatically matching data application models for intelligent generation of application services.

[0099] 4. Application service layer: The application service layer includes an application presentation layer and a service access layer.

[0100] (4.1) Application presentation layer The application presentation layer can be oriented to different user roles, and can automatically match the existing data sources in the data storage layer according to the various business model libraries obtained in the business encapsulation layer, automatically generate actual services, and enable users to filter out the application list according to the actual scenario needs, and present it in the form of a service collection. Its specific presentation methods include one or any combination of the following: one-stop service, AI human-computer interaction center, one-network management, and one-network learning.

[0101] Among them, the one-stop service is to concentrate management-type business application microservices in a unified interface for classification, display and access, so that all teachers and students can handle their work, study and other related business while on campus, such as teacher professional title evaluation, student leave, etc. At the same time, automatic matching services can be realized based on AI operation technology.

[0102] Among them, the AI ​​human-computer interaction center is used as the interface between the smart campus and users, and provides users with convenient service access channels through various terminal devices such as mobile phones, computers, etc. Its main users are: all teachers and students, users at all levels, who can answer various questions raised by users in a unified question-and-answer consultation interface, and can realize end-to-end service, directly point to application links, quickly answer and recommend services, build a problem consultation service center in the process of smart campus application, and improve and iterate based on AI technology to realize automatic operation.

[0103] Among them, Yiwangtongxue is used to provide students with comprehensive online learning services, and supports all-time and all-round smart campus applications. Based on AI technology, the system integrates AI teaching, AI supervision, and AI evaluation functions to provide integrated teaching support.

[0104] Among them, one-network management is based on digital twin technology to build an operation command center for a smart campus, realizing unified management and monitoring of the operating status of software, hardware, etc.; at the same time, it also has automatic fault detection and repair functions to ensure the smooth operation of the campus system.

[0105] For example: For information management departments, they can use the capabilities of the digital twin engine to build a smart campus operation command center, realize real-time unified management and monitoring of the operating status of software, hardware, etc. during the construction of the smart campus, and realize automatic fault detection and fault repair operation and maintenance of software and hardware.

[0106] The campus brain is based on the premise of campus governance, combining the various functional modules of the core layer of the system, establishing a fast and efficient linkage and coordination mechanism based on cross-departmental business within the campus, and building a unified intelligent decision-making center and intelligent integrated application center for the smart campus. Combined with AI technology, it can support self-evolution and iterative upgrades.

[0107] For example: For school leaders at all levels, they can use the digital twin platform or various BI tools to build various types of leadership cockpits for smart campuses, such as teacher data summary analysis, academic early warning analysis, and discipline construction forecast trend analysis.

[0108] For example, for campus management, through the intelligent collaboration of video surveillance, sensor networks and business applications, the whole process of campus operation and management events, from automatic discovery of alarms to collaborative business applications, can be managed and controlled. For example, the integrated application of emergency management for student dormitories can, based on the results of video analysis, enable one-click gate opening and one-click unlocking of all floors of the apartment when a fire or other disaster occurs.

[0109] (4.2) Service access layer The service access layer is used to provide an integrated service portal to each application in the application presentation layer, and supports multiple service channels; the multiple service channels include but are not limited to PC, mobile, large screen, and tablet computer.

[0110] 5. Three-list operation system: The three-list operation system is used to build a self-operated system in the process of data production and business adjustment in smart campuses to reduce mandatory intervention mechanisms. The suppliers, demanders, and managers (such as information management departments) of data and business generate three lists under the premise of self-coordination and restraint: a responsibility list, a demand list, and a negative list. The operation management platform based on the three lists can be used for self-operated iteration and upgrading of the smart campus operating system.

[0111] 6. AI Operations Center The AI ​​operation center is based on the AI ​​middle platform component. It labels the functions of each level of the smart campus operating system with AI parameters, introduces large-model algorithms for private deployment, and continuously optimizes system functions and user experience through self-learning and training.

[0112] 7. Security layer The security layer is used to provide unified information security for the smart campus operating system. Its specific requirements can be referred to the requirements of the national general smart campus architecture model, which will not be introduced in this article.

[0113] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications shall all fall within the protection scope of the claims attached to the present invention.

Claims

1. A smart campus operating system integrating intelligent technology architecture, characterized in that: Includes infrastructure layer, system access layer, system core layer and application service layer; The infrastructure layer is connected to the system access layer and collects the collected data into the system access layer; the system access layer is connected to the system core layer to provide data support for it; The system core layer is connected to the application service layer to provide it with a unified service platform capability, and also provides it with data storage and management; The infrastructure layer includes an information infrastructure unit and an infrastructure intelligence unit, which are used to provide a physical basis and activity carrier for the operation of the smart campus operating system and support the access of intelligent equipment and new generation information technology; The system access layer includes a third-party data source layer, a data preprocessing layer and a data storage layer; The data collected by the infrastructure layer is imported into the third-party data source layer; The third-party data source layer is used to manage third-party data generated by subsystems running independently of the operating system, and the third-party data is stored in different types of databases; The data preprocessing layer is used to translate various types of data in the third-party data source layer into standard data sources, and translate different communication protocols of various intelligent networked devices into standardized communication protocols recognized by the smart campus operating system to ensure the interconnection between devices, and finally store the translated data in the data storage layer; The data storage layer adopts a data storage architecture that complies with national general standards, and is used to centrally manage, store and share various types of data on the smart campus, eliminate information islands, achieve data interoperability, and provide data support for application services; The data generated in the application service layer is fed back to the data storage layer; The system core layer includes a platform component layer, a general capability platform layer and a business encapsulation layer; The platform component layer is used to provide a variety of public technical components for the smart campus operating system, which are used to aggregate, clean, govern, store, manage, analyze and mine the standardized source data in the data storage layer, and are also used to standardize data input and output, standardize reusable technical component calls, smart IoT device access and AI calls; The general capability platform layer is used to uniformly and effectively manage the core elements involved in the operation of the smart campus, and to build a general support platform for the smart campus operating system; it is also used to comprehensively deconstruct the core functions of the various public technical components contained in the platform component layer, and recombine the core functional technical components into the general support platform, build multiple functional modules and provide general development capabilities to support the integrated management and services of the smart campus operating system; the core elements of the operation of the smart campus include users, physical assets, data, equipment, computing resources and finance; The business encapsulation layer is used to classify and encapsulate the technical components in the general capability platform layer after comprehensive deconstruction and reassembly according to various business scenarios, so as to obtain multiple business model libraries; the various business scenarios at least include management-type business, teaching-type business, resource-type business, and various data analysis and reporting business scenarios; The application service layer includes an application presentation layer and a service access layer; The application presentation layer can be oriented to different user roles, and can automatically match the existing data sources in the data storage layer according to the various business model libraries obtained in the business encapsulation layer, automatically generate actual services, and enable users to filter out the application list according to actual scenario needs and present it in the form of a service collection; The service access layer is used to provide an integrated service entry for each application in the application presentation layer.

2. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The source data of the third-party data source layer includes structured data, semi-structured data and unstructured data; The structured data is derived from the business data generated by the application software during the business digitization process of each functional department on campus and the status data of the operation of IoT devices on campus; The semi-structured data comes from log data generated by the application system; The unstructured data comes from audio, video and image data in actual scenarios, and the actual scenarios at least include: video surveillance of the teaching process and a safe campus.

3. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The data warehouse layer is further divided into: data detail layer, dimension table layer, data middle layer and data service layer.

4. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The platform component layer includes at least any one of the following public technical components: data middle platform component, technology middle platform component, IoT middle platform component and AI middle platform component; The data middle platform component is based on the data storage layer and is used to manage data entry into the lake, data cleaning, data warehousing, data sharing, historical data storage and management, and data application. It also provides a data security mechanism and metadata management to achieve data traceability and lineage analysis. The technical middle platform component is used to provide a public service component for the smart campus, and the public service component is used to provide one or any combination of the following functions: single sign-on, real-name verification, aggregate authentication, aggregate payment, process engine, unified search, message center, digital twin engine, personalized homepage application, mobile application service management platform; The IoT middle platform component is used to softwareize IoT devices, build a digitized physical model, provide unified management of physical models, provide unified management of IoT device status data and business data, and provide a unified calling interface standard for physical models; The AI ​​middle platform component is used in the smart campus operating system. In the process of using AI technology, a general access mode is adopted, and based on the large model algorithm library deployed in a hybrid manner of public cloud and private cloud, a series of components of the AI ​​middle platform component are constructed to realize self-training and self-evolution in the smart campus system, while uniformly and effectively managing and operating the general intelligent algorithm library and general knowledge base.

5. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The multiple functional modules constructed by the general capability platform layer include at least: user center, data standard center, basic data center, data management center, API application management center, intelligent network equipment management center, financial center, application security center, credit center, AI training and application center, data visualization center and AI help center.

6. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The multiple business model libraries include one of the following or any combination: subject data model library, business application model library, object model library, data filling form library, teaching model library, data analysis model library, data report model library, microservice program library, early warning analysis model library, and data element application library.

7. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The specific presentation methods of the application presentation layer include one of the following or any combination: one-stop service, AI human-computer interaction center, one-network management, one-network learning, and campus brain; The one-stop service is used to integrate management business applications through microservices and display them by category in a unified interface, making it convenient for all teachers and students to handle corresponding business during their stay at school; The AI ​​human-computer interaction center is a quick access center that provides problem consultation and application services in the smart campus operating system. It continuously improves and optimizes through AI technology to achieve automated operations, help teachers and students quickly solve problems, and provide a portal for quick access to application services. The one-stop learning platform is used to provide students with comprehensive online learning services, and supports all-time and all-round smart campus applications. Based on AI technology, it integrates AI teaching, AI supervision and AI teaching evaluation functions to provide integrated teaching support. The one-network unified management is the operation command center of the smart campus built based on digital twin technology, which is used to achieve unified management and monitoring of the operating status of software and hardware. At the same time, it also has automatic fault detection and repair functions to ensure the smooth operation of the campus system. The campus brain is based on campus governance, combines the various functional modules of the system core layer, and builds a unified intelligent decision-making center and intelligent integrated application center for the smart campus based on the linkage and coordination mechanism of cross-departmental business within the campus. Combined with AI technology, it can support self-evolution and iterative upgrades.

8. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The integrated intelligent technology architecture also includes a three-list operation system; during the data production and business adjustment process of the smart campus, the three-list operation system forms a responsibility list, a demand list and a negative list through self-coordination and constraints of suppliers, demanders and managers, thereby realizing the self-operation and iterative upgrade of the smart campus operating system.

9. A smart campus operating system integrating intelligent technology architecture as claimed in claim 1, characterized in that: The integrated intelligent technology architecture also includes an AI operation center; the AI ​​operation center performs AI parameter annotation on functions at all levels of the smart campus operating system based on the AI ​​middle-end components, and realizes self-learning and training by introducing privately deployed large-model algorithms, thereby continuously optimizing system functions and user experience.

10. The smart campus operating system integrated with intelligent technology architecture as claimed in claim 1, characterized in that: The framework also includes a security layer; the security layer is used to provide unified information security protection for the smart campus operating system.

Images