Hydraulic engineering and environmental geological information system based on service full life cycle digitization

Abstract

The application provides a hydraulic and environmental geological information system based on service full life cycle digitization, and the system framework comprises five parts of infrastructure, data center, function hub, application scene and user group, hydraulic and environmental geological services are divided into four fixed basic process units of service deployment, service execution, service inspection, data management and application, a digital closed-loop management based on a PDCA cycle and covering the full life cycle of hydraulic and environmental geological services is constructed; a hydraulic and environmental geological big data center composed of hydraulic and environmental geological discipline knowledge, technical rules, service knowledge, algorithm models and service data is established, intelligent control of hydraulic and environmental geological service processes is realized based on big data technology and artificial intelligence technology; based on software engineering principles, modular design methods, various software design patterns, micro-service architecture and interface technology are adopted, and the system is divided into five function modules of service management, service management, technology management, model management and data management.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of digital and intelligent construction of water conservancy and environmental geological information, and particularly relates to a water conservancy and environmental geological information system based on business full life cycle digitalization. BACKGROUND

[0002] With the gradual and widespread application of advanced information technology in traditional industries, traditional water conservancy and environmental geological information systems usually adopt a monolithic architecture, which has problems such as high system coupling, poor scalability, and difficult maintenance. With the development of big data, AI, micro-service technology, and the digitalization of traditional geological industries such as water conservancy and environment, there is an urgent need for a digital system architecture that covers the full life cycle of water conservancy and environmental geological business to realize intelligent and data-driven management of business processes. By comprehensively using advanced technologies such as big data, AI, and micro-services, the traditional geological industry such as water conservancy and environment can be closely integrated with information technology, promoting the digitalization and intelligent transformation of the full life cycle of business and the digitalization and upgrading of the industry. This is an inevitable requirement for the development of traditional geological industries such as water conservancy and environment.

[0003] The existing software system has problems such as lack of digitalization of the full life cycle of water conservancy and environmental business and intelligent control of water conservancy and environmental business processes, and difficulty in expanding new formats and new technologies. Specifically, it mainly includes:

[0004] (1) Lack of digital closed-loop linkage in each business link, and the full life cycle of water conservancy and environmental business closed-loop management digitalization has not been realized. The existing system mainly focuses on the digitalization of the geological data collection (survey) process, and rarely involves front-end work deployment, back-end data quality evaluation and review, and sharing and utilization management. The business process is fragmented, and each business link lacks digital closed-loop linkage, and the full life cycle of water conservancy and environmental geological business closed-loop management digitalization has not been formed.

[0005] (2) Lack of dynamic control capability based on big data and AI, and low intelligent degree of water conservancy and environmental business process control. The existing system mainly focuses on the digitalization of the geological data collection (survey) technology process, and the combination of subject knowledge, technology method rules, and digital technology involved in various technology methods of water conservancy and environmental geological data collection (survey) is not enough. Lack of dynamic control capability based on big data and AI, and low digitalization degree of water conservancy and environmental geological business.

[0006] (3) Poor system flexibility and scalability, difficult to adapt to the requirements of new formats and new technology expansion. The existing system mainly focuses on the digitalization of mature geological survey technology methods, and has obvious characteristics of high cohesion and high coupling. The flexibility and scalability of the system are poor, and it is difficult to adjust and improve existing functions and expand new functions brought by new formats and new technologies. SUMMARY

[0007] The invention aims to provide a water conservancy and environmental geology information system based on business full life cycle digitization.

[0008] The invention aims to provide a water conservancy and environmental geology information system based on business full life cycle digitization.

[0009] A water conservancy and environmental geology information system based on business full life cycle digitization, comprising:

[0010] Infrastructure: including data acquisition, network communication, data storage and processing server, user terminal equipment, basic information and state information of infrastructure as system data, stored and updated regularly by MySQL database, system based on basic information and state information of infrastructure, monitoring and discovering equipment abnormal state, and issuing monitoring and early warning instructions;

[0011] Data center: according to data source, characteristics and purpose, divided into five types of management, including bottom plate data, knowledge data, model data, business data and system data, based on the characteristics of multi-source, heterogeneous and large amount of water conservancy and environmental data, using PostgreSQL+MySQL+Hadoop database, descriptive electronic file, multimedia file, graphic file and other forms of mixed storage mode, combining bottom plate data, knowledge data, model data and business data, using multi-source data fusion, big data technology and artificial intelligence technology, simulating field experts, building water conservancy and environmental knowledge graph and business and data correlation model, assisting intelligent design of business deployment, intelligent control of business execution, intelligent analysis of business inspection and intelligent prediction of data application, setting access permission control for various data, providing data query and statistical analysis functions according to access permission control;

[0012] Function center: divide the water conservancy and environmental geology business into four fixed basic process units of business deployment, business execution, business inspection, data management and application, build a digital closed-loop management based on PDCA cycle covering the whole life cycle of water conservancy and environmental geology business, build a large database of water conservancy and environmental geology composed of discipline knowledge, technical rules, business knowledge, algorithm model and historical data, based on big data and artificial intelligence technology, carry out big data driven intelligent control of water conservancy and environmental geology business process, adopt modular design method, separate the management contents of service application, business process, technical method, algorithm model and data resource into five function modules of service management, business management, technical management, model management and data management, adopt abstract factory software design pattern between modules, connect through interface with loose coupling, adopt micro service development framework integration;

[0013] Application scenario: take industry field-business type and business type-technical method as factory-product family, adopt abstract factory software design pattern and interface technology to build a process model of water conservancy and environmental geology information system based on digitalization of business whole life cycle, based on the expansion of future industry field, extension of industry chain and change of technical method, expand applicable industry field, business type and technical method;

[0014] User group: including water conservancy and environmental engineers to carry out water conservancy and environmental data collection and engineering project construction work, water conservancy and environmental researchers to carry out water conservancy and environmental three-dimensional modeling and digital twin construction work, project management personnel to carry out project implementation whole life cycle management work, to carry out resource development, engineering construction, disaster prevention and ecological restoration industry management work, to carry out remote command work of emergency events, to query and search water conservancy and environmental information and services, covering all roles in water conservancy and environmental industry chain.

[0015] Further, the infrastructure includes data collection, network communication, data storage and processing server, user terminal equipment, including:

[0016] Data acquisition equipment: including general water conservancy and environmental field manual collection equipment and remote real-time automatic collection equipment, the data collected by field manual collection equipment is checked and controlled by field experts to control data quality, adopts data entry system manual input and OCR technology and ASR technology intelligent collection data, and is transmitted to function center for processing, the data collected by remote real-time automatic collection equipment is checked and controlled by data checking algorithm conforming to discipline knowledge and technical rules, and is transmitted to function center for processing through protocol interface and Internet of Things communication technology, sensitive data is desensitized by encryption technology, transmitted by secure transmission protocol and access permission control, and the collected data is stored in business database, and the remote real-time automatic collection equipment has data local short-term storage function;

[0017] Network communication equipment: including wide area Internet, local area Internet, Internet of Things, and routers, switches, firewall facilities, using distributed collaborative network architecture and load balancing, using secure transmission protocol, encryption technology decryption, setting up firewall, deploying intrusion detection and defense system and network monitoring and operation tool measures to build network security protection system;

[0018] Data storage and processing server: including self-built computer room and service provider's file server, database server, application server, storage server supports mass data storage by configuring large capacity hard disk and SSD, using RAID, load balancing, cluster architecture, data redundancy and disaster recovery management, application server uses computing server, and two sets of equipment are configured in 1:1 scale;

[0019] User terminal equipment: including service console, user computer, display large screen, tablet computer and mobile phone, user terminal uses system function according to user permission control difference through protocol interface.

[0020] Further, the data center: according to data source, characteristics and use, is divided into five types of bottom plate data, knowledge data, model data, business data and system data for management, including:

[0021] Knowledge data: including subject knowledge data, technical rule data, business knowledge data and data directory data, data directory data is converted into PDF file format and saved in data directory database as original data, and data information is registered in data directory, using machine learning and artificial learning combination, according to unified standardization and structuring requirements, after data cleaning, data integration and data conversion, using PostgreSQL+MySQL+Hadoop database, descriptive electronic file, multimedia file and graphic file form, it is divided into subject knowledge data, technical rule data and business knowledge data three kinds of sub database for saving, based on subject knowledge data, instant text and graphic prompt function is provided, data dictionary is provided as standardization option, using responsibility chain design mode, according to technical rule data and business knowledge data, business process is assembled, based on AOP technology and interface technology, instant quality check, error warning and auxiliary acceptance of data are carried out;

[0022] Model data: created when designing model, using MySQL database, descriptive electronic file, multimedia file and graphic file form to store functional conceptual model design scheme structured model elements, text description, audio and video and spatial graphic data, model parameters are updated when model is modified and optimized in service configuration and optimization, business configuration and technical configuration, and provide prototype template for business management;

[0023] Business data: stored in the form of PostgreSQL+MySQL+Hadoop database, descriptive electronic files, multimedia files, graphic files, when business management, create the business data structure of the corresponding business, based on technical method reliability, instrument precision, technical personnel level, business process compliance, data integrity, data timeliness factor, use hydraulic and environmental data quality confidence index HEEDQI for quality evaluation and quality labeling, the calculation formula of HEEDQI is as follows: Wherein represents the number of quality factors participating in the calculation of the hydraulic and environmental data quality confidence index, represents the quality factor, including technical method reliability, instrument precision, technical personnel level, business process compliance, data integrity, data timeliness, represents the total number of samples of the quality factor, that is, the total number of technical methods used, represents the sample of the quality factor, represents the weight of the quality factor, The value is between 0 and 1, , represents the sample of the quality factor, The value is between 0 and 1, represents the artificial intervention correction coefficient, which is determined by machine learning value and field expert, The value is between 0 and 1,

[0024] represents the artificial intervention correction coefficient, which is determined by machine learning value and field expert, The value is between 0 and 1,

[0025] System data: according to user permissions, application field knowledge, technical rules, and the principle of agreement greater than configuration, establish system database structure and system data while working deployment, system data is intelligently set and modified according to business technical rules and system running state and user configuration modification, using MySQL database, XML file form storage.

[0026] Further, divided into service management, business management, technical management, model management, data management five independent function modules, including:

[0027] Service management module: responsible for the system service registration, discovery, call and monitoring, based on modular design method, divided into industry field, business type, technical method, algorithm model, data resource five modules vertically, using micro service development framework, using micro service discovery and management tools, integrated containerized deployment and service orchestration tools, for the automatic management and expansion of micro services, provide unified API gateway, integrated user authentication authorization protocol and network security protocol management micro service call and permission control, using RESTful API and message queue to realize the communication between services, service management module uses adapter mode to provide micro service management function;

[0028] Business management module: using modular design method, multiple software design patterns and interface technology, providing intelligent control of various application scenarios and industry fields, various business type business process management process and management elements;

[0029] Based on the builder software design pattern, the water conservancy and environment business PDCA process model is constructed, and the water conservancy and environment technical method life cycle is divided into four fixed PDCA basic process units of deployment business deployment Plan, business execution Do, business inspection Check, data management and application Application. The business process abstract builder interface is used as the top interface of various business processes, and the public interface of business deployment, business execution, business inspection, data management and application is provided;

[0030] Based on the abstract factory design pattern, the water conservancy and environment business process structure model is constructed, and the industry field and specific industry field are used as the abstract factory interface and specific factory class respectively, and various types of water conservancy and environment business are used as water conservancy and environment business products. Inherit the above business process abstract builder interface to build different water conservancy and environment business abstract product interface, and provide specific water conservancy and environment business implementation corresponding to different industry fields;

[0031] The bridge design pattern is adopted to access the hydraulic environment business management process and management elements in the business process model, the combination relationship is used to replace the inheritance relationship, the hydraulic environment geological business process system basic template of different application scenarios is established according to the hydraulic environment discipline knowledge and technical rules, the default configuration of the business process of different application scenarios is provided by object copying according to the principle of convention over configuration, the prototype design pattern, the database storage technology and the Java reflection mechanism, and the automatic flow of the corresponding hydraulic environment business process is driven according to the default configuration; the configuration parameters are modified before the business process is started and in the execution process, and the business process is adjusted according to the new configuration parameters;

[0032] In the business process execution process, the AOP technology and the interface technology are used to access the artificial intelligence auxiliary business inspection module based on the discipline knowledge and the technical rules according to the specific configuration of the business deployment unit to each management element, the binding mechanism and the preset business inspection interface, intelligent inspection of the business process configuration, the process execution process and the result data quality is realized;

[0033] The technical management module is set based on the method described in the business management module;

[0034] The algorithm model module: based on the hydraulic environment geological business knowledge, the discipline knowledge and the technical specification, the core algorithms of each functional module are screened, the basic process of various algorithms, the model index system describing the algorithm and the algorithm model template of the index parameter value are constructed, the business process steps, the model index and the model parameter value of various algorithm models are stored by using the structured database, and the classified algorithm model template database supporting the operation of the service management module, the business management module, the technical management module, the model management module and the data management module is established;

[0035] Based on the algorithm model template database, the model function body is constructed by using the modular design method, the responsibility chain design pattern, the Java reflection mechanism and the database code generation technology, the model parameter is automatically optimized and manually modified through machine learning;

[0036] The data management module: based on the hydraulic environment discipline knowledge, the technical rules, the business knowledge and the artificial intelligence technology, the hydraulic environment discipline knowledge, the technical rules, the business knowledge system and the knowledge graph are constructed, the hydraulic environment data structure model and the meta database are established, and the structured database storage is used to construct the hydraulic environment data center composed of the bottom data, the knowledge data, the model data, the business data and the system data;

[0037] The water conservancy and environment data is managed by using a mixed storage mode PostgreSQL+MySQL+Hadoop, the water conservancy and environment big data is stored and processed by using Hadoop and Spark, the data permission management and security audit functions are provided, the cache technology is used to store and quickly retrieve data, and a large language model, an artificial intelligence body and a knowledge graph are used to assist the data center data to be updated and mined.

[0038] The water conservancy and environment data is managed by using a mixed storage mode PostgreSQL+MySQL+Hadoop, the water conservancy and environment big data is stored and processed by using Hadoop and Spark, the data permission management and security audit functions are provided, the cache technology is used to store and quickly retrieve data, and a large language model, an artificial intelligence body and a knowledge graph are used to assist the data center data to be updated and mined. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 It is a functional module schematic diagram of a water conservancy and environment geological information system based on business full life cycle digitization.

[0040] Figure 2 It is a functional module schematic diagram of a water conservancy and environment geological information system based on business full life cycle digitization. DETAILED DESCRIPTION

[0041] The present application will be further clarified by the following description, but the scope of protection of the present application is not limited thereto.

[0042] A water conservancy and environment geological information system based on business full life cycle digitization comprises:

[0043] Infrastructure: The infrastructure provides basic support for the water conservancy and environment digitized geological information system, including data acquisition, network communication, data storage and processing servers, user terminal equipment, and the infrastructure is the basis for realizing the collection, transmission, storage, processing and sharing application of water conservancy and environment and business (project) management data, the basic information and state information of the infrastructure are used as system data, and the MySQL database is used for storage and timing update; the system understands the basic information and state information of the infrastructure by calling system data at regular intervals, so as to discover abnormal states of equipment in time and issue monitoring and early warning instructions.

[0044] Data center: The data center is divided into five types of management according to the data source, characteristics and use, namely, baseboard data, knowledge data, model data, business data and system data, adopts a mixed storage mode combining PostgreSQL+MySQL+Hadoop database, descriptive electronic files, multimedia files and graphic files, to adapt to the characteristics of multi-source, heterogeneous and large amount of water conservancy and environment data, meet the requirements of unified management and shared use of water conservancy and environment big data, the invention combines baseboard data, knowledge data, model data, business data, adopts multi-source data fusion, big data technology and artificial intelligence technology, simulates field experts, constructs water conservancy and environment knowledge graph and the correlation model of business and data, and assists in realizing intelligent design of business deployment, intelligent control of business execution, intelligent analysis of business inspection, intelligent prediction of data application, sets access permission control for various data, provides data query and retrieval and statistical analysis functions according to the access permission control.

[0045] Function hub: The function hub is the core of the water conservancy and environment intelligent geological information system, the invention divides the water conservancy and environment geological business into four fixed basic process units of business deployment (Plan), business execution (Do), business inspection (Check) and data management and application (Application), constructs a digital closed-loop management based on the PDCA cycle and covering the whole life cycle of water conservancy and environment geological business, establishes a water conservancy and environment big database composed of water conservancy and environment discipline knowledge, technical rules, business knowledge, algorithm model and historical data, realizes intelligent control of water conservancy and environment geological business process driven by big data based on big data and artificial intelligence technology, adopts modular design method, separates the management contents of service application, business process, technical method, algorithm model and data resource into five independent function modules of service management (SM), business management (BM), technical management (TM), model management (MM) and data management (DM), adopts abstract factory software design mode between modules, connects through interface with loose coupling, adopts micro-service development framework integration, supports rapid integration of new functions, and improves the flexibility and scalability of the system.

[0046] Application scenarios: the application takes the industry field-service type and the service type-technical method as the factory-product family pair, adopts the abstract factory software design pattern and interface technology to build a process model of a water conservancy and environmental geology information system based on the digitization of the whole life cycle of the service, enhances the flexibility and expansibility of the system, supports the application of multiple industry fields, multiple service types and multiple technical methods, and can be flexibly expanded according to the expansion of future industry fields, the extension of industry chains and the changes of technical methods. The applicable industry fields of the application include but are not limited to hydrogeology, geothermal mineral spring, geological engineering, geological disaster and ecological restoration. The applicable service types include but are not limited to investigation and evaluation, engineering exploration (survey), engineering consultation, engineering design, engineering construction, engineering supervision, dynamic monitoring and scientific research. The applicable technical methods include but are not limited to data collection, remote sensing interpretation, topographic survey, geological mapping (field mapping), geophysical prospecting, geochemical prospecting, mountain engineering, drilling, field test, sampling test, dynamic observation, digital simulation and special research.

[0047] User groups: the user groups of the application include water conservancy and environmental engineers for carrying out water conservancy and environmental data collection and engineering project construction work, water conservancy and environmental researchers for carrying out water conservancy and environmental three-dimensional modeling and digital twin construction work, project management personnel for carrying out project implementation whole life cycle management work, carrying out resource development, engineering construction, disaster prevention and control, ecological restoration industry management work, carrying out emergency remote command work, querying and searching water conservancy and environmental information and services, and the user groups can cover all roles in the water conservancy and environmental industry chain. The system has wide applicability.

[0048] Reference Figure 1 As shown in the figure, it is a functional module schematic diagram of a water conservancy and environmental geology information system based on the digitization of the whole life cycle of the service.

[0049] Further, the infrastructure includes data collection, network communication, data storage and processing servers, user terminal equipment, including:

[0050] Data acquisition equipment: including general water engineering field manual collection equipment and remote real-time automatic collection equipment, the data collected by the field manual collection equipment is checked by the field expert to control the data quality, the data is collected by the data entry system manual input and OCR technology and ASR technology intelligent collection, and is transmitted to the function hub (data management module) for processing; the data collected by the remote real-time automatic collection equipment is checked by the data checking algorithm conforming to the subject knowledge and technical rules to control the data quality, ensure the data integrity and accuracy, and is transmitted to the function hub (data management module) for processing through the protocol interface and the Internet of Things communication technology; the sensitive data is desensitized by encryption technology, transmitted safely by security transmission protocol and access permission control, to prevent leakage and illegal tampering, and to protect the safety of data transmission; the collected data is stored in the business database, and the remote real-time automatic collection equipment should have the function of local short-term data storage to prevent data loss caused by network anomalies.

[0051] Network communication equipment: including wide area Internet, local area Internet, Internet of Things, and routers, switches, firewall facilities, using distributed collaborative network architecture and load balancing to improve system reliability and performance; network security protection system is built by using security transmission protocol, encryption technology, setting firewall, deploying intrusion detection and defense system (IDS / IPS) and network monitoring and operation tools, to ensure network security.

[0052] Data storage and processing server: including self-built computer room and service provider's file server, database server, application server, storage server, supporting mass data storage by configuring large capacity hard disk and SSD, ensuring data reliability by RAID; ensuring business continuity by load balancing, cluster architecture, data redundancy and disaster recovery management, and ensuring high computing demand scenarios such as AI training and video rendering by using computing servers; two sets of equipment are configured in a 1:1 scale to ensure dual-link load balancing and fault switching functions.

[0053] User terminal equipment: including service console, user computer, display large screen, tablet computer and mobile phone, user terminal uses system function according to user permission control difference to ensure the open sharing and safety and stability of coefficient and data.

[0054] Further, the data center: according to the data source, characteristics and use, is divided into five types of bottom plate data, knowledge data, model data, business data and system data for management, including:

[0055] Knowledge data: the knowledge data of the application includes subject knowledge data, technical rule data, business knowledge data and data directory data.

[0056] The discipline knowledge data includes professional term data and knowledge structure data of the discipline field required for establishing the discipline system of water conservancy and environment science. The professional term data can include basic geography professional term data, basic geology professional term data, geophysical professional term data, geochemical professional term data, hydrogeological professional term data, geothermal mineral spring professional term data, geological engineering professional term data, geological disaster professional term data, and ecological restoration professional term data. The professional term data can be increased according to the expansion of the industrial field. The knowledge structure data can include basic geography knowledge structure data, basic geology knowledge structure data, geophysical knowledge structure data, geochemical professional knowledge structure data, hydrogeological knowledge structure data, geothermal mineral spring knowledge structure data, geological engineering knowledge structure data, geological disaster knowledge structure data, and ecological restoration knowledge structure data. The knowledge structure data can be increased according to the expansion of the industrial field.

[0057] The technical rule data includes water conservancy and environment geological business process and business process data and technical quality index data of technical methods used in the process of water conservancy and environment geological business process data, which can include investigation and evaluation business process data, engineering exploration business process data, engineering consultation business process data, engineering design business process data, engineering construction business process data, engineering supervision business process data, dynamic monitoring business process data, scientific research business process data, and business process data can be increased or adjusted according to the extension or adjustment of the industrial chain; the investigation and evaluation business process data can include hydrogeological investigation and evaluation business process data, geothermal mineral spring investigation and evaluation business process data, geological engineering investigation and evaluation business process data, geological disaster investigation and evaluation business process data, ecological restoration investigation and evaluation business process data, and the investigation and evaluation business process data can be increased according to the expansion and subdivision of the industrial field; the business process data of other water conservancy and environment business types are similar, and the water conservancy and environment business technical quality index data can include investigation and evaluation technical quality index data, engineering exploration technical quality index data, engineering consultation technical quality index data, engineering design technical quality index data, engineering construction technical quality index data, engineering supervision technical quality index data, dynamic monitoring technical quality index data, and scientific research technical quality index data, and the technical quality index data can be increased or adjusted according to the extension or adjustment of the industrial chain; the investigation and evaluation technical quality index data can include hydrogeological investigation and evaluation technical quality index data, geothermal mineral spring investigation and evaluation technical quality index data, geological engineering investigation and evaluation technical quality index data, geological disaster investigation and evaluation technical quality index data, and ecological restoration investigation and evaluation technical quality index data, and the investigation and evaluation technical quality index data can be increased according to the expansion and subdivision of the industrial field; the technical quality index data of other water conservancy and environment business types are similar, and the water conservancy and environment technical method business process data can include data collection business process data, remote sensing interpretation business process data, topographic survey business process data, geological mapping (field mapping) business process data, physical exploration business process data, chemical exploration business process data, mountain engineering business process data, geological drilling business process data, field test business process data, sampling test business process data, dynamic monitoring business process data, digital simulation business process data, and special research business process data, and the water conservancy and environment technical method business process data can be increased or adjusted according to the introduction and subdivision of new technical methods; the remote sensing interpretation business process data can include hydrogeological remote sensing interpretation business process data, geothermal mineral spring remote sensing interpretation business process data, geological engineering remote sensing interpretation business process data, geological disaster remote sensing interpretation business process data, and ecological restoration remote sensing interpretation business process data, and the remote sensing interpretation business process data can be increased according to the expansion and subdivision of the industrial field;Other water conservancy and environmental technology method business process data are similar, and water conservancy and environmental technology method technical quality index data can include data collection technical quality index data, remote sensing interpretation technical quality index data, topographic survey technical quality index data, geological mapping (field mapping) technical quality index data, physical exploration technical quality index data, chemical exploration technical quality index data, mountain engineering technical quality index data, geological drilling technical quality index data, field test technical quality index data, sampling test technical quality index data, dynamic monitoring technical quality index data, digital simulation technical quality index data, and special research technical quality index data, and the water conservancy and environmental technology method technical quality index data can be increased or adjusted according to the introduction and subdivision of new technology methods; the remote sensing interpretation technical quality index data can include hydrogeological remote sensing interpretation technical quality index data, geothermal spring remote sensing interpretation technical quality index data, geological engineering remote sensing interpretation technical quality index data, geological disaster remote sensing interpretation technical quality index data, and ecological restoration remote sensing interpretation technical quality index data, and the remote sensing interpretation technical quality index data can be increased according to the expansion and subdivision of the industry field; other water conservancy and environmental technology method technical quality index data are similar.

[0058] Business knowledge data can include business management process knowledge data and business management element knowledge data, the business management process knowledge data can include project planning knowledge data, project declaration knowledge data, project establishment and bidding knowledge data, project design knowledge data, project implementation knowledge data, achievement compilation knowledge data, achievement evaluation knowledge data, project acceptance knowledge data, project examination knowledge data, data management knowledge data, achievement application knowledge data, and after-sales service knowledge data, the business management process knowledge data can be adjusted according to the optimization of the business management process, and the business management element knowledge data can include work target knowledge data, work position knowledge data, work task knowledge data, work flow knowledge data, work time knowledge data, technical quality knowledge data, human resource knowledge data, work material knowledge data, work cost knowledge data, and work achievement knowledge data, and the business management element knowledge data can be adjusted according to the optimization of the business management element.

[0059] Data catalog data can include technical specification catalog data, professional book catalog data, technical manual catalog data, legal document catalog data, policy document catalog data, periodical literature catalog data, technical report catalog data, and network article catalog data; the data catalog can be adjusted according to the increase of the data source type.

[0060] The present application establishes a subject knowledge database reflecting the knowledge structure system of the subject of water conservancy and environment, a technical rule database reflecting the business process and technical method system of water conservancy and environment, a business knowledge database reflecting the business management knowledge system of water conservancy and environment, and a data catalog database indicating the data sources of the above three types of databases, to jointly build the water conservancy and environmental knowledge data.

[0061] First, through data collection, network search, collect water engineering and geological technical specifications, professional books, technical manuals, legal documents, policy documents, journal articles, technical reports, network articles, scan paper files, together with the collected electronic files of charts, texts, tables, convert to PDF file format in the data directory database as the original data saved, and register data information in the data directory, data directory can be saved in MySQL database.

[0062] Then, the collected data is combined with machine learning and artificial learning, according to the unified standardization and structured requirements, after data cleaning, data integration, data conversion, using PostgreSQL+MySQL+Hadoop database, descriptive electronic files, multimedia files, graphic files, divided into three types of subject knowledge data, technical rule data and business knowledge data sub-database for saving.

[0063] Finally, using subject knowledge data can provide instant text and graphic prompt function in business deployment, business execution, business inspection, data management and application operation, reduce misoperation; Provide data dictionary as a standardized option, realize data acquisition standardization; Using responsibility chain design pattern, according to the technical rule data and business knowledge data to assemble business process, realize the intelligent design of business deployment and intelligent flow of business execution; Based on AOP technology and interface technology, using technical rule data, realize the instant quality check of data, error warning and auxiliary acceptance function, improve work efficiency and quality.

[0064] Model data: model data can include comprehensive service model data, business process model data, technical method model data, data management model data, model management model data, map rendering model data, geological calculation model data, general algorithm model data, model data is created when designing model, respectively using MySQL database, descriptive electronic files, multimedia files, graphic files form storage function concept model design scheme structured model elements, text description, audio and video and spatial graphic data, model parameters can be updated when service configuration and optimization, business configuration, technical configuration modify (optimize) the model, model data for supporting service management, business management, technical management, data management, model management, map rendering, water conservancy and geological calculation and artificial intelligence algorithm implementation, for business management provides prototype template.

[0065] Business data: business data includes the data added and updated in the whole life cycle of business processes such as water conservancy and environmental geological business deployment, business execution, business inspection, data management and application, business data includes business basic information data, business management information data, business deployment data, business execution data, business inspection data, data management and application data, digital modeling data, prediction and evaluation data.

[0066] According to the characteristics of multi-source, heterogeneous and large amount of water conservancy and environmental geological business data, the PostgreSQL+MySQL+Hadoop database, descriptive electronic file, multimedia file and graphic file are comprehensively used for storage, and the business data structure of the corresponding business is created during business management (business deployment). The data formed in the overall execution process of various technical methods, various business types and projects are quality evaluated and marked according to the technical method reliability, instrument and equipment precision, technical personnel level, business process compliance, data integrity and data timeliness factors by using the water conservancy and environmental geological data quality credibility index (HEEDQI), and the HEEDQI calculation formula is as follows: , wherein represents the number of quality factors participating in the calculation of the water conservancy and environmental geological data quality credibility index of the data set, represents the th quality factor, including technical method reliability, instrument and equipment precision, technical personnel level, business process compliance, data integrity and data timeliness, represents the total number of samples of the th quality factor, that is, the total number of technical methods used, represents the th sample of the th quality factor, represents the weight of the th quality factor, the value is between 0 and 1, , represents the single-factor data quality credibility index of the th sample of the th quality factor, which is determined by machine learning and domain experts, the value is between 0 and 1, represents the artificial intervention correction coefficient, which is determined by the conversion value of the inspection and acceptance score of the domain expert, the value is between 0 and 1;

[0067] The average quality of the sample of each quality factor is calculated, each factor is assigned a weight according to business requirements, the weight reflects the importance of the overall quality, the contributions of each factor are integrated by the weighted sum formula, the comprehensive quality credibility index is formed, the weighted contributions of the comprehensive multi-dimensional quality factors are quantified, and the overall quality of the business data is quantified. Through expert empowerment method and machine learning dynamic optimization, adapt to business demand changes, introduce artificial correction coefficient on the basis of weighted sum , allow domain experts to adjust the results according to actual business experience, make up for the limitations of machine learning model.

[0068] The business data of HEEDQI index greater than a predetermined threshold (evaluated by machine learning and domain experts) is integrated into the corresponding theme database of the bottom plate data after data cleaning and data conversion (HEEDQI index is recorded and quality is marked), realizing data aggregation.

[0069] Bottom plate data: bottom plate data can include basic geographic data, geological structure data, geophysical data, geochemical data, hydrogeological data, geothermal mineral spring data, ecological environment data, geological engineering data, geological disaster data; bottom plate data can be increased according to the expansion of industry field.

[0070] The application collects basic geographic, geological structure, geophysical, geochemical basic data and hydrological and ecological geological field theme historical data, superimposes new data collected and observed in the field, gathers data according to the method in the business data, forms a hydrological and ecological data lake, constructs system bottom plate data, establishes a unified database structure and data dictionary according to the theme field concept model, specification and standardization, structured requirements, and comprehensively uses PostgreSQL+MySQL+Hadoop database, descriptive electronic file, multimedia file and graphic file form storage to adapt to the characteristics of multi-source, heterogeneous and large amount of theme data.

[0071] The bottom plate data mainly provides basic data for digital modeling, prediction evaluation, scheme design and scientific decision-making,

[0072] System data: system data includes permission management data, interface management data and system configuration data supporting system operation, the system establishes system database structure and system data (parameters) according to user permission, application field basic knowledge, technical rules and according to the principle of agreement greater than configuration, system data (parameters) are intelligently set and modified according to business technical rules and system running state and user configuration modification, system data adopts MySQL database and XML file form storage, and is mainly used for supporting and guiding system operation.

[0073] Further, it is divided into five function modules of service management, business management, technical management, model management and data management which are independent of each other, including:

[0074] The service management module is responsible for service registration, discovery, calling and monitoring of the system, and is vertically divided into five modules of industrial field, business type, technical method, algorithm model and data resource based on a modular design method, and is horizontally divided into hydrogeology, geothermal mineral spring, geological engineering, geological disaster and ecological restoration industrial field, the industrial field can be expanded according to actual needs; investigation and evaluation, engineering exploration (survey), engineering consultation, engineering design, engineering construction, engineering supervision, dynamic monitoring, scientific research business type, the business type can be expanded and adjusted according to the actual situation of the industrial chain; data collection, remote sensing interpretation, topographic survey, geological mapping (field mapping), physical exploration, chemical exploration, mountain engineering, geological drilling, field test, sampling test, dynamic monitoring, digital simulation, special research technical method, the technical method can be expanded according to the actual situation of new technology and new method; comprehensive service, business process, technical method, data management, model management, map rendering, geological calculation, general algorithm algorithm model, bottom plate data, knowledge data, model data, model data, business data, system data, the application can be expanded according to the specific requirement application scene and actual situation based on various industrial fields, various business types, various technical methods and various algorithm models Design single function micro service function body, use the micro service development framework (including Spring Cloud), adopt micro service discovery and management tools (including Nacos), integrate containerized deployment and service orchestration tools (including Kubernetes), realize the automatic management and expansion of micro service; provide unified API gateway (including SpringCloud Gateway), integrate user authentication authorization protocol (including OAuth2.0) and network security protocol (including SSL / TLS) to manage the calling and permission control of micro service, adopt RESTful API and message queue to realize the communication between services, ensure the efficient communication between micro services, the service management module adopts the adapter mode, that is, by increasing the pretreatment before calling and the post-processing after calling, integrates internal and external functional components (including QGIS API), provides permission management, interface management, business management, model management, map rendering, log audit, system monitoring, system configuration, help system basic service and service construction, service registration, service configuration, service retrieval, service calling, service stop, service optimization, service deletion, service statistics micro service management function, coordinates the efficient, safe and stable operation of the whole system, constructs the water conservancy and environmental geological information system based on the micro service architecture, and enhances the flexibility and expandability of the system.

[0075] The business management module is responsible for management of the whole life cycle of the water conservancy and environment geological business, supports the whole life cycle of the water conservancy and environment geological business, adopts a modular design method, various software design modes and interface technologies, and provides intelligent control of various application scenarios (industrial fields), various business type business process management processes and management elements.

[0076] Firstly, the water conservancy and environment business PDCA process model is constructed based on the builder software design mode, the water conservancy and environment technical method life cycle is divided into four fixed PDCA basic process units (PdcaBase), i.e., deployment business deployment (Plan), business execution (Do), business inspection (Check) and data management and application (Application), which are respectively responsible for configuration, implementation, inspection and data management and application of the water conservancy and environment business process, the builder software design mode is adopted, the business deployment, business execution, business inspection and data management and application are taken as fixed unit modules of the business process abstract builder interface, the four basic process units are solidified, the business process abstract builder interface (AbstractBusiness, inherits the PDCA basic process unit interface PdcaBase) is taken as a top interface of various business processes, and the business deployment, business execution, business inspection and data management and application public interfaces are provided, the builders of various business processes are independent of each other, and independently provide respective implementation details, the flexibility and expansibility of the business process are enhanced, the business achievement data can be applied to optimization and business redeployment of the present business deployment model, the business deployment-business execution-business inspection-data management and application are started again, and a business process PDCA loop is constructed; the basic process unit division of the business process covers the whole life cycle of the water conservancy and environment geological business, the water conservancy and environment business process constructed based on the basic process unit can realize closed loop management of the water conservancy and environment business process.

[0077] Then, based on the abstract factory design pattern, the structure model of the hydraulic environment business process is constructed. The hydraulic environment business can be divided into investigation and evaluation, engineering exploration, engineering consultation, engineering design, engineering construction, engineering supervision, dynamic monitoring, and scientific research. The work flow, work content, and technical method of the hydraulic environment business are not completely the same in different application scenarios (industrial fields). The abstract factory design pattern is adopted. The industrial field and the specific industrial field (including hydrogeology) are taken as the abstract factory interface (AbstractField) and the concrete factory class (ConcreteField1- ConcreteFieldn), respectively. Various types of hydraulic environment business (including engineering exploration) are taken as the hydraulic environment business product. The above business process abstract builder interface (AbstractBusiness) is inherited to construct different hydraulic environment business abstract product interfaces (AbstractBusiness1-AbstractBusinessm). Each industrial field (factory) can have (i.e., produce) multiple hydraulic environment businesses (products). That is, through different specific implementations (ConcreteBusiness11- ConcreteBusinessmn) of various types of hydraulic environment business interfaces (AbstractBusiness1-AbstractBusinessm), the specific hydraulic environment business (product, including geothermal exploration) implementation corresponding to different industrial fields can be provided (produced). The abstract factory design pattern is adopted. When a new type of business (product family) is added, the original code does not need to be modified. The software development open-closed principle is met. Only the industrial field (factory) class needs to be modified to enhance the extensibility of the hydraulic environment business type.

[0078] Finally, the bridge design pattern is adopted to access the hydraulic engineering and environment business management processes (project planning, project declaration, project design, project implementation, achievement compilation, achievement review, project acceptance, project assessment, data management, achievement application and after-sales service) and management elements (work target, work location, work task, work process, work time, technical quality index, human resource, work material, work cost, work achievement) in the business process model. The combination relationship is used to replace the inheritance relationship, separate the abstract part from the concrete implementation part, reduce the coupling degree of the two variable dimensions of abstraction and implementation, enhance flexibility and expansion capability. At the same time, according to the knowledge and technical rules of hydraulic engineering and environment discipline, the basic templates of hydraulic engineering and environment geological business process system for different application scenarios are established. According to the principle of agreement over configuration, the prototype design pattern, database (including XML) storage technology and Java reflection mechanism are adopted to provide default configuration of business process for different application scenarios through object copying, and drive the automatic flow of corresponding hydraulic engineering business process according to the default configuration, supporting the automatic flow of hydraulic engineering business in different application scenarios. The AOP technology and interface technology are used to modify the configuration parameters before and during the execution of the business process according to the specific application scenario and special circumstances, and adjust the business process according to the new configuration parameters, improving the flexibility and expansibility of the system. During the execution of the business process, according to the specific configuration of each management element by the business deployment unit, through the binding mechanism and the preset business check interface, the association of user operation and business process model, business process model data is realized. Based on the knowledge of hydraulic engineering and environment discipline, technical rules, artificial intelligence technology and AOP technology, the process guidance and operation prompt, pre-selection and pre-filling, standardized selection, data verification and intelligent error warning control function are dynamically provided, improving the intelligent degree of the system, reducing the tedious business configuration and deployment work and user misoperation, improving the work efficiency, data integrity and quality of hydraulic engineering and environment business. During the execution of the business process and at the end of the execution, the AOP technology and interface technology can be used to access the artificial intelligence auxiliary business check module based on the knowledge and technical rules of the discipline, to realize the intelligent check of the business process configuration, the process execution process and the achievement data quality, greatly improving the intelligent degree and resource utilization, the work efficiency of technical personnel and review experts.

[0079] Technology management module: The technology management module is responsible for the management of the technology methods of the whole life cycle of hydraulic engineering and environment geological business, and supports the process flow of the technology methods of the whole life cycle of hydraulic engineering and environment geological business. Modular design method, multiple software design patterns and interface technology are used to provide intelligent control of various application scenarios (various business types in various industries), various technical method process management processes and management elements.

[0080] Firstly, based on the builder design pattern, a hydraulic environment technology PDCA process model is constructed, and the hydraulic environment technology method life cycle is also divided into four fixed basic process units of business deployment (Plan), business execution (Do), business inspection (Check), and data management and application (Application), which are responsible for the configuration, implementation, inspection, and data management and application of the hydraulic environment technology method respectively. The application adopts the builder software design pattern, takes the business deployment, business execution, business inspection, and data management and application as the fixed unit modules of the abstract method builder interface, solidifies the four basic process units, takes the abstract method builder interface (AbstractMethod, inherits the PDCA basic process unit interface PdcaBase) as the top-level interface of various technical methods, provides the business deployment, business execution, business inspection, and data management and application public interfaces, and enhances the flexibility and expansibility of the technical method. The business result data can be applied to the optimization and business redeployment of the business deployment model, and the business deployment-business execution-business inspection-data management and application are started again to construct the business process PDCA loop. The basic process unit division of the technical method covers the whole life cycle of the hydraulic environment geological technology method, and the technical method business process constructed based on the basic process unit can realize the closed-loop management of the hydraulic environment technology method business process.

[0081] Then, based on the abstract factory design pattern, a hydraulic environment technology method process structure model is constructed. The hydraulic environment geological technology method can be divided into data collection, remote sensing interpretation, topographic survey, geological mapping (field mapping), geophysical prospecting, geochemical prospecting, mountain engineering, drilling, field test, sampling test, dynamic observation, digital simulation, and thematic research types. The business process, work content, and technical requirements of the technical method for different application scenarios (industrial fields and business types) are not completely the same, and the abstract factory design pattern is adopted,

[0082] The different business types (including engineering survey) and specific industry field business types (including hydrogeological engineering survey) are used as abstract factory interfaces (AbstractBusiness1-AbstractBusinessm) and concrete factory classes (ConcreteBusiness11- ConcreteBusinessmn), and various types of technical methods (including geophysical prospecting) are used as technical method products. The above technical method abstract builder interface (AbstractMethod) is inherited to construct different types of technical method abstract product interfaces (AbstractMethod1-AbstractMethodx). Each industry field and each business type (factory) can have (i.e., produce) multiple technical methods (products). That is, different specific implementations (ConcreteMethod111- ConcreteMethodxmn) of various types of technical method interfaces (AbstractMethod1-AbstractMethodx) can be used to provide (produce) specific technical method (products, including hydrogeological survey and evaluation geophysical prospecting) implementations corresponding to different industry fields (including hydrogeology) and different business types (survey and evaluation). The abstract factory software design pattern is adopted. When a new type of technical method (product family) is added, the original code does not need to be modified. The software development open-closed principle is met. Only the business type (factory) class needs to be modified to enhance the extensibility of the technical method.

[0083] Finally, the bridging design pattern is adopted to access technical method management elements (work objectives, work positions, work tasks, work processes, work time, technical quality indicators, human resources, work materials, work costs, and work results) in the technical process model. The combination relationship is used to replace the inheritance relationship, separate the abstract part from the concrete implementation part, reduce the coupling degree of the two variable dimensions of abstraction and implementation, and enhance flexibility and expansion capability. At the same time, according to the knowledge and technical rules of the hydrographic and environmental geology discipline, the basic templates of the hydrographic and environmental geology business technical method system for different application scenarios are established. According to the principle of convention over configuration, the prototype design pattern, database (including XML) storage technology, and Java reflection mechanism are used to provide default configurations of technical methods for different application scenarios through object copying and drive the automatic flow of corresponding technical methods according to the default configurations. The AOP technology and interface technology are used to realize the modification of configuration parameters before the start and during the execution of the technical method process according to the specific application scenario and special circumstances, and adjust the technical method process according to the new configuration parameters, thereby improving the flexibility and expansibility of the system. During the execution of the technical method, the user operation is associated with the technical method model and technical method model data through the binding mechanism and the preset business inspection interface according to the specific configuration of each management element by the business deployment unit. Based on the knowledge of the hydrographic and environmental geology discipline, technical rules, artificial intelligence technology, and AOP technology, the process guide and operation prompt, pre-selection and pre-filling, standardized selection, data verification, and error warning intelligent control functions are dynamically provided to improve the intelligent degree of the system, reduce the tedious business configuration and deployment work and user misoperation, and improve the work efficiency, data integrity, and quality of the hydrographic and environmental business. During the execution of the technical method process and at the end of the execution, the AOP technology and interface technology can be used to access the artificial intelligence auxiliary business inspection module based on the knowledge of the discipline and technical rules to realize the intelligent inspection of the technical method process configuration, process execution process, and result data quality, thereby greatly improving the intelligent degree and resource utilization, and the work efficiency of technical personnel and review experts.

[0084] Algorithm model module: The algorithm model module is responsible for the management and optimization of the algorithm model of the hydrographic and environmental geology business throughout the life cycle. The modular design method, prototype software design pattern, and interface technology are used to provide support for the intelligent control of each functional module.

[0085] First, based on the knowledge of hydraulic and environmental geology business, discipline knowledge and technical specifications, the core algorithms of each functional module are screened, including the permission management algorithm of microservice management, the business calculation algorithm of hydraulic and environmental geology business management, the profile drawing algorithm of technical method management, the model construction algorithm of model management, and the professional term description algorithm of data management. The basic flow of various algorithms, the model index system of algorithm description, and the algorithm model template of index parameter value are constructed. The structured database (including MySQL) is used to store the business process steps, model indexes and model parameter values of various algorithm models. The classified algorithm model template database supporting the operation of service management, business management, technical management, model management and data management modules is established.

[0086] Then, based on the algorithm model template database, the modular design method, the responsibility chain design pattern, the Java reflection mechanism and the database code generation technology are used to construct the model function body. Under the support of artificial intelligence technology, through machine learning, automatic optimization and manual modification of model parameters, the evolution of the model is realized by using the prototype design pattern. The resource reuse rate is improved. The map rendering in the map compilation process and the geological calculation and general algorithm in the hydraulic and environmental business implementation process are solidified and implemented. The corresponding algorithm model library is established.

[0087] Finally, the calling interface of the model is provided to support the intelligent processing of the functional modules and realize the use of the model.

[0088] Data management module: The data management module is responsible for the unified management of data, supports the data-driven intelligent control of the hydraulic and environmental business process, and constructs the hydraulic and environmental discipline knowledge, technical rules, business knowledge system and knowledge graph based on the discipline knowledge, technical rules, business knowledge and artificial intelligence technology of hydraulic and environmental engineering. The hydraulic and environmental data structure model and meta database are established and stored in the structured database (including MySQL). The hydraulic and environmental data center is classified and constructed by bottom data, knowledge data, model data, business data and system data. The hybrid storage mode (PostgreSQL+MySQL+Hadoop) is used to manage multi-source, multi-type, large-volume, multi-dimensional, multi-temporal and heterogeneous hydraulic and environmental data. Hadoop and Spark are used to realize the storage and processing of hydraulic and environmental big data. The data permission management and security audit functions are provided. The cache technology is used to store and quickly retrieve data to reduce the number of requests to the database server, thereby improving the response speed and reducing the network load. By accessing large language models (including DeepSeek), artificial intelligence agents (including Manus), and knowledge graphs (including Neo4j), the data center data update and mining are assisted to improve the data update efficiency and utilization rate.

[0089] Reference Figure 2As shown, it is a water conservancy and environmental geology information system architecture diagram based on business full life cycle digitalization.

[0090] The application provides a water conservancy and environmental geology information system based on business full life cycle digitalization, the system architecture includes five parts of infrastructure, data center, function hub, application scene and user group, water conservancy and environmental geology business is divided into four fixed basic process units of business deployment, business execution, business inspection, data management and application, a digital closed-loop management based on PDCA cycle and covering the whole life cycle of water conservancy and environmental geology business is constructed; a water conservancy and environmental geology big data center composed of water conservancy and environmental geology discipline knowledge, technical rules, business knowledge, algorithm model and business data is established, intelligent control of water conservancy and environmental geology business process is realized based on big data technology and artificial intelligence technology; based on the software engineering principle, a modular design method, various software design modes, micro-service architecture and interface technology are adopted, and the system is divided into five function modules of service management, business management, technical management, model management and data management.

Claims

1. A hydraulic engineering and environmental geological information system based on business full life cycle digitalization, characterized in that, Comprise: Infrastructure: including data acquisition, network communication, data storage and processing server, user terminal equipment, basic information and state information of infrastructure as system data, using MySQL database storage and timing update, based on the basic information and state information of infrastructure, the system monitors the abnormal state of equipment and issues monitoring and early warning instructions; Data center: according to the data source, characteristics and use, divided into five types of management of bottom plate data, knowledge data, model data, business data and system data, based on the characteristics of multi-source, heterogeneous and large amount of water conservancy and environmental data, using PostgreSQL+MySQL+Hadoop database, descriptive electronic file, multimedia file, graphic file, a variety of forms combined with hybrid storage mode, combined with bottom plate data, knowledge data, model data, business data, using multi-source data fusion, big data technology, artificial intelligence technology, simulate field experts, build water conservancy and environmental knowledge graph and business and data association model, auxiliary business deployment intelligent design, business execution intelligent control, business inspection intelligent analysis, data application intelligent prediction, set access control for all kinds of data, according to access control, provide data query, statistical analysis function; The data center: according to the data source, characteristics and use, divided into five types of management of bottom plate data, knowledge data, model data, business data and system data, including: Knowledge data: including discipline knowledge data, technical rule data, business knowledge data and data directory data, data directory data is converted into PDF file format and saved in data directory database as original data, and the data information is registered in data directory, using machine learning and artificial learning combination, according to the unified standardization and structured requirements, after data cleaning, data integration, data conversion, using PostgreSQL+MySQL+Hadoop database, descriptive electronic file, multimedia file, graphic file, divided into discipline knowledge data, technical rule data and business knowledge data three types of sub database for saving, based on discipline knowledge data, provide instant text and graphic prompt function, provide data dictionary as standardization option, using responsibility chain design mode, according to technical rule data and business knowledge data to assemble business process, based on AOP technology and interface technology, carry out instant quality check, error warning and auxiliary acceptance of data; Model data: create when designing model, respectively using MySQL database, descriptive electronic file, multimedia file, graphic file form to store functional concept model design scheme structured model element, text description, audio and video and spatial graphic data, model parameters are updated when service configuration and optimization, business configuration, technical configuration modify and optimize the model, provide prototype template for business management; Business data: stored in the form of PostgreSQL+MySQL+Hadoop database, descriptive electronic files, multimedia files, graphic files, when business management, create the business data structure of the corresponding business, based on technical method reliability, instrument accuracy, technical personnel level, business process compliance, data integrity, data timeliness factor, use hydraulic and environmental data quality credibility index HEEDQI for quality evaluation and quality labeling, HEEDQI calculation formula is as follows: Wherein represents the number of quality factors participating in the calculation of the hydraulic and environmental data quality credibility index, represents the th quality factor, including technical method reliability, instrument accuracy, technical personnel level, business process compliance, data integrity, data timeliness, represents the th quality factor, including technical method reliability, instrument accuracy, technical personnel level, business process compliance, data integrity, data timeliness, represents the th sample of the th quality factor, represents the weight of the th quality factor, the value is between 0 and 1, , represents the single factor data quality credibility index of the th sample of the th quality factor, determined by machine learning and domain experts, the value is between 0 and 1, represents the artificial intervention correction coefficient, determined by domain experts, the value is between 0 and 1, for business data with HEEDQI index greater than the predetermined threshold, after data cleaning and data conversion, integrate into the corresponding theme database of the bottom plate data, record HEEDQI index and quality label at the same time; The bottom plate data: superimposed update field to collect new data, according to the method in the business data, gather data, form the data lake of water conservancy and environment, build the system bottom plate data, the bottom plate data according to the theme field conceptual model, specification and standardization, structured requirements, establish a unified database structure and data dictionary, and after data cleaning, data integration, data conversion processing; System data: in the work deployment at the same time according to user permission, application field basic knowledge, technical rules, according to the principle of agreement is greater than configuration, establish system database structure and system data, system data according to the business technical rules and system running state intelligent setting and modification and user configuration modification, using MySQL database, XML file form storage; Function center: the water conservancy and environment geology business is divided into business deployment, business execution, business inspection, data management and application four fixed basic process units, build based on PDCA ring, cover the whole life cycle of water conservancy and environment geology business digital closed loop management, establish by water conservancy and environment discipline knowledge, technical rules, business knowledge, algorithm model and historical data of water conservancy and environment big database, based on big data and artificial intelligence technology, carry out big data driven water conservancy and environment geological business process intelligent control, using modular design method, separate the management content of service application, business process, technical method, algorithm model and data resource into five function modules of service management, business management, technology management, model management and data management, the modules adopt abstract factory software design pattern, through interface loose coupling connection, using micro service development framework integration; Application scenario: take industry field-business type and business type-technical method as factory-product family, adopt abstract factory software design pattern and interface technology to build a kind of process model of water conservancy and environment geological information system based on business whole life cycle digitalization, based on the expansion of future industry field, extension of industry chain and change of technical method, expand the applicable industry field, business type and technical method; User group: including water conservancy and environment engineers to carry out water conservancy and environment data collection and engineering project construction work, water conservancy and environment researchers to carry out water conservancy and environment three-dimensional modeling and digital twin construction work, project management personnel to carry out project implementation whole life cycle management work, carry out resource development, engineering construction, disaster prevention and control, ecological restoration industry management work, carry out remote command work of emergency, query retrieval water conservancy and environment information and service, cover all roles in water conservancy and environment industry chain.

2. The hydraulic and environmental geological information system based on the digitization of the entire life cycle of a service according to claim 1, characterized in that, The infrastructure includes data collection, network communication, data storage and processing server, user terminal equipment, including: Data acquisition equipment: including general water conservancy field manual collection equipment and remote real-time automatic collection equipment, the data collected by the field manual collection equipment is checked by the field experts to control the data quality, the data is collected by the data entry system, the OCR technology and the ASR technology, and is transmitted to the function hub processing, the data collected by the remote real-time automatic collection equipment is checked by the data verification algorithm conforming to the subject knowledge and technical rules, and is transmitted to the function hub processing through the protocol interface and the Internet of Things communication technology, the sensitive data is desensitized by the encryption technology, the secure transmission protocol and the access permission control, the collected data is stored in the business database, and the remote real-time automatic collection equipment has the data local short-term storage function; Network communication equipment: including wide area Internet, local area Internet, Internet of Things, routers, switches and firewall facilities, adopting distributed collaborative network architecture and load balancing, using secure transmission protocol, encryption technology, setting up firewall, deploying intrusion detection and defense system and network monitoring and operation tool measures to build network security protection system; Data storage and processing server: including self-built computer room and service provider's file server, database server and application server, the storage server supports mass data storage by configuring large capacity hard disk and SSD, adopts RAID, load balancing, cluster architecture, data redundancy and disaster recovery management, and the application server is configured with two sets of equipment through 1:1 scale by using computing server; User terminal equipment: including service console, user computer, display screen, tablet computer and mobile phone, the user terminal uses the system function according to the user permission control difference through the protocol interface.

3. The hydraulic and environmental geological information system based on the digitization of the entire life cycle of a service according to claim 1, characterized in that, It is divided into five function modules of service management, business management, technology management, model management and data management, including: Service management module: responsible for service registration, discovery, calling and monitoring of the system, based on modular design method, divided into five modules of industry field, business type, technical method, algorithm model and data resource vertically, using micro-service development framework, using micro-service discovery and management tool, integrating containerized deployment and service orchestration tool, carrying out automatic management and expansion of micro-service, providing unified API gateway, integrating user authentication authorization protocol and network security protocol to manage the calling and permission control of micro-service, using RESTful API and message queue to realize the communication between services, and the service management module uses adapter mode to provide micro-service management function; Business management module: using modular design method, multiple software design patterns and interface technology, providing intelligent control of various application scenarios and industry fields, various business type business process management processes and management elements; The PDCA process model of water conservancy and environment business is built based on the builder software design pattern, and the life cycle of water conservancy and environment technology method is divided into four fixed PDCA basic process units of business deployment Plan, business execution Do, business inspection Check and data management and application Application. The business process abstract builder interface is used as the top interface of various business processes, and the public interfaces of business deployment, business execution, business inspection and data management and application are provided; Based on the abstract factory design pattern, the business process structure model of water conservancy and environment is built, the industry field and specific industry field are used as the abstract factory interface and specific factory class respectively, and various types of water conservancy and environment business are used as the product of water conservancy and environment business. The abstract product interface of different water conservancy and environment business is built by inheriting the above business process abstract builder interface, and the specific implementation of water conservancy and environment business corresponding to different industry fields is provided; The bridge design pattern is used to connect the water conservancy and environment business management process and management elements in the business process model, and the combination relationship is used to replace the inheritance relationship. According to the knowledge and technical rules of water conservancy and environment discipline, the basic template of water conservancy and environment geological business process system in different application scenarios is established. According to the principle of convention over configuration, the prototype design pattern, database storage technology and Java reflection mechanism are used to provide the default configuration of business process in different application scenarios through object copying, and the automatic flow of corresponding water conservancy and environment business process is driven according to the default configuration. Before the start of the business process and in the execution process, the configuration parameters are modified, and the business process is adjusted according to the new configuration parameters; In the execution process of business process, according to the specific configuration of each management element by business deployment unit, binding mechanism and preset business inspection interface, AOP technology and interface technology are used to connect the artificial intelligence auxiliary business inspection module based on the knowledge and technical rules of discipline, and the intelligent inspection of business process configuration, process execution process and result data quality is realized; The technical management module is set according to the method described in the business management module; The algorithm model module: based on the knowledge, discipline knowledge and technical specifications of water conservancy and environment geology, the core algorithms of each function module are screened, the basic process of various algorithms, the model index system of algorithm and the algorithm model template of index parameter value are built, the structured database is used to store the business process steps, model indexes and model parameter values of various algorithm models, and the classified algorithm model template database supporting the operation of service management, business management, technical management, model management and data management modules is established; Based on the algorithm model template database, the modular design method, responsibility chain design pattern, Java reflection mechanism and database code generation technology are used to build the model function body, and the model parameters are automatically optimized and manually modified through machine learning. The data management module is based on the knowledge of the discipline of hydraulic engineering and environment, technical rules, business knowledge and artificial intelligence technology to construct the knowledge of the discipline of hydraulic engineering and environment, technical rules, business knowledge system and knowledge graph, establish a hydraulic engineering and environment data structure model and a meta database, and store the data by using a structured database, and classify and construct a hydraulic engineering and environment data center composed of bottom data, knowledge data, model data, business data and system data. The mixed storage mode PostgreSQL+MySQL+Hadoop is adopted to manage the data of the hydraulic engineering and environment, Hadoop and Spark are adopted to store and process the big data of the hydraulic engineering and environment, the permission management and security audit functions of the data are provided, the cache technology is adopted to store and quickly retrieve the data, and the big language model, artificial intelligence agent and knowledge graph are connected to assist the data center in updating and mining the data.

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