Data aggregation system and method based on the construction industry

Abstract

This application provides a data aggregation system and method for the construction industry, comprising: a primary reverse proxy server responding to user service requests and sending the service requests to a secondary application gateway according to a preset load balancing strategy; the secondary application gateway authenticating the service requests and, when the service request is a building drawing request, routing the building drawing request to an AI service module; the AI ​​service module, upon receiving the building drawing request, calling AI creation software to generate an image and sending task completion information to a message queue after image generation; and a data aggregation service module, upon detecting task completion information in the message queue, calling ERP management software to update the work progress and / or design output value of the target project in the ERP management software based on the workload completed by the AI ​​creation software. This application can improve enterprise management efficiency and handle high-concurrency data requests.

Description

Technical Field

[0001] This application relates to the field of data processing in the construction industry, and in particular to a data aggregation system and method based on the construction industry. Background Technology

[0002] With the development of Building Information Modeling (BIM) and Artificial Intelligence (AI) technologies, the architectural design and management industry is undergoing a digital transformation. However, despite the progress made by existing technologies in their respective vertical fields (materials, drafting, interaction, and operation and maintenance), current digital platforms in the construction industry generally suffer from the following limitations: 1. Severe system silos: AI design tools, enterprise financial systems (business-finance integration), and knowledge base management systems are often fragmented, and data cannot be automatically aggregated and transferred.

[0003] 2. Poor architectural scalability: Most existing platforms adopt a monolithic architecture, which is difficult to cope with high-concurrency AI inference requests and data throughput of massive building files, and lacks a unified service governance and circuit breaker mechanism.

[0004] Therefore, a new data aggregation system based on the construction industry is urgently needed to solve the above problems. Summary of the Invention

[0005] In view of this, this application provides a data aggregation system and method based on the construction industry, which can improve enterprise management efficiency and handle high-concurrency data requests.

[0006] A first aspect of this application provides a data aggregation system based on the construction industry. The architecture of the data aggregation system includes: an access gateway layer, including a primary reverse proxy server and a secondary application gateway; a microservice application layer, including an AI service module and a data aggregation service module; a middleware and data layer, including a message queue; and a downstream system integration layer, including ERP management software and AI creation software. The primary reverse proxy server responds to user service requests and sends the service requests to the secondary application gateway according to a preset load balancing strategy. The secondary application gateway authenticates the service requests and, if the service request is an architectural drawing request, routes the architectural drawing request to the AI ​​service module. Upon receiving the architectural drawing request, the AI ​​service module calls the AI ​​creation software to generate an image and sends task completion information to the message queue after image generation. The data aggregation service module, upon detecting the task completion information in the message queue, calls the ERP management software to update the work progress and / or design output value of the target project in the ERP management software based on the workload completed by the AI ​​creation software.

[0007] In one possible implementation, when the authentication result of the secondary application gateway is that the service request is a project financial statement viewing request, the project financial statement viewing request is routed to the data aggregation service module; after receiving the project financial statement viewing request, the data aggregation service module calls the ERP management software to display the target project financial statement that matches the project financial statement viewing request.

[0008] In one possible implementation, the microservice application layer further includes a registration and configuration center module; the secondary application gateway authenticates the service request, and when the service request is an architectural drawing request, routes the architectural drawing request to the AI ​​service module, including: the secondary application gateway obtaining a service list from the registration and configuration center module, wherein the service list includes the IP address, port number, health status bit, and custom metadata of different AI service modules; the secondary application gateway determining the target AI service module among different AI service modules based on the service list; and when the authentication result indicates that the service request is the architectural drawing request, routing the architectural drawing request to the target AI service module.

[0009] In one possible implementation, the data aggregation system further includes an infrastructure layer; the infrastructure layer includes an automation server for implementing continuous integration and continuous delivery, and a container management tool; the automation server is used to automatically build the AI ​​service module and the data aggregation service module based on the code input by the developers; the container management tool is used to visually manage the running status of the AI ​​service module and the data aggregation service module.

[0010] In one possible implementation, the infrastructure layer further includes a distributed task scheduling platform; the distributed task scheduling platform is used to respond to data scheduling requests and retrieve data reports that match the data scheduling requests from the ERP management software.

[0011] In one possible implementation, the primary reverse proxy server is Nginx, and the secondary application gateway is Spring Cloud Gateway.

[0012] Secondly, this application also provides a data aggregation method based on the construction industry, applied to the data aggregation system based on the construction industry described in the first aspect; the data aggregation method includes: responding to user service requests through the first-level reverse proxy server, and sending the service requests to the second-level application gateway according to a preset load balancing strategy; authenticating the service requests through the second-level application gateway, and routing the architectural drawing requests to the AI ​​service module when the service requests are architectural drawing requests; receiving the architectural drawing requests through the AI ​​service module, and calling the AI ​​creation software to generate images after receiving the architectural drawing requests, and sending task completion information to the message queue after image generation; listening to the message queue through the data aggregation service module, and calling the ERP management software after listening to the task completion information in the message queue, and updating the work progress and / or design output value of the target project in the ERP management software according to the workload completed by the AI ​​creation software.

[0013] In one possible implementation, if the authentication result of the secondary application gateway indicates that the service request is a project financial statement viewing request, the method further includes: routing the project financial statement viewing request to the data aggregation service module through the secondary application gateway; receiving the project financial statement viewing request through the data aggregation service module, and, upon receiving the project financial statement viewing request, invoking the ERP management software to display the project financial statement matching the project financial statement viewing request.

[0014] In one possible implementation, authenticating the service request through the secondary application gateway and routing the architectural drawing request to the AI ​​service module when the service request is an architectural drawing request includes: obtaining a service list from the registration and configuration center module through the secondary application gateway, wherein the service list includes the IP address, port number, health status bit, and custom metadata of different AI service modules; determining the target AI service module among the different AI service modules through the secondary application gateway based on the service list; and routing the architectural drawing request to the target AI service module when the authentication result indicates that the service request is the architectural drawing request.

[0015] In one possible implementation, after updating the work progress and / or design output value of the target project in the ERP management software based on the workload completed by the AI ​​creation software, the method further includes: sending an update notification of the target project to the manager of the target project.

[0016] Compared with related technologies, the embodiments of this application have at least the following advantages: By setting up a first-level reverse proxy server and a second-level application gateway at the access gateway layer, the first-level reverse proxy server can send user service requests to the second-level application gateway according to a preset load distribution strategy. Furthermore, since the AI ​​service module sends task completion information to a message queue after image generation, and the data aggregation service module listens for task completion information in the message queue and calls the ERP management software, on the one hand, through the asynchronous message processing of RocketMQ and the load balancing of the first-level reverse proxy server, the data aggregation system can withstand a large number of users simultaneously initiating AI drawing requests without crashing, ensuring that the data aggregation system can handle high-concurrency data requests. On the other hand, since the data structure of the front-end architectural drawing requests and the back-end ERP management software are completely different, and their processing speeds are not on the same order of magnitude (drawing may take 1 minute, while accounting only takes 10 milliseconds), the asynchronous communication of the message queue achieves asynchronous decoupling between the architectural drawing requests and the ERP management software, improving the reliability of the data aggregation system. In addition, the data aggregation system can automate the entire process from architectural drawing design to target project progress and financial settlement, greatly improving enterprise management efficiency.

[0017] The technical effects achieved by the second aspect are similar to those achieved by the corresponding technical means in the first aspect, and will not be repeated here. Attached Figure Description

[0018] Figure 1 A schematic diagram of the functional modules of a data aggregation system based on the construction industry provided in an embodiment of this application; Figure 2 A schematic diagram of the overall architecture of a data aggregation system based on the construction industry provided in an embodiment of this application; Figure 3 A flowchart illustrating the steps of a data aggregation method based on the construction industry provided in an embodiment of this application. Detailed Implementation

[0019] To better understand the above-mentioned objectives, features, and advantages of this application, the application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0020] The following description sets forth many specific details to provide a full understanding of this application. The described embodiments are only some, not all, of the embodiments of this application.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application.

[0022] It should be further noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0023] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and drawings of this application are used to distinguish similar objects, not to describe a specific order or sequence.

[0024] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0025] For ease of understanding, some concepts related to the embodiments of this application are illustrated and explained by way of example for reference.

[0026] Nginx is a high-performance HTTP and reverse proxy server, which can also be used as a mail proxy server, TCP / UDP load balancer, and content caching service. It is known for its low resource consumption, high concurrency handling capabilities, and stability, and is widely used in various websites and modern application architectures worldwide.

[0027] Spring Cloud Gateway is a mainstream API gateway solution in current microservice architectures. Developed by Spring based on Spring 5, Spring Boot 2, and Project Reactor technology stacks, it aims to replace Netflix Zuul, providing more efficient and flexible routing and filtering capabilities. It adopts an asynchronous non-blocking model, is based on WebFlux and Netty, and features high throughput and low resource consumption, making it suitable for modern cloud-native and microservice environments.

[0028] Nacos is an open-source platform for dynamic service discovery, configuration management, and service management, primarily used to help build and manage microservice architectures and cloud-native applications.

[0029] ERP management software: Its core function is to integrate various business processes of an enterprise (such as sales, procurement, production, inventory, finance, human resources, etc.) into a unified digital system, so as to achieve data interoperability, process standardization and resource optimization, thereby improving overall operational efficiency.

[0030] Jenkins is an open-source automation server primarily used to implement continuous integration (CI) and continuous delivery (CD) processes. It automates tasks such as building, testing, and deployment in software development, improving development efficiency and reducing human error.

[0031] Portainer is an open-source, lightweight container management platform primarily used to simplify the deployment and operation management of Docker, DockerCompose, and Kubernetes environments. It provides an intuitive web graphical interface, allowing users to easily manage resources such as containers, images, networks, volumes, and clusters without needing to master complex command-line commands, greatly lowering the barrier to entry for container technology.

[0032] XXL-JOB is a lightweight distributed task scheduling platform primarily used to solve the problem of scheduled task management in large-scale distributed systems. It separates "scheduling" from "execution," using a central scheduling center to manage task triggering, monitoring, and logging, while the specific business logic is handled by individual executors, thus achieving decoupling, high availability, and easy scalability in task scheduling.

[0033] Please refer to Figure 1 , Figure 1This is a functional module diagram of the data aggregation system for the construction industry based on this application. For ease of explanation, the structural diagram of the data aggregation system embodiment based on the construction industry only shows the parts related to the embodiments of this application. Those skilled in the art will understand that the illustrated structure does not constitute a limitation on the device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0034] The data aggregation system 10 based on the construction industry includes: an access gateway layer 11, including a primary reverse proxy server 111 and a secondary application gateway 112; a microservice application layer 12, including an AI service module 121 and a data aggregation service module 122; a middleware and data layer 13, including a message queue 131; and a downstream system integration layer 14, including ERP management software 141 and AI creation software 142. The primary reverse proxy server 111 responds to user service requests and sends the service requests to the secondary application gateway 112 according to a preset load balancing strategy. 2. Authentication of service requests. When the service request is an architectural drawing request, the architectural drawing request is routed to the AI ​​service module 121. After receiving the architectural drawing request, the AI ​​service module 121 calls the AI ​​creation software to generate an image and sends the task completion information to the message queue 131 after the image is generated. The data aggregation service module 122 is used to call the ERP management software 141 after listening to the task completion information in the message queue 131, and update the work progress and / or design output value of the target project in the ERP management software 141 according to the workload completed by the AI ​​creation software 142.

[0035] In some embodiments, when the authentication result of the secondary application gateway 112 is a service request for viewing project financial statements, the project financial statement viewing request is routed to the data aggregation service module 122; after receiving the project financial statement viewing request, the data aggregation service module 122 calls the ERP management software 141 to display the target project financial statement that matches the project financial statement viewing request.

[0036] In some embodiments, the microservice application layer 12 further includes a registration and configuration center module 123; the secondary application gateway 112 authenticates service requests, and when the service request is an architectural drawing request, routes the architectural drawing request to the AI ​​service module 121, including: the secondary application gateway 112 obtaining a service list from the registration and configuration center module 123, wherein the service list includes the IP address, port number, health status bit and custom metadata of different AI service modules; the secondary application gateway 112 determining the target AI service module in different AI service modules 121 according to the service list; when the authentication result indicates that the service request is an architectural drawing request, the architectural drawing request is routed to the target AI service module.

[0037] In some embodiments, the data aggregation system 10 further includes an infrastructure layer 15; the infrastructure layer 15 includes an automation server 151 for implementing continuous integration and continuous delivery, and a container management tool 152; the automation server 151 is used to automatically build AI service modules and data aggregation service modules based on code input by developers; the container management tool 152 is used to perform visual management of the running status of AI service modules and data aggregation service modules.

[0038] In some embodiments, the infrastructure layer 15 further includes a distributed task scheduling platform 153; the distributed task scheduling platform 153 is used to respond to data scheduling requests and retrieve data reports that match the data scheduling requests from the ERP management software.

[0039] To facilitate understanding, the following will be combined with... Figure 2 The functions of the data aggregation system 10 in this embodiment will be described in detail below: Please refer to Figure 2 This is a schematic diagram of the overall architecture of a data aggregation system based on the construction industry provided in this application embodiment.

[0040] The following is about Figure 2 The functions of each architectural layer of the data aggregation system shown are explained in detail below: 1. The access gateway layer uses Nginx as the primary reverse proxy layer, responsible for load balancing and static resource processing. Spring Cloud Gateway is used as the secondary application gateway, responsible for routing, authentication, and traffic control for all microservices. This layer shields the complexity of internal microservices and provides a unified API to the outside world.

[0041] 2. The microservice application layer uses Nacos as the registration and configuration center module. Nacos performs service registration and discovery, as well as dynamic management of configuration files, ensuring that services can be aware of each other and that configuration modifications do not require a restart.

[0042] The AI ​​service module, as an independent microservice, encapsulates the AI ​​inference interface and connects to the underlying "AI creation platform" to handle high-computing requests such as design drawing generation and optimization.

[0043] The data aggregation service module does not produce data, but is responsible for capturing, cleaning, and assembling data from "AI services", "membership services", and "downstream systems".

[0044] Figure 2 The microservice application layer shown also includes membership and system services: handling user identity, permissions, and basic settings.

[0045] 3. The middleware and data layer use RocketMQ as the message queue. When the AI ​​service generates a large number of design documents, it asynchronously notifies the data aggregation service module through RocketMQ to smooth out peaks and avoid blocking the main thread.

[0046] Figure 2 The middleware and data layer also includes MinIO, Redis, and MySQL. MinIO is used as the object storage service, specifically for storing large files (drawings, models) unique to the construction industry, solving the problem of traditional databases' inefficient access to large files. Redis is used to cache frequently accessed data (such as user tokens and common configurations), and MySQL stores business relationship data.

[0047] 4. The downstream system integration layer includes ERP management software and AI creation software, among which, Figure 2 The integrated business and finance system shown is ERP management software; the AI ​​creation software is not included. Figure 2 As shown in the image.

[0048] also, Figure 2 The downstream system integration layer shown also integrates "Xinzhutong" and "Knowledge Base" to automatically archive and accumulate AI-generated results into enterprise knowledge assets.

[0049] 5. The infrastructure layer uses Jenkins as the automation server and Portainer as the container management tool. By introducing Jenkins and Portainer, along with Docker containerization technology, automated building, image packaging, and service deployment after code submission are achieved, ensuring high availability of the platform.

[0050] The following is about Figure 2 The functions of the data aggregation system shown are explained in detail below: First, the data aggregation system in this embodiment adopts a microservice governance architecture of "Nginx + Spring Cloud Gateway + Nacos" to achieve dynamic service scaling and fault isolation.

[0051] To facilitate understanding, the following examples illustrate how to achieve dynamic service scaling and fault isolation: When the 10th "AI Service" instance is started due to peak business conditions (such as hundreds of people needing to produce diagrams in the middle of the year), the new instance will automatically send a signal to acos: "I am the AI ​​service, my IP is 192.168.xx, my port is 8080, I am online." Real-time awareness: Spring Cloud Gateway subscribes to Nacos's service list in real-time (or near real-time). Once Nacos is updated, the Gateway immediately knows: "Oh, now there are 10 AI services available to work, instead of the original 9." Traffic distribution: When the next user request comes in, the Gateway will naturally distribute the request to the newly added instance according to the load balancing algorithm (such as round-robin).

[0052] Because Spring Cloud Gateway no longer hardcodes the target IP in the code, but instead looks it up in Nacos by "service name", the routing policy automatically takes effect whenever the list in Nacos changes, without needing to restart the gateway or manually modify the configuration.

[0053] All microservice instances (such as the "AI service") send a heartbeat to Nacos every few seconds. If an instance crashes (for example due to an out-of-memory error) and cannot send a heartbeat, Nacos will remove it from the "address book" within a few seconds. After the Gateway is synchronized and updated, it will never forward requests to this failed instance again, thus achieving the first layer of isolation.

[0054] Suppose the ERP management software crashes or responds extremely slowly (over 5 seconds). Without isolation, the data aggregation service module will wait indefinitely, causing threads to freeze and ultimately crippling the entire data aggregation system. Spring Cloud Gateway is configured with a circuit breaker (such as Resilience4j). When it detects that the error rate of calls to the ERP management software reaches a threshold (e.g., 50%), it will trip the circuit breaker. After the circuit breaker trips, subsequent requests will directly return a fast failure response of "System busy, please wait" instead of waiting for the crashed system, thus achieving a second layer of isolation.

[0055] Secondly, this embodiment innovatively designs a "data aggregation service" module, which uses RocketMQ asynchronous decoupling to connect the front-end AI creation requests with the back-end financial accounting (business-finance integration) and knowledge accumulation (knowledge base), forming a closed loop.

[0056] Specifically, the data aggregation service constantly listens for messages in RocketMQ. When the AI ​​service finishes generating the image, it sends a message to RocketMQ: {TaskID: 101, Status: Success, User: ZhangSan}.

[0057] The data aggregation service receives a message containing business logic. It knows that "ZhangSan has completed Task 101, which, according to the rules, represents the generation of a design output value." Therefore, the data aggregation service proactively calls the ERP management software to write the output value and simultaneously calls the "knowledge base interface" to upload images.

[0058] The above approach separates the business logic from the "AI drawing tool" and places it separately in the data aggregation service module. The AI ​​tool is only responsible for production, while the aggregation service is responsible for "transporting" and "distributing" it to various departments.

[0059] The "closed-loop" state formed in this embodiment is as follows: Starting point: User initiates a design request. Process: AI generates the design. Flow: Data aggregation service automatically retrieves the results.

[0060] In other words: 1. Financial closed loop: Automatic generation of output value -> Financial statement update -> Management sees real-time costs -> Guidance for the next budget approval.

[0061] 2. Knowledge closed loop: Automatically archive design -> accumulate into knowledge base materials -> serve as corpus for the next AI training -> improve the quality of the next AI design.

[0062] In other words, the data aggregation system of this embodiment enables a single production activity (design) to automatically trigger management activities (finance / archiving), and this management data can ultimately be fed back to optimize production. Through automation, the data aggregation system of this embodiment ensures that no link in this cycle requires manual data handling, guaranteeing the authenticity and flow of the data.

[0063] Finally, the data aggregation system in this embodiment encapsulates the complex building software environment in a Docker container and uses Jenkins to implement an automated pipeline, thus resolving the environment dependency conflict problem.

[0064] Compared with related technologies, the embodiments of this application have at least the following advantages: By setting up a first-level reverse proxy server and a second-level application gateway at the access gateway layer, the first-level reverse proxy server can send user service requests to the second-level application gateway according to a preset load distribution strategy. Furthermore, since the AI ​​service module sends task completion information to a message queue after image generation, and the data aggregation service module listens for task completion information in the message queue and calls the ERP management software, on the one hand, through the asynchronous message processing of RocketMQ and the load balancing of the first-level reverse proxy server, the data aggregation system can withstand a large number of users simultaneously initiating AI drawing requests without crashing, ensuring that the data aggregation system can handle high-concurrency data requests. On the other hand, since the data structure of the front-end architectural drawing requests and the back-end ERP management software are completely different, and their processing speeds are not on the same order of magnitude (drawing may take 1 minute, while accounting only takes 10 milliseconds), the asynchronous communication of the message queue achieves asynchronous decoupling between the architectural drawing requests and the ERP management software, improving the reliability of the data aggregation system. In addition, the data aggregation system can automate the entire process from architectural drawing design to target project progress and financial settlement, greatly improving enterprise management efficiency.

[0065] Based on the same idea as the data aggregation system based on the construction industry in the above embodiments, this application also provides a data aggregation method based on the construction industry, which can be applied to the above-mentioned data aggregation system based on the construction industry.

[0066] Please refer to Figure 3 This is a flowchart of a data aggregation method based on the construction industry provided in an embodiment of this application.

[0067] The specific process of this embodiment is as follows: Figure 3 As shown, it includes the following steps: S301: Responds to user service requests through the primary reverse proxy server and sends the service requests to the secondary application gateway according to the preset load balancing strategy.

[0068] In some embodiments, a "weighted round-robin" or "least connections" strategy is adopted at the Nginx layer (as a primary access gateway).

[0069] Specifically, Nginx uses a weighted round-robin algorithm as its load balancing strategy. System administrators assign different weight values ​​to each node in the Nginx configuration file based on the server hardware performance (such as the number of CPU cores and memory size) of the backend Spring Cloud Gateway nodes.

[0070] The working principle described above will be illustrated with specific examples below: Server A (high performance, 64GB memory): configured weight=3; Server B (normal performance, 16GB memory): configured weight=1. When 4 user requests arrive at Nginx consecutively: Nginx will distribute 3 of the requests to server A and 1 request to server B.

[0071] Construction companies often have a mix of old and new server configurations. By weighting the servers, more powerful servers can handle more traffic, while less powerful servers can handle less, thus avoiding the "weakest link effect" (where the entire system's processing capacity is slowed down by the weakest server).

[0072] When performing canary releases or maintenance shutdowns, the weight of a server can be dynamically adjusted to 0, causing it to stop receiving new requests and achieving a smooth, seamless shutdown.

[0073] S302: Authentication of service requests is performed through a secondary application gateway. When the service request is an architectural drawing request, the architectural drawing request is routed to the AI ​​service module.

[0074] In some embodiments, if the authentication result of the secondary application gateway is that the service request is a project financial statement viewing request, the method further includes: routing the project financial statement viewing request to the data aggregation service module through the secondary application gateway; receiving the project financial statement viewing request through the data aggregation service module, and calling the ERP management software after receiving the project financial statement viewing request to display the project financial statement matching the project financial statement viewing request.

[0075] In some embodiments, service requests are authenticated through a secondary application gateway. When the service request is an architectural drawing request, the architectural drawing request is routed to the AI ​​service module. This includes: obtaining a service list from the registration and configuration center module through the secondary application gateway, wherein the service list includes the IP address, port number, health status bit, and custom metadata of different AI service modules; determining the target AI service module among the different AI service modules based on the service list through the secondary application gateway; and routing the architectural drawing request to the target AI service module when the authentication result indicates that the service request is an architectural drawing request.

[0076] Specifically, the service list includes the following key information fields: 1. Unique Service Name: For example, service-ai-generation (AI service) or service-finance-sync (financial aggregation service).

[0077] 2. Instance Network Address (IP Address & Port): The specific IP address (e.g., 192.168.1.105) and port number (e.g., 8080) on which the microservice instance runs. The Gateway uses this address for physical forwarding.

[0078] 3. Healthy Status: A boolean value (True / False).

[0079] 4. Metadata: A collection of key-value pairs.

[0080] The Gateway pulls the service list from the Nacos registry in real time. This service list includes not only the IP addresses and ports of the microservice instances, but also their health status and metadata. The Gateway first filters out faulty instances based on their health status, achieving fault isolation. Then, based on tags in the metadata (such as whether they have GPU computing power), it precisely routes specific AI drawing requests to microservice instances with the corresponding hardware capabilities (i.e., the target AI service module).

[0081] S303: Receives architectural drawing requests through the AI ​​service module, calls AI creation software to generate images after receiving the architectural drawing requests, and sends task completion information to the message queue after the images are generated.

[0082] S304: Listen to the message queue through the data aggregation service module, and after listening to the task completion information in the message queue, call the ERP management software to update the work progress and / or design output value of the target project in the ERP management software according to the workload completed by the AI ​​creation software.

[0083] In some embodiments, after updating the work progress and / or design output of the target project in the ERP management software based on the workload completed by the AI ​​authoring software, the method further includes: sending an update notification of the target project to the management personnel of the target project.

[0084] Compared with related technologies, the embodiments of this application have at least the following advantages: By setting up a first-level reverse proxy server and a second-level application gateway at the access gateway layer, the first-level reverse proxy server can send user service requests to the second-level application gateway according to a preset load distribution strategy. Furthermore, since the AI ​​service module sends task completion information to a message queue after image generation, and the data aggregation service module listens for task completion information in the message queue and calls the ERP management software, on the one hand, through the asynchronous message processing of RocketMQ and the load balancing of the first-level reverse proxy server, the data aggregation system can withstand a large number of users simultaneously initiating AI drawing requests without crashing, ensuring that the data aggregation system can handle high-concurrency data requests. On the other hand, since the data structure of the front-end architectural drawing requests and the back-end ERP management software are completely different, and their processing speeds are not on the same order of magnitude (drawing may take 1 minute, while accounting only takes 10 milliseconds), the asynchronous communication of the message queue achieves asynchronous decoupling between the architectural drawing requests and the ERP management software, improving the reliability of the data aggregation system. In addition, the data aggregation system can automate the entire process from architectural drawing design to target project progress and financial settlement, greatly improving enterprise management efficiency.

[0085] The data aggregation system and method based on the construction industry provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A data aggregation system based on the construction industry, characterized in that, The architecture of the data aggregation system includes: an access gateway layer, comprising a primary reverse proxy server and a secondary application gateway; a microservice application layer, comprising an AI service module and a data aggregation service module; a middleware and data layer, comprising a message queue; and a downstream system integration layer, comprising ERP management software and AI creation software. The primary reverse proxy server responds to user service requests and sends the service requests to the secondary application gateway according to a preset load balancing strategy. The secondary application gateway authenticates the service request and routes the architectural drawing request to the AI ​​service module when the service request is an architectural drawing request. After receiving the architectural drawing request, the AI ​​service module calls the AI ​​creation software to generate an image, and sends the task completion information to the message queue after the image is generated. The data aggregation service module is used to call the ERP management software after listening to the task completion information in the message queue, and update the work progress and / or design output value of the target project in the ERP management software according to the workload completed by the AI ​​creation software.

2. The data aggregation system based on the construction industry according to claim 1, characterized in that, When the authentication result of the secondary application gateway is that the service request is a request to view the project financial statements, the request to view the project financial statements will be routed to the data aggregation service module. Upon receiving the request to view the project's financial statements, the data aggregation service module invokes the ERP management software to display the target project's financial statements that match the request.

3. The data aggregation system based on the construction industry according to claim 1 or 2, characterized in that, The microservice application layer also includes a registration and configuration center module; The secondary application gateway authenticates the service request, and when the service request is an architectural drawing request, routes the architectural drawing request to the AI ​​service module, including: The secondary application gateway obtains the service list from the registration and configuration center module, wherein the service list includes the IP address, port number, health status bit and custom metadata of different AI service modules; The secondary application gateway determines the target AI service module from the different AI service modules according to the service list; If the authentication result indicates that the service request is the architectural drawing request, the architectural drawing request will be routed to the target AI service module.

4. The data aggregation system based on the construction industry according to claim 1, characterized in that, The data aggregation system also includes an infrastructure layer; The infrastructure layer includes automated servers for enabling continuous integration and continuous delivery, as well as container management tools; The automation server is used to automatically build the AI ​​service module and the data aggregation service module based on the code input by the developers. The container management tool is used to visually manage the operational status of the AI ​​service module and the data aggregation service module.

5. The data aggregation system based on the construction industry according to claim 4, characterized in that, The infrastructure layer also includes a distributed task scheduling platform; The distributed task scheduling platform is used to respond to data scheduling requests and retrieve data reports that match the data scheduling requests from the ERP management software.

6. The data aggregation system based on the construction industry according to claim 1, characterized in that, The primary reverse proxy server is Nginx, and the secondary application gateway is Spring Cloud Gateway.

7. A data aggregation method based on the construction industry, characterized in that, Applied to the data aggregation system according to any one of claims 1 to 6; The data aggregation method includes: The primary reverse proxy server responds to user service requests and sends the service requests to the secondary application gateway according to a preset load balancing strategy. The service request is authenticated through the secondary application gateway. When the service request is an architectural drawing request, the architectural drawing request is routed to the AI ​​service module. The AI ​​service module receives the architectural drawing request, calls the AI ​​creation software to generate an image after receiving the architectural drawing request, and sends the task completion information to the message queue after the image is generated. The data aggregation service module listens to the message queue, and after listening to the task completion information in the message queue, it calls the ERP management software to update the work progress and / or design output value of the target project in the ERP management software according to the workload completed by the AI ​​creation software.

8. The data aggregation method based on the construction industry according to claim 7, characterized in that, If the authentication result of the secondary application gateway indicates that the service request is a request to view project financial statements, the method further includes: The request to view the project's financial statements is routed to the data aggregation service module via the secondary application gateway. The data aggregation service module receives the project financial statement viewing request and, upon receiving the request, invokes the ERP management software to display the project financial statement that matches the request.

9. The data aggregation method based on the construction industry according to claim 7, characterized in that, The step of authenticating the service request through the secondary application gateway, and routing the architectural drawing request to the AI ​​service module when the service request is an architectural drawing request, includes: The service list is obtained from the registration and configuration center module through the secondary application gateway. The service list includes the IP address, port number, health status bit and custom metadata of different AI service modules. The secondary application gateway determines the target AI service module from the different AI service modules based on the service list. If the authentication result indicates that the service request is the architectural drawing request, the architectural drawing request will be routed to the target AI service module.

10. The data aggregation method based on the construction industry according to claim 7, characterized in that, After updating the work progress and / or design output value of the target project in the ERP management software based on the workload completed by the AI ​​creation software, the method further includes: Send an update notification for the target project to the project's administrator.

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