A server information intelligent interaction method and system based on NFC technology

Abstract

The application discloses a kind of server information intelligent interaction method and system based on NFC technology, belong to server information interaction technical field.The method is by obtaining server static information and dynamic information and write in NFC module to complete binding and update, trigger NFC module to read information or send instruction trigger predefined operation, send server unique identifier to cloud platform query and receive value-added information, relevant picture of server is photographed and uploaded cloud platform analysis and cooperates with the server information read and shows;System includes NFC hardware module, server main body, intelligent terminal and cloud service platform, each module cooperates work.The scheme realizes the near distance convenient interaction of server information, without complex wiring and manual configuration, supplement rich operation and maintenance data and intelligent visual analysis result, improve information acquisition efficiency and operation and maintenance decision accuracy, guarantee data transmission storage security, adapt to diversified operation and maintenance demand.

Description

Technical Field

[0001] This invention relates to the field of server information interaction technology, and in particular to a server information intelligent interaction method and system based on NFC technology. Background Technology

[0002] With the continuous expansion of data center scale and the rapid growth in the number of servers, server operation and maintenance management has become one of the core aspects of the information technology field. Efficient server information interaction is a key support for ensuring the smooth operation of maintenance work. Currently, information interaction technology in the server operation and maintenance field is developing towards intelligence and convenience, and various data collection, transmission, and display technologies have been widely applied in actual operation and maintenance scenarios. At the information collection level, mainstream servers generally have basic hardware status and operating parameter collection capabilities, achieving initial data collection through built-in sensors and software agents. In terms of interaction methods, communication between terminal devices and servers is gradually diversifying, with both wired communication and traditional wireless communication technologies having mature applications. In terms of data support, the popularization of cloud platforms has made the storage and management of massive amounts of server-related data possible, providing a data foundation for operation and maintenance decisions. At the same time, the application of image recognition technology in industrial equipment operation and maintenance is also gradually expanding, providing technical reference for the visual detection of equipment status, forming an overall multi-technology integrated server operation and maintenance information interaction ecosystem.

[0003] Although current server operation and maintenance information interaction technologies have made some progress, many technical problems still need to be solved in light of actual operation and maintenance needs, and these problems cannot be effectively solved by existing conventional technical solutions. Specifically, current methods of acquiring server information are cumbersome, relying heavily on physical wiring or complex manual configuration processes, making it difficult to achieve rapid, close-range interaction. This results in low efficiency for operation and maintenance personnel when acquiring static and dynamic server information on-site, increasing operation and maintenance costs. Simultaneously, current technologies cannot achieve convenient linkage between server information and terminal devices. It is difficult to trigger predefined operation and maintenance operations through simple operations, nor can it efficiently coordinate locally acquired server information with value-added information stored in the cloud, leaving operation and maintenance decisions without comprehensive data support. Furthermore, existing solutions lack intelligent visual analysis capabilities for the status of server physical components, failing to correlate and display device visual information with data information. Operation and maintenance personnel must rely on manual visual inspection to judge component status, which is prone to human error and makes it difficult to quickly locate faulty components, further affecting the accuracy and efficiency of operation and maintenance work. These problems severely restrict the level of intelligence and overall efficiency of server operation and maintenance management. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a server information intelligent interaction method and system based on NFC technology.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A method for intelligent interaction of server information based on NFC technology is provided, the method comprising the following steps:

[0007] S1. Obtain static and dynamic information from the server, and write the static and dynamic information into the storage area of ​​the NFC module to complete information binding and updating;

[0008] S2. Trigger the NFC module to read server information in the storage area, or send a command to the NFC module to trigger a predefined operation;

[0009] S3. Send the server's unique identifier to the cloud platform, query the cloud platform's database, and receive the returned value-added information;

[0010] S4. Take pictures of the server and upload them to the cloud platform. Analyze and process the pictures through the cloud platform, receive the analysis results and display them together with the read server information.

[0011] Furthermore, step S1 includes the following sub-steps:

[0012] S1.1. Continuously collect static and dynamic information of the server. Static information includes fixed attribute information, such as asset identifier, model and specifications, production batch and manufacturing date. Dynamic information includes hardware operating status, operating system parameters and resource usage performance data, such as CPU utilization, memory usage, remaining storage space and network transmission rate.

[0013] S1.2. After the static and dynamic information is collected, a stable data transmission link is established through the preset standard serial communication interface, and the collected static and dynamic information is completely written into the designated storage partition of the NFC module in the preset format.

[0014] S1.3. Write operations to the NFC module based on static and dynamic information to complete the two-way information binding between the server and the NFC module. When the dynamic information changes, the real-time update mechanism is automatically triggered to keep the dynamic information in the storage area synchronized with the actual operating status of the server.

[0015] Furthermore, step S2 includes the following sub-steps:

[0016] S2.1. Connect the NFC-enabled terminal to the NFC module integrated in the server to trigger the contactless communication connection establishment process, and ensure the stability of the communication link through signal strength detection;

[0017] S2.2. Automatically read the pre-stored static information and updated dynamic information in the NFC module's storage area through the dedicated NFC communication channel, and perform CRC data integrity verification during transmission to prevent information loss or tampering;

[0018] S2.3. The terminal's built-in dedicated application edits the preset format operation instructions. The instructions are forwarded to the server's built-in agent service via the NFC module, triggering the server to execute predefined operations. The predefined operations include restarting the service, collecting operation logs, hardware self-testing, and parameter configuration querying.

[0019] Furthermore, step S3 includes the following sub-steps:

[0020] S3.1. The server's unique identifier, which is read, is encapsulated and sent to the preset cloud service platform through a secure encrypted transmission protocol. During the transmission process, an asymmetric encryption algorithm is used to encrypt and protect the data.

[0021] S3.2. After receiving the identifier, the cloud platform establishes a stable connection with the database through the backend service, performs an accurate retrieval based on the unique identifier, and filters the associated data corresponding to the server.

[0022] S3.3. Receive value-added information returned by the cloud platform. The value-added information includes historical server operation data, data center topology relationships, past maintenance work order records and equipment configuration parameters. After being sorted by data type, the information is transmitted to the terminal.

[0023] Furthermore, step S4 includes the following sub-steps:

[0024] S4.1. Take targeted photos of key areas or suspected faulty components on the front panel of the server, and adjust the shooting angle and focal length to ensure that the key components in the image are unobstructed and the clarity meets the requirements of algorithm analysis.

[0025] S4.2. Through a stable communication link between the terminal and the cloud platform, the captured images are uploaded to the image processing module of the cloud platform in a preset lossless file format;

[0026] S4.3. The cloud platform calls the preset target detection algorithm to perform real-time regional analysis of the image, and locates the specific location of key components through feature point extraction and matching;

[0027] S4.4. Identify the operating status of key components based on algorithm analysis results, determine whether there is any damage, abnormal indication, or looseness, and mark it accordingly;

[0028] S4.5. Receive the labeled recognition results returned by the cloud platform, and display the labeled recognition results in conjunction with the server information read in step S2 according to the device component association logic.

[0029] Furthermore, in step S1, the server constructs a continuous data collection mechanism through its built-in proxy service, periodically acquiring its own static and dynamic information according to preset collection rules. The static information includes the server's fixed attribute data, which includes asset identification, production specifications, factory parameters, and equipment number. The dynamic information includes hardware operating status parameters, operating system operating status data, and resource usage performance indicators, which include CPU, memory, storage, and network usage data. The collected information is first temporarily stored in a local cache for deduplication and format standardization preprocessing, and then transmitted to the NFC module through a designated channel.

[0030] Furthermore, in step S3, the cloud platform builds a backend API service based on a high-performance web framework and a dedicated runtime environment. After receiving the server's unique identifier, the backend API service first performs format verification and legality verification on the identifier, and then calls the database interface according to the preset query logic. The database adopts a distributed database type that supports highly flexible queries and large-capacity storage, and quickly retrieves relevant data associated with the server's unique identifier. The relevant data includes historical data, topology relationships, and configuration parameters, and the relevant data is organized into a standardized format and returned.

[0031] Furthermore, in step S3, all functional service components of the cloud platform are uniformly packaged and deployed using containerization technology. Each functional module runs independently in a dedicated container. Container orchestration tools are used to achieve collaborative scheduling between modules, ensuring operational consistency in different deployment environments. Reverse proxy tools are used to receive requests sent by terminals, and to perform protocol conversion, forwarding, illegal request filtering, and data integrity security verification on the requests. At the same time, load balancing strategies are configured to dynamically allocate request traffic based on the real-time load of each backend service node.

[0032] Furthermore, in step S4.3, the target detection algorithm first performs preprocessing operations on the uploaded image to optimize image quality. The preprocessing operations include noise reduction, contrast enhancement, and edge sharpening. Then, the image is analyzed in real time by region using a preset feature model to automatically match and identify key components of the server. Key components include hard drive indicator lights, power buttons, status display panels, interface areas, and fan operation indicator lights. Status recognition marks normal operation status and abnormal prompt status based on the color, flashing frequency, shape, and brightness change characteristics of the components, while recording the coordinate information and feature description of the abnormal area.

[0033] A server information intelligent interaction system based on NFC technology is provided. The system includes an NFC hardware module, a server body, a smart terminal, and a cloud service platform.

[0034] The NFC hardware module is modularly integrated inside or outside the server chassis, integrating an NFC chip, signal transmission antenna, microcontroller, and standard serial communication interface. It stores static and dynamic information about the server and enables bidirectional data interaction with smart terminals. The server itself has a built-in proxy service module with data acquisition, processing, temporary storage, and transmission functions. This module continuously collects its own static and dynamic information and synchronizes it to the NFC module. The smart terminal has NFC communication capabilities and a built-in dedicated application. This application supports information reading, command editing and sending, image capture, data reception, and collaborative display functions. It reads information stored in the NFC hardware module, sends operation commands to the NFC module, and captures images of the server. The cloud service platform deploys a backend service cluster, a distributed database, and a target detection algorithm module. The backend service cluster is responsible for request reception, processing, and data forwarding. The distributed database stores server-related data, including asset information, historical operating data, topology relationships, maintenance work order records, and equipment configuration parameters. The target detection algorithm module analyzes and processes uploaded images, providing a complete system for data querying, image analysis, and result feedback.

[0035] The beneficial effects of this invention are:

[0036] (1) Realizes short-range intelligent interaction of server information through NFC technology, without the need for complicated wiring and manual configuration, simplifies the operation and maintenance process, efficiently obtains server information, and reduces the threshold of operation and maintenance.

[0037] (2) By relying on the linkage of cloud data retrieval and intelligent image analysis, rich value-added information is supplemented, the equipment status is presented intuitively, and the operation and maintenance are accurately judged, thus improving the accuracy of operation and maintenance work;

[0038] (3) Integrating modular design and multiple security protection mechanisms ensures data transmission and storage security, enhances system expansion and adaptability, and adapts to diverse operation and maintenance scenarios. Attached Figure Description

[0039] Figure 1 A flowchart illustrating the steps of a server information intelligent interaction method based on NFC technology;

[0040] Figure 2 This is a flowchart illustrating a specific implementation of a server information intelligent interaction method based on NFC technology, provided as an example. Detailed Implementation

[0041] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Example 1

[0043] See Figure 1 A server information intelligent interaction method based on NFC technology, the method includes the following steps:

[0044] S1. Obtain static and dynamic information from the server, and write the static and dynamic information into the storage area of ​​the NFC module to complete information binding and updating;

[0045] S2. Trigger the NFC module to read server information in the storage area, or send a command to the NFC module to trigger a predefined operation;

[0046] S3. Send the server's unique identifier to the cloud platform, query the cloud platform's database, and receive the returned value-added information;

[0047] S4. Take pictures of the server and upload them to the cloud platform. Analyze and process the pictures through the cloud platform, receive the analysis results and display them together with the read server information.

[0048] In some embodiments, step S1 includes the following sub-steps:

[0049] S1.1. Continuously collect static and dynamic information of the server. Static information includes fixed attribute information, such as asset identifier, model and specifications, production batch and manufacturing date. Dynamic information includes hardware operating status, operating system parameters and resource usage performance data, such as CPU utilization, memory usage, remaining storage space and network transmission rate.

[0050] S1.2. After the static and dynamic information is collected, a stable data transmission link is established through the preset standard serial communication interface, and the collected static and dynamic information is completely written into the designated storage partition of the NFC module in the preset format.

[0051] S1.3. Write operations to the NFC module based on static and dynamic information to complete the two-way information binding between the server and the NFC module. When the dynamic information changes, the real-time update mechanism is automatically triggered to keep the dynamic information in the storage area synchronized with the actual operating status of the server.

[0052] In some embodiments, step S2 includes the following sub-steps:

[0053] S2.1. Connect the NFC-enabled terminal to the NFC module integrated in the server to trigger the contactless communication connection establishment process, and ensure the stability of the communication link through signal strength detection;

[0054] S2.2. Automatically read the pre-stored static information and updated dynamic information in the NFC module's storage area through the dedicated NFC communication channel, and perform CRC data integrity verification during transmission to prevent information loss or tampering;

[0055] S2.3. The terminal's built-in dedicated application edits the preset format operation instructions. The instructions are forwarded to the server's built-in agent service via the NFC module, triggering the server to execute predefined operations. The predefined operations include restarting the service, collecting operation logs, hardware self-testing, and parameter configuration querying.

[0056] In some embodiments, step S3 includes the following sub-steps:

[0057] S3.1. The server's unique identifier, which is read, is encapsulated and sent to the preset cloud service platform through a secure encrypted transmission protocol. During the transmission process, an asymmetric encryption algorithm is used to encrypt and protect the data.

[0058] S3.2. After receiving the identifier, the cloud platform establishes a stable connection with the database through the backend service, performs an accurate retrieval based on the unique identifier, and filters the associated data corresponding to the server.

[0059] S3.3. Receive value-added information returned by the cloud platform. The value-added information includes historical server operation data, data center topology relationships, past maintenance work order records and equipment configuration parameters. After being sorted by data type, the information is transmitted to the terminal.

[0060] In some embodiments, step S4 includes the following sub-steps:

[0061] S4.1. Take targeted photos of key areas or suspected faulty components on the front panel of the server, and adjust the shooting angle and focal length to ensure that the key components in the image are unobstructed and the clarity meets the requirements of algorithm analysis.

[0062] S4.2. Through a stable communication link between the terminal and the cloud platform, the captured images are uploaded to the image processing module of the cloud platform in a preset lossless file format;

[0063] S4.3. The cloud platform calls the preset target detection algorithm to perform real-time regional analysis of the image, and locates the specific location of key components through feature point extraction and matching;

[0064] S4.4. Identify the operating status of key components based on algorithm analysis results, determine whether there is any damage, abnormal indication, or looseness, and mark it accordingly;

[0065] S4.5. Receive the labeled recognition results returned by the cloud platform, and display the labeled recognition results in conjunction with the server information read in step S2 according to the device component association logic.

[0066] In some embodiments, in step S1, the server constructs a continuous acquisition mechanism through a built-in proxy service, periodically acquiring its own static and dynamic information according to preset acquisition rules. The static information includes the server's fixed attribute data, which includes asset identification, production specifications, factory parameters, and equipment number. The dynamic information includes hardware operating status parameters, operating system operating status data, and resource usage performance indicators, which include CPU, memory, storage, and network usage data. The acquired information is first temporarily stored in a local cache for deduplication and format standardization preprocessing, and then transmitted to the NFC module through a designated channel.

[0067] In some embodiments, in step S3, the cloud platform builds a backend API service based on a high-performance web framework and a dedicated runtime environment. After receiving the server's unique identifier, the backend API service first performs format verification and legality verification on the identifier, and then calls the database interface according to the preset query logic. The database adopts a distributed database type that supports highly flexible queries and large-capacity storage, and quickly retrieves relevant data associated with the server's unique identifier. The relevant data includes historical data, topology relationships, and configuration parameters, and the relevant data is organized into a standardized format and returned.

[0068] In some embodiments, in step S3, all functional service components of the cloud platform are uniformly packaged and deployed using containerization technology. Each functional module runs independently in a dedicated container. The collaborative scheduling between modules is achieved through container orchestration tools to ensure operational consistency in different deployment environments. The reverse proxy tool receives requests sent by the terminal, performs protocol conversion, forwarding, illegal request filtering, and data integrity security verification on the requests, and configures load balancing strategies to dynamically allocate request traffic based on the real-time load of each backend service node.

[0069] In some embodiments, in step S4.3, the target detection algorithm first performs preprocessing operations on the uploaded image to optimize image quality. The preprocessing operations include noise reduction, contrast enhancement, and edge sharpening. Then, the image is analyzed in real time by region using a preset feature model to automatically match and identify key components of the server. Key components include hard disk indicator lights, power buttons, status display panels, interface areas, and fan operation indicator lights. Status recognition marks normal operation status and abnormal prompt status based on the color, flashing frequency, shape, and brightness change characteristics of the components, while recording the coordinate information and feature description of the abnormal area.

[0070] In some embodiments, a server information intelligent interaction system based on NFC technology is provided, the system including an NFC hardware module, a server body, a smart terminal and a cloud service platform;

[0071] The NFC hardware module is modularly integrated inside or outside the server chassis, integrating an NFC chip, signal transmission antenna, microcontroller, and standard serial communication interface. It stores static and dynamic information about the server and enables bidirectional data interaction with smart terminals. The server itself has a built-in proxy service module with data acquisition, processing, temporary storage, and transmission functions. This module continuously collects its own static and dynamic information and synchronizes it to the NFC module. The smart terminal has NFC communication capabilities and a built-in dedicated application. This application supports information reading, command editing and sending, image capture, data reception, and collaborative display functions. It reads information stored in the NFC hardware module, sends operation commands to the NFC module, and captures images of the server. The cloud service platform deploys a backend service cluster, a distributed database, and a target detection algorithm module. The backend service cluster is responsible for request reception, processing, and data forwarding. The distributed database stores server-related data, including asset information, historical operating data, topology relationships, maintenance work order records, and equipment configuration parameters. The target detection algorithm module analyzes and processes uploaded images, providing a complete system for data querying, image analysis, and result feedback.

[0072] Example 2

[0073] This embodiment provides a specific implementation process of a server information intelligent interaction method and system based on NFC technology, such as... Figure 2 As shown, the specific steps are as follows:

[0074] Step S1: Obtain server information and complete the binding and update with the NFC module:

[0075] The purpose of step S1 is to collect various types of information from the server and associate this information with the NFC module to achieve information storage and dynamic updates, laying the foundation for subsequent near-field interaction. This step includes three closely linked sub-steps, each building upon the previous one to ensure the comprehensiveness of information collection, the stability of transmission, and the reliability of binding.

[0076] S1.1: Continuously collect static and dynamic information from the server:

[0077] The server utilizes a built-in proxy service module to establish a continuous data collection mechanism, periodically acquiring its own static and dynamic information according to preset collection rules. Static information comprises fixed server attributes that do not change with operational status. These fixed attributes include asset identification, model specifications, production batch, and manufacturing date. This information serves as the fundamental identifier for different servers and is crucial for asset management. Dynamic information, on the other hand, consists of real-time data that changes during server operation. This primarily includes hardware operating status, operating system parameters, and resource usage performance data. Specifically, resource usage performance data encompasses CPU utilization, memory usage, remaining storage space, and network transmission rate. This data directly reflects the server's real-time operating load and health status.

[0078] During the data collection process, the proxy service module performs preliminary processing on the acquired information. The collected information is first temporarily stored in a local cache for deduplication and format standardization preprocessing. Deduplication removes redundant information collected repeatedly, reducing data storage pressure and bandwidth consumption for subsequent transmission. Format standardization preprocessing converts information from different sources and in different formats into a preset standard format, ensuring consistency in subsequent data transmission and processing, and avoiding parsing errors or information loss due to inconsistent formats.

[0079] S1.2: Write the collected information to the designated storage partition of the NFC module:

[0080] After static and dynamic information is collected and preprocessed, a stable data transmission link is established through a preset standard serial communication interface. This information is then written completely into the designated storage partition of the NFC module according to a preset format. The standard serial communication interface features stable communication and strong compatibility, ensuring reliable data transmission between the server and the NFC module and avoiding data transmission interruptions or errors caused by unstable communication interfaces.

[0081] When establishing a data transmission link, the connectivity of the communication link is first checked, and data transmission only begins after confirming that the link is unobstructed. During data transmission, static and dynamic information are encapsulated according to a preset format to ensure a clear data structure for easy reception and storage by the NFC module. The designated storage partitions of the NFC module are pre-divided, with different types of information stored in corresponding partitions. For example, static information is stored in one partition, and dynamic information in another. This partitioning design facilitates rapid retrieval and management of subsequent information while also preventing interference between different types of information.

[0082] S1.3: Complete information binding and realize real-time updates of dynamic information:

[0083] By writing static and dynamic information to the NFC module, a two-way information binding is achieved between the server and the NFC module. This two-way information binding means that the information stored in the NFC module forms a unique association with the corresponding server. By reading the information in the NFC module, the corresponding server can be accurately identified, and the server can also update and maintain the information in the NFC module through the communication link.

[0084] When the server's dynamic information changes, a real-time update mechanism is automatically triggered. The server's proxy service module monitors these changes in real time. Once a change is detected, it immediately initiates a data transmission process, sending the updated dynamic information to the NFC module via the established communication link. This overwrites the old data in the original storage area, ensuring that the dynamic information in the NFC module's storage area remains synchronized with the server's actual operating status. This real-time update mechanism ensures that subsequent read dynamic information is always the latest server status data, preventing operational decision-making errors caused by information lag.

[0085] Step S2: Trigger the NFC module and realize information reading and command transmission:

[0086] Step S2 enables near-field intelligent interaction through contactless communication between the terminal and the NFC module, facilitating the reading of server information and the transmission of operation commands. This eliminates the need for complex physical wiring or manual configuration, simplifying the operation and maintenance process. This step also comprises three interoperable sub-steps, which respectively establish a communication connection, verify information reading, and forward and execute commands.

[0087] S2.1: Establish a stable communication connection between the terminal and the NFC module:

[0088] The process involves placing an NFC-enabled terminal against the NFC module integrated into the server to trigger a contactless communication connection establishment process. The NFC-enabled terminal has a built-in dedicated NFC communication module that can proactively initiate communication requests with the NFC module. When the terminal and NFC module are within communication range, the terminal automatically detects the NFC module's signal, initiates a connection request, and the NFC module responds upon receiving the request. Both parties then negotiate communication parameters and establish a communication link.

[0089] During the communication link establishment process, signal strength detection ensures the stability of the communication link. The terminal monitors the communication signal strength with the NFC module in real time. If the signal strength is lower than a preset threshold, the user is prompted to adjust the contact position or angle between the terminal and the NFC module to ensure that the signal strength meets the communication requirements. If the signal strength is stable above the preset threshold, the communication link is confirmed to be successfully established. This signal strength detection mechanism can effectively avoid communication interruptions or data transmission errors caused by excessive communication distance or improper contact position, ensuring the smooth operation of subsequent interactive operations.

[0090] S2.2: Read information from the NFC module and perform integrity verification:

[0091] Once the communication link is stably established, the pre-stored static information and updated dynamic information in the NFC module's storage area are automatically read through the dedicated NFC communication channel. The dedicated NFC communication channel uses a specialized communication protocol, featuring high data transmission speed and high security, ensuring rapid information transmission between the terminal and the NFC module. The reading process proceeds in a preset order, first reading data from the static information storage partition, then reading data from the dynamic information storage partition, ensuring the orderly and complete reading of information.

[0092] To prevent information loss or tampering during transmission, a CRC (CRC checksum) is performed during transmission. CRC is a commonly used error detection method. It calculates a checksum from the transmitted data. After receiving the information, the terminal recalculates the checksum and compares it with the checksum sent by the NFC module. If they match, the information transmission is complete and has not been lost or tampered with. If they do not match, an anomaly has occurred, and the terminal sends a reread request to the NFC module. Upon receiving the request, the NFC module retransmits the corresponding information until the terminal receives complete and error-free information.

[0093] S2.3: Transmit operation instructions and trigger the server to execute predefined operations:

[0094] While reading information, users can edit preset-format operation commands through a dedicated application built into the terminal. The terminal's dedicated application provides an intuitive operation interface, allowing users to select corresponding predefined operations according to their operational needs, or manually input custom operation commands. The application will encapsulate the user-selected or input commands according to a preset format, ensuring that the command format meets the parsing requirements of the server proxy service module.

[0095] The encapsulated operation command is forwarded to the server's built-in agent service via the NFC module. After receiving the command from the terminal, the NFC module transmits it to the agent service module through the communication link with the server. The agent service module parses the received command and identifies the corresponding predefined operation. These predefined operations include common maintenance tasks such as restarting the service, collecting operation logs, hardware self-testing, and parameter configuration queries. These operations do not require manual execution by the user on-site and can be triggered remotely via command transmission.

[0096] After parsing the instructions, the server proxy service module executes the corresponding predefined operations according to the instructions. After the operation is completed, the proxy service module generates operation execution result information and transmits the result information to the NFC module through the communication link. The NFC module then forwards the result information to the terminal, and the terminal's dedicated application displays the result information to the user, allowing the user to understand the operation execution status in a timely manner.

[0097] Step S3: Cloud Interaction and Value-Added Information Acquisition

[0098] Step S3 involves interacting with the cloud platform using the server's unique identifier to obtain richer value-added information, enabling the linkage between local information and cloud data, and providing more comprehensive data support for operational and maintenance decisions. This step comprises three sub-steps: identifier transmission, cloud retrieval, and value-added information reception and organization. It also integrates with the cloud platform's deployment architecture and service mechanisms to ensure the efficiency and reliability of cloud interaction.

[0099] S3.1: Encrypt the transmission server's unique identifier to the cloud platform:

[0100] After reading the static information of the server, the terminal extracts the server's unique identifier, which is used to distinguish different servers and corresponds one-to-one with the server data stored in the cloud platform's database. The terminal then encapsulates the extracted server unique identifier using a secure encrypted transmission protocol and sends it to the preset cloud platform. The encapsulation process packages the unique identifier according to a preset format and adds transmission header information to facilitate cloud platform recognition and parsing.

[0101] During transmission, an asymmetric encryption algorithm is used to protect the data. This algorithm uses a public and private key pair for encryption and decryption. The terminal uses the public key publicly available from the cloud platform to encrypt the encapsulated unique identifier. The encrypted ciphertext is then transmitted to the cloud platform over the network. Upon receiving the ciphertext, the cloud platform uses its own private key to decrypt it, obtaining the original server unique identifier. This encryption method effectively prevents the unique identifier from being intercepted or tampered with during transmission, ensuring the security of data transmission.

[0102] S3.2: Cloud platform retrieves server-related data:

[0103] After receiving the identifier, the cloud platform first decrypts it to obtain the original server-unique identifier. The cloud platform builds a backend API service based on a high-performance web framework and a dedicated runtime environment. Upon receiving the server-unique identifier, the backend API service first performs format validation and validity verification. Format validation confirms that the identifier's format conforms to preset standards, avoiding retrieval failures due to format errors; validity verification confirms that the server corresponding to the identifier has been registered with the cloud platform, preventing malicious requests from unauthorized identifiers.

[0104] After successful verification, the backend API service calls the database interface according to the preset query logic, establishing a stable connection with the distributed database. The database is a distributed database type that supports highly flexible queries and large-capacity storage, capable of storing a large amount of server-related data and possessing fast retrieval capabilities. The backend API service sends the server's unique identifier as a search condition to the distributed database, which performs an accurate search based on this identifier, filtering the associated data corresponding to that server. This associated data includes the server's historical operational data, data center topology relationships, past maintenance work order records, and equipment configuration parameters, supplementing and expanding upon the information retrieved locally.

[0105] S3.3: Receive and process value-added information returned from the cloud:

[0106] After the distributed database completes its retrieval, it returns the filtered server-related data to the cloud platform's backend API service. The backend API service then organizes this data into a standardized format, forming value-added information. This value-added information includes historical server operation data, data center topology relationships, past maintenance work order records, and equipment configuration parameters. This information is categorized and organized according to data type; for example, historical operation data is arranged in chronological order, and maintenance work order records are categorized by work order status, ensuring a clear information structure that is easy for terminals to parse and display.

[0107] The cloud platform transmits the processed value-added information to the terminal via the network. After receiving the value-added information, the terminal associates and stores it with the static and dynamic information read from the server in step S2. The terminal's dedicated application further processes and preprocesses the value-added information according to preset logic, such as binding the value-added information with the corresponding server information to ensure that information can be linked during subsequent display.

[0108] The deployment and service guarantee mechanism of the cloud platform is as follows:

[0109] All functional service components of the cloud platform are uniformly packaged and deployed using containerization technology, with each functional module running independently in its own dedicated container. Containerization ensures that each functional module operates in an independent environment, avoiding environmental conflicts between different modules, and also facilitates module deployment, updates, and maintenance. Container orchestration tools enable collaborative scheduling between modules. These tools can dynamically adjust the resource allocation of each container based on service requirements, achieving efficient collaboration between modules and ensuring operational consistency across different deployment environments.

[0110] The cloud platform receives requests from terminals through a reverse proxy tool. This reverse proxy tool is responsible for protocol conversion, forwarding, illegal request filtering, and data integrity and security verification of the requests. Protocol conversion transforms the requests sent by the terminal into a protocol that the cloud platform's internal services can recognize; request forwarding forwards the requests to the corresponding backend service modules based on the request type and content; illegal request filtering identifies and blocks malicious or non-compliant requests, ensuring the secure operation of the cloud platform; and data integrity and security verification verifies the request data to ensure that it has not been tampered with during transmission.

[0111] Meanwhile, the cloud platform is configured with a load balancing strategy to dynamically allocate request traffic based on the real-time load of each backend service node. The load balancing strategy can evenly distribute a large number of terminal requests to various backend service nodes, avoiding slow response or service interruption caused by excessive load on a single node, and effectively improving the system's response speed and operational stability in high-concurrency scenarios.

[0112] Step S4: Intelligent Image Recognition and Collaborative Information Display:

[0113] Step S4 introduces a target detection algorithm to intelligently analyze server-related images, digitizing the visual information of the physical equipment. This digitized information is then displayed in conjunction with previously acquired server information, reducing the workload of manual visual inspection and improving operational efficiency. This step comprises five sub-steps, covering image capture, uploading, analysis, annotation, and collaborative display, forming a complete image recognition and information display process.

[0114] S4.1: Take photos of the server that meet the requirements:

[0115] Maintenance personnel use NFC-enabled terminals to take targeted photos of key areas on the server's front panel or components suspected of being faulty. Before taking photos, personnel can view shooting instructions through a dedicated terminal application to clarify the location of key areas and shooting requirements. They adjust the shooting angle and focus to ensure that key components are unobstructed and the image clarity meets the requirements of algorithm analysis, guaranteeing that the image clearly presents the appearance and operational status of key components, providing high-quality image data for subsequent algorithm analysis.

[0116] During the shooting process, the terminal's dedicated application provides a real-time preview function. Maintenance personnel can adjust shooting parameters through the preview screen to ensure that critical components are fully within the frame without significant blur, reflections, or obstructions. If the captured image does not meet the requirements, the application will provide prompts, guiding maintenance personnel to retake the image until a satisfactory result is obtained.

[0117] S4.2: Upload images to the cloud platform image processing module:

[0118] After capturing images that meet the requirements, the captured images are uploaded to the cloud platform's image processing module in a preset lossless file format via a stable communication link between the terminal and the cloud platform. The lossless file format fully preserves the original pixel information and detailed features of the image, avoiding image quality degradation caused by format compression and ensuring the accuracy of subsequent algorithm analysis.

[0119] During the upload process, the terminal will display the upload progress in real time, informing the user of the completion status of the image upload. If the network is interrupted or abnormal, the upload process will be paused and will automatically resume once the network is restored, realizing the function of resuming interrupted uploads and avoiding image upload failures or duplicate uploads due to network problems. At the same time, the terminal will perform a simple format verification on the uploaded image to confirm that the image format meets the receiving requirements of the cloud platform's image processing module. If the format does not meet the requirements, the user will be prompted to convert the image format before uploading.

[0120] S4.3: The cloud platform performs image preprocessing and key component localization.

[0121] After an image is uploaded to the image processing module of the cloud platform, the object detection algorithm first performs preprocessing operations on the uploaded image to optimize image quality. Preprocessing operations include noise reduction, contrast enhancement, and edge sharpening. Noise reduction removes noise interference from the image, making it clearer; contrast enhancement improves the contrast between key components and the background, highlighting the features of key components; edge sharpening enhances the edge contours of key components, making their shapes and boundaries clearer, facilitating subsequent feature extraction and recognition.

[0122] After preprocessing, the image is analyzed in real-time by region using a preset feature model. This region-based analysis divides the image into multiple continuous regions, and the algorithm scans and analyzes each region sequentially to avoid missing key components. The specific location of key components is located through feature point extraction and matching. The feature model stores feature data of various key components from the server. The algorithm compares the feature points in the image with the feature data in the model; when the similarity reaches a preset threshold, it determines that a corresponding key component exists at that location and records the coordinate information of the key component.

[0123] Key components include external server components such as hard drive indicator lights, power buttons, status display panels, interface areas, and fan operation indicator lights. The operating status of these components directly reflects the server's working condition and is a key focus of maintenance and inspection.

[0124] S4.4: Identify and label the status of key components:

[0125] Based on the key component location results output by the algorithm analysis, the operating status of key components is further identified. Status identification is based on the component's color, flashing frequency, shape, and brightness change characteristics; different operating states correspond to different feature combinations. For example, a solid green hard drive indicator light indicates that the hard drive is operating normally, while a flashing red light indicates that the hard drive is faulty; a pressed power button indicates that the server is powered on, while a released power button indicates that the server is powered off.

[0126] Based on these feature combinations, the algorithm determines whether key components are damaged, show abnormal indicators, or are loose, and then labels the abnormalities. The labeling process adds clear markers to the locations of abnormal components in the image, such as selecting the abnormal component with a red box and labeling it with the type of abnormality, such as "damaged," "abnormal indicator," or "loose." Simultaneously, it records the coordinate information and feature descriptions of the abnormal area. The coordinate information is accurate to the pixel level, and the feature descriptions record the specific characteristics of the abnormal component in detail, such as "the hard drive indicator light is solid red and does not flicker" or "the power button is loose and has a gap with the panel."

[0127] S4.5: Collaborative display of labeled recognition results and server information:

[0128] After the cloud platform's image processing module completes image analysis and annotation, it transmits the annotated recognition results to the terminal via the network. The terminal's dedicated application receives the annotated recognition results. The application then collaboratively displays the annotated recognition results and the server information read in step S2 according to the device component association logic, achieving complementarity between visual and data information.

[0129] The collaborative display uses a combination of images and text, presenting labeled images alongside corresponding static and dynamic server information. For example, a labeled image is displayed on the left side of the terminal screen, while the right side displays static information such as the server's asset identifier and model specifications, along with dynamic information such as CPU utilization and memory usage. Clicking on a key component label in the image automatically redirects the application to a detailed data information page for that component, displaying historical operational data, relevant maintenance work order records, and other value-added information, allowing users to intuitively combine the component's visual status with data information for analysis.

[0130] The system composition and the collaborative working mechanism of each module are as follows:

[0131] The server information intelligent interaction system based on NFC technology in this embodiment includes four components: NFC hardware module, server body, smart terminal and cloud platform. Each module has a clear division of labor and works together to realize the intelligent interaction function of server information.

[0132] The NFC hardware module is integrated modularly inside or outside the server chassis, integrating an NFC chip, a signal transmission antenna, a microcontroller, and a standard serial communication interface. The NFC chip is responsible for information storage and processing, the signal transmission antenna is used for contactless communication with smart terminals, the microcontroller controls the overall operation of the module, and the standard serial communication interface is used for data interaction with the server. The module's main functions are to store static and dynamic information from the server, enable bidirectional data interaction with smart terminals, receive operation commands from smart terminals and forward them to the server, and simultaneously update and synchronize information from the server to its own storage area.

[0133] The server's main body has a built-in proxy service module, which has data acquisition, processing, temporary storage, and transmission functions. The proxy service module collects its own static and dynamic information through the server's hardware and software interfaces, performs preprocessing such as deduplication and format standardization on the collected information, temporarily stores it in a local cache, and then transmits the information to the NFC hardware module via a serial communication interface to complete information binding and updating. Simultaneously, this module receives operation commands forwarded by the NFC hardware module, parses them, executes the corresponding predefined operations, and feeds back the operation results to the NFC hardware module.

[0134] The smart terminal features NFC communication capabilities and a built-in dedicated application. The NFC communication function establishes a contactless communication link with the NFC hardware module, enabling information reading and command transmission. The dedicated application supports information reading, command editing and sending, image capture, data reception, and collaborative display functions. It can read server information stored in the NFC hardware module, edit and send operation commands, capture server-related images and upload them to the cloud platform, receive value-added information and labeled recognition results returned by the cloud platform, and perform collaborative display according to association logic, providing users with an intuitive operation interface and information display window.

[0135] The cloud platform deploys a backend service cluster, a distributed database, and an object detection algorithm module. The backend service cluster receives requests from smart terminals, including requests for server unique identifiers and image uploads, processes and forwards these requests, and interacts with the distributed database to obtain value-added information about the server. The distributed database stores server-related data, including asset information, historical operational data, topology relationships, maintenance work order records, and device configuration parameters, supporting highly flexible queries and large-capacity storage. The object detection algorithm module preprocesses images uploaded from smart terminals, locates key components, identifies their status, and annotates them, generating labeled recognition results and returning them to the smart terminal.

[0136] The modules interact with each other through stable communication links. The NFC hardware module transmits data with the server via a serial communication interface, the NFC hardware module interacts with the smart terminal via NFC contactless communication, and the smart terminal transmits data with the cloud platform via the network. The data flow of the entire system is clear and orderly, forming a complete closed loop from server information collection and local interaction to cloud data retrieval, image analysis, and collaborative information display, ensuring the smooth implementation of each function.

[0137] The server information intelligent interaction method and system based on NFC technology described in this embodiment achieves several significant technical effects through a series of orderly technical steps and module collaboration. The information acquisition process is simple and efficient, eliminating the need for maintenance personnel to perform complex physical wiring or manual query operations. Static and dynamic information of the server can be quickly obtained simply by the close contact between the terminal and the NFC module, greatly simplifying the maintenance operation process and improving the efficiency of information acquisition.

[0138] The information has good real-time performance. The dynamic information of the server is continuously collected and synchronized to the NFC module through the agent service module. When the dynamic information changes, the update mechanism can be automatically triggered to ensure that the information read by the terminal is always consistent with the actual operating status of the server, avoiding operational and maintenance decision errors caused by information lag.

[0139] The data transmission and storage process is secure and reliable. Through a variety of security mechanisms such as asymmetric encryption algorithms, data integrity verification, and illegal request filtering, it provides comprehensive security protection for server unique identifiers, operation instructions, images, and other data, preventing data from being intercepted, tampered with, or leaked during transmission and storage, and ensuring the security of operation and maintenance.

[0140] With a high degree of intelligence, the system introduces target detection algorithms to automatically analyze and label relevant images of the server, enabling intelligent identification of the status of key components. This reduces the workload of manual visual inspection, lowers the technical threshold and human error in operation and maintenance, and improves the accuracy and efficiency of operation and maintenance work.

[0141] The system has good scalability and adaptability. Its modular design allows each functional module to be upgraded and expanded independently. It supports the addition of predefined operations and the optimization and updating of target detection algorithm models. It can be flexibly adjusted according to actual operation and maintenance needs and changes in server type to adapt to application needs of different scales and scenarios.

[0142] The information display is intuitive and clear. Through a collaborative display method that combines text and graphics, it organically integrates labeled images with static, dynamic, and value-added information of the server, realizing the linkage between visual and data information. This makes it easy for operation and maintenance personnel to quickly understand the server's operating status and provides comprehensive and intuitive data support for operation and maintenance decisions.

[0143] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A server information intelligent interaction method based on NFC technology, characterized in that, Includes the following steps: S1. Obtain static and dynamic information from the server, and write the static and dynamic information into the storage area of ​​the NFC module to complete information binding and updating; S2. Trigger the NFC module to read server information in the storage area, or send a command to the NFC module to trigger a predefined operation; S3. Send the server's unique identifier to the cloud platform, query the cloud platform's database, and receive the returned value-added information; S4. Take pictures of the server and upload them to the cloud platform. Analyze and process the pictures through the cloud platform, receive the analysis results and display them together with the read server information; Step S1 includes the following sub-steps: S1.

1. Continuously collect static and dynamic information of the server. Static information includes fixed attribute information, such as asset identifier, model and specifications, production batch and manufacturing date. Dynamic information includes hardware operating status, operating system parameters and resource usage performance data, such as CPU utilization, memory usage, remaining storage space and network transmission rate. S1.

2. After the static and dynamic information is collected, a stable data transmission link is established through the preset standard serial communication interface, and the collected static and dynamic information is completely written into the designated storage partition of the NFC module in the preset format. S1.

3. Write operations to the NFC module based on static and dynamic information to complete the two-way information binding between the server and the NFC module. When the dynamic information changes, the real-time update mechanism is automatically triggered to keep the dynamic information in the storage area synchronized with the actual operating status of the server. Step S3 includes the following sub-steps: S3.

1. The server's unique identifier, which is read, is encapsulated and sent to the preset cloud service platform through a secure encrypted transmission protocol. During the transmission process, an asymmetric encryption algorithm is used to encrypt and protect the data. S3.

2. After receiving the identifier, the cloud platform establishes a stable connection with the database through the backend service, performs an accurate retrieval based on the unique identifier, and filters the associated data corresponding to the server. S3.

3. Receive value-added information returned by the cloud platform. The value-added information includes historical server operation data, data center topology relationships, past maintenance work order records and equipment configuration parameters. After being sorted by data type, the information is transmitted to the terminal. Step S4 includes the following sub-steps: S4.

1. Take targeted photos of key areas or suspected faulty components on the front panel of the server, and adjust the shooting angle and focal length to ensure that the key components in the image are unobstructed and the clarity meets the requirements of algorithm analysis. S4.

2. Through a stable communication link between the terminal and the cloud platform, the captured images are uploaded to the image processing module of the cloud platform in a preset lossless file format; S4.

3. The cloud platform calls the preset target detection algorithm to perform real-time regional analysis of the image, and locates the specific location of key components through feature point extraction and matching; S4.

4. Identify the operating status of key components based on algorithm analysis results, determine whether there is any damage, abnormal indication, or looseness, and mark it accordingly; S4.

5. Receive the labeled recognition results returned by the cloud platform, and display the labeled recognition results in conjunction with the server information read in step S2 according to the device component association logic.

2. The method according to claim 1, characterized in that, Step S2 includes the following sub-steps: S2.

1. Connect the NFC-enabled terminal to the NFC module integrated in the server to trigger the contactless communication connection establishment process, and ensure the stability of the communication link through signal strength detection; S2.

2. Automatically read the pre-stored static information and updated dynamic information in the NFC module's storage area through the dedicated NFC communication channel, and perform CRC data integrity verification during transmission to prevent information loss or tampering; S2.

3. The terminal's built-in dedicated application edits the preset format operation instructions. The instructions are forwarded to the server's built-in agent service via the NFC module, triggering the server to execute predefined operations. The predefined operations include restarting the service, collecting operation logs, hardware self-testing, and parameter configuration querying.

3. The method according to claim 1, characterized in that, In step S1, the server constructs a continuous data collection mechanism through its built-in proxy service, periodically acquiring its own static and dynamic information according to preset collection rules. The static information includes the server's fixed attribute data, which includes asset identification, production specifications, factory parameters, and equipment number. The dynamic information includes hardware operating status parameters, operating system operating status data, and resource usage performance indicators, which include CPU, memory, storage, and network usage data. The collected information is first temporarily stored in a local cache for deduplication and format standardization preprocessing, and then transmitted to the NFC module through a designated channel.

4. The method according to claim 1, characterized in that, In step S3, the cloud platform builds a backend API service based on a high-performance web framework and a dedicated runtime environment. After receiving the server's unique identifier, the backend API service first performs format validation and legality verification on the identifier, and then calls the database interface according to the preset query logic. The database adopts a distributed database type that supports highly flexible queries and large-capacity storage, and quickly retrieves relevant data associated with the server's unique identifier. The relevant data includes historical data, topology relationships, and configuration parameters, and the relevant data is organized into a standardized format and returned.

5. The method according to claim 1, characterized in that, In step S3, all functional service components of the cloud platform are uniformly packaged and deployed using containerization technology. Each functional module runs independently in a dedicated container. Container orchestration tools are used to achieve collaborative scheduling between modules, ensuring operational consistency in different deployment environments. Reverse proxy tools are used to receive requests sent by terminals, and to perform protocol conversion, forwarding, illegal request filtering, and data integrity and security verification on the requests. At the same time, load balancing strategies are configured to dynamically allocate request traffic based on the real-time load of each backend service node.

6. The method according to claim 1, characterized in that, In step S4.3, the target detection algorithm first performs preprocessing operations on the uploaded image to optimize image quality. The preprocessing operations include noise reduction, contrast enhancement, and edge sharpening. Then, the image is analyzed in real time by region using a preset feature model to automatically match and identify key components of the server. Key components include hard drive indicator lights, power buttons, status display panels, interface areas, and fan operation indicator lights. Status recognition marks normal operation status and abnormal prompt status based on the color, flashing frequency, shape, and brightness change characteristics of the components, and records the coordinate information and feature description of the abnormal area.

7. A server information intelligent interaction system based on NFC technology, characterized in that, Includes NFC hardware module, server body, smart terminal and cloud service platform; The NFC hardware module is integrated in a modular form inside or outside the server chassis. It integrates an NFC chip, a signal transmission antenna, a microcontroller, and a standard serial communication interface. It is used to store static and dynamic information of the server and to realize two-way data interaction with smart terminals. The dynamic information includes hardware operating status, operating system parameters, and resource usage performance data. The resource usage performance data includes CPU utilization, memory usage, remaining storage space, and network transmission rate. The server has a built-in proxy service module, which has data collection, processing, temporary storage and transmission functions. It is used to continuously collect its own static and dynamic information and synchronize it to the NFC module. The smart terminal has NFC communication capabilities and a built-in dedicated application. The application supports information reading, command editing and sending, image capture, data reception, and collaborative display functions. It is used to read information stored in the NFC hardware module, send operation commands to the NFC module, and capture images related to the server. It continuously collects static and dynamic information from the server. Static information includes fixed attribute information, such as asset identification, model specifications, production batch, and manufacturing date. After the static and dynamic information is collected, a stable data transmission link is established through a preset standard serial communication interface. The collected static and dynamic information is then completely written into the designated storage partition of the NFC module according to a preset format. Based on the write operation of static and dynamic information to the NFC module, a two-way information binding between the server and the NFC module is completed. When the dynamic information changes, a real-time update mechanism is automatically triggered to keep the dynamic information in the storage area synchronized with the actual operating status of the server. The NFC-enabled terminal is attached to the NFC module integrated in the server to trigger the contactless communication connection establishment process, and the stability of the communication link is ensured by signal strength detection. The system automatically reads the pre-stored static information and updated dynamic information in the NFC module's storage area through the dedicated NFC communication channel. During transmission, CRC data integrity verification is performed to prevent information loss or tampering. The system also allows users to edit operation commands in a preset format through a dedicated application built into the terminal. These commands are forwarded to the server's built-in agent service via the NFC module, triggering the server to execute predefined operations, including restarting the service, collecting operation logs, hardware self-testing, and parameter configuration querying. The unique identifier of the server, obtained through a secure encrypted transmission protocol, is encapsulated and sent to the preset cloud service platform. During transmission, an asymmetric encryption algorithm is used to encrypt and protect the data. After receiving the identifier, the cloud platform establishes a stable connection with the database through backend services, performs accurate retrieval based on the unique identifier, and filters the associated data corresponding to the server. The cloud platform also receives value-added information, including historical server operation data, data center topology relationships, past maintenance work order records, and equipment configuration parameters, which are then categorized and transmitted to the terminal according to data type. Targeted photography is taken of key areas or suspected faulty components on the server's front panel. The shooting angle and focal length are adjusted to ensure that the key components in the image are unobstructed and the clarity meets the requirements of the algorithm analysis. The captured images are uploaded to the cloud platform's image processing module in a preset lossless file format through a stable communication link between the terminal and the cloud platform. The cloud platform calls a preset target detection algorithm to perform real-time regional analysis of the images, and locates the specific positions of key components through feature point extraction and matching. Based on the algorithm analysis results, the operating status of key components is identified, and it is determined whether there is any damage, abnormal indication, or looseness, and these are marked. The marked identification results returned by the cloud platform are received, and the marked identification results are displayed in conjunction with the server information read in step S2 according to the device component association logic. The cloud service platform deploys a backend service cluster, a distributed database, and a target detection algorithm module. The backend service cluster is responsible for receiving, processing, and forwarding requests. The distributed database is used to store server-related data, including asset information, historical operation data, topology relationships, maintenance work order records, and equipment configuration parameters. The target detection algorithm module is used to analyze and process uploaded images, thus realizing complete functions of data query, image analysis, and result feedback.

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