Building engineering data information intelligent management platform

Abstract

The invention provides a building engineering data information intelligent management platform which comprises an intelligent sensing module, an edge calculation module, a data management module, an AI decision module, a business application module and a safety standard module. Through the intelligent sensing module, the edge calculation module, the data management module, the AI decision module, the service application module and the safety standard module, the position of a constructor and the equipment state can be tracked in real time, personnel are prevented from entering a dangerous area by mistake and the mechanical overload risk is prevented, operation safety is guaranteed, AI quality inspection and fault diagnosis are locally processed, cloud dependence is reduced, and the working efficiency is improved. According to the method, the system and the device, real-time early warning of potential safety hazards can still be ensured when the network is interrupted, BIM, IoT and service data can be integrated in a standardized manner, information islands are eliminated, and cross-stage quality tracing and responsibility definition are realized.

Description

Technical Field

[0001] The present invention relates to the field of construction engineering management platforms, and in particular to an intelligent management platform for construction engineering data information. Background Art

[0002] Due to the continuous improvement of the construction industry's demand for high efficiency, environmental protection, and safety, and with the acceleration of urbanization, issues such as building energy consumption, safety management, and operational efficiency have become increasingly prominent. Intelligent construction management, through the introduction of modern information technology, communication technology, automatic control technology, computer technology, etc., can achieve real-time collection, processing, and analysis of various types of information on the construction site, thereby improving construction efficiency, reducing costs, and improving building quality. At the same time, national policy support, market demand drive, and technological innovation have jointly made intelligent construction management a new trend in the development of the industry. The widespread application of new-generation information technologies such as big data technology, cloud computing, and the Internet of Things in the field of construction engineering has provided a solid technical foundation for the implementation of intelligent management solutions;

[0003] Existing intelligent management platforms for construction project data and information generally have core defects such as serious data silos and low collaborative efficiency. The BIM, ERP, progress management and other systems used by different participants are not unified in data formats and interface standards, resulting in the inability to automatically connect design models and construction data. Manual conversion is required and has an error rate as high as 15%-20%. For example, component properties are often lost when Revit models are imported into construction quantity calculation software. Personnel safety management relies on low-precision GPS positioning (error > 5 meters) and regular inspections, making it impossible to monitor personnel movements in high-risk areas in real time. Fatigue and illegal operations are difficult to intervene promptly, and accident warnings are highly delayed. Quality control is limited to spot checks and paper reports. AI visual inspection capabilities are lacking. The acceptance process for hidden projects lacks reliable evidence, resulting in a high risk of tampering and a long dispute resolution cycle. Progress management relies on manual daily reporting, with data updates delayed by over 48 hours. Resource conflicts and schedule deviations are often discovered after the fact, exacerbating delay losses. Equipment operation and maintenance relies on regular inspections, with an average response time of 72 hours. Sudden downtime leads to cascading delays. Material management relies on manual records, lacking batch tracking, making it difficult to trace overconsumption and shoddy workmanship, and resulting in a waste rate generally exceeding 5%. Carbon emissions accounting relies on empirical formulas with errors exceeding 20%, making it difficult to accurately guide emissions reductions. System security is weak, static password authentication is easily cracked, and there is a high risk of design drawings and engineering data being leaked. Tamper-proof mechanisms such as blockchain are also lacking. The platform's poor scalability and closed architecture make it difficult to integrate new technologies (such as digital twins). High software and hardware costs and training barriers hinder adoption by small and medium-sized enterprises, creating an unbalanced market where leading enterprises specialize in the market and the long-tail market is left blank. These issues collectively lead to extensive management, resource waste, and quality risks, severely hindering the industry's digital transformation. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In response to the shortcomings of the existing technology, the present invention provides an intelligent management platform for construction project data information, which solves the core defects of the existing intelligent management platform for construction project data information, such as serious data silos and low collaboration efficiency.

[0006] (2) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent management platform for construction engineering data information, including an intelligent sensing module, an edge computing module, a data governance module, an AI decision module, a business application module, and a safety standard module;

[0008] The intelligent sensing collects personnel location, equipment status and environmental data in real time through intelligent terminals and sensors, builds a digital perception network for the entire construction site, and eliminates blind spots in manual inspections;

[0009] The edge computing module performs data cleaning, lightweight AI reasoning, and priority transmission locally on the construction site, reducing cloud load and ensuring real-time response capabilities in weak network environments.

[0010] The data governance module standardizes multi-source heterogeneous data and combines it with blockchain to achieve quality traceability and cross-stage data connectivity, breaking down information silos.

[0011] The AI decision-making module dynamically optimizes schedule planning, resource scheduling, and carbon emission paths based on machine learning and operations research models, upgrading empirical decision-making to data-driven intelligence.

[0012] The business application module uses digital twin visualization and AR mobile terminals to achieve a closed business loop from risk warning to rectification execution, improving on-site collaboration efficiency;

[0013] The security standard module adopts zero-trust architecture and national encryption algorithm to ensure data security, is compatible with industry standards and government regulatory interfaces, and ensures platform compliance and ecological openness.

[0014] Preferably, the intelligent sensing module includes a personnel safety monitoring unit, a project quality monitoring unit and a progress tracking unit;

[0015] The personnel safety monitoring unit uses a smart safety helmet: integrated UWB positioning, heart rate monitoring, posture sensor and electronic work badge: it records working hours and area permissions, can monitor personnel positions in real time, automatically sound and light alarms when entering dangerous areas, and triggers forced rest reminders when working continuously for more than 8 hours, thereby reducing the risk of fatigue work.

[0016] Preferably, the project quality monitoring unit includes an AI visual camera: equipped with an EdgeTPU chip, supporting concrete crack and steel bar spacing detection, and a wireless stress sensor: embedded in key structures, monitoring load changes in real time, and automatically comparing construction results with BIM model deviations, issuing alarms when exceeding thresholds, and recording the entire hidden construction process and uploading it to the blockchain for evidence storage;

[0017] The progress tracking unit includes a drone inspection system: daily automatic patrol, generating point cloud models through lidar, and IoT progress beacons: RFID tags are deployed at key nodes to automatically record completion time, which can replace manual daily reports, generate three-dimensional progress heat maps in real time, dynamically calculate the remaining construction period, and trigger early warnings when the deviation exceeds 5%.

[0018] Preferably, the edge computing module device includes an industrial-grade edge server with a built-in lightweight model: a safety helmet / reflective clothing recognition model and an equipment vibration spectrum analysis model. It can still perform safety monitoring and equipment diagnosis locally when the network is interrupted, and key data is uploaded first, reducing bandwidth usage by 70%.

[0019] Preferably, the data governance module crosses the system data middle platform unit and the blockchain evidence storage unit;

[0020] The cross-system data middle platform includes an IFC standardization engine: it converts design BIM, construction logs, and sensor data into the ISO 19650 standard format, and a spatiotemporal database: it stores data according to the three-dimensional index of "time-space-responsible person", supports retrieval in seconds, and realizes automatic synchronization of design changes to the construction and operation and maintenance stages, reducing information gaps by 90%. When tracing quality, the full life cycle data of any component can be retrieved within 10 seconds.

[0021] Preferably, the blockchain evidence storage unit builds a private chain based on Hyperledger Fabric, stores key processes, and automatically verifies data integrity through smart contracts, shortening the quality dispute processing cycle from 30 days to 3 days. It is directly connected to government regulatory data and increases the acceptance pass rate by 25%.

[0022] Preferably, the AI decision-making module includes a schedule risk prediction unit, a material dynamic management unit, and a carbon accounting and optimization unit;

[0023] The progress risk prediction unit supports multi-scenario deduction and recommends the optimal construction plan through historical progress data + real-time resources + external factors and Transformer timing model + Monte Carlo simulation;

[0024] The dynamic material management unit uses RFID tags to bind steel bar / concrete batches, automatically writes off usage, and combines it with the BIM quantity calculation model to dynamically calculate the loss rate and optimize procurement plans. This has reduced the steel waste rate from 6% to 1.5%, increased inventory turnover by 40%, and reduced capital occupation.

[0025] The carbon accounting and optimization unit automatically generates a carbon emission report based on the AI carbon footprint model of LCA through equipment energy consumption, transportation distance, material carbon factor, etc., with an error rate of ≤5%, in compliance with ISO 14064 standards, and recommends low-carbon processes.

[0026] Preferably, the business application module digital twin command cabin and mobile collaborative terminal;

[0027] The data twin command cabin can visualize the real-time status of personnel, machinery, and materials in three dimensions, simulate the impact of extreme weather on progress, and rehearse response plans;

[0028] The mobile collaborative terminal uses an explosion-proof industrial tablet and AR glasses. Workers receive masonry instructions through the AR glasses. When equipment fails, engineers scan the code to retrieve the maintenance manual and call for spare parts.

[0029] Preferably,

[0030] Working Principle: The security standard module includes a zero-trust security system and a standard-compliant interface;

[0031] The zero-trust security system uses dynamic access control, the national secret SM9 algorithm to encrypt core data, and quantum key distribution to prevent cracking;

[0032] The standard-compatible interface supports docking with the government regulatory platform to automatically upload quality acceptance data, and opens the API for third-party system calls.

[0033] (3) Beneficial effects

[0034] The present invention provides an intelligent management platform for construction engineering data information.

[0035] Beneficial effects:

[0036] 1. Through the intelligent sensing module, edge computing module, data governance module, AI decision-making module, business application module, and safety standard module, this invention can track the location of construction workers and equipment status in real time, prevent personnel from accidentally entering dangerous areas and the risk of machinery overloading, and ensure operational safety. It also locally processes AI quality inspection and fault diagnosis, reducing cloud dependence and ensuring real-time warning of safety hazards even when the network is interrupted. At the same time, it can standardize and integrate BIM, IoT, and business data, eliminating information silos and achieving cross-stage quality traceability and responsibility definition.

[0037] 2. The present invention can analyze the relationship between labor efficiency, materials and progress, accurately predict construction period deviations and recommend optimization plans, reduce resource waste, and use digital twins and AR to guide construction, intuitively locate problem points, and improve the first-time acceptance rate of complex processes. The blockchain evidence storage is combined with national secret encryption to ensure that data cannot be tampered with, meeting government supervision and legal compliance requirements. Through six major innovations of full-domain perception, edge intelligence, data integration, AI optimization, virtual-reality collaboration, and security and trustworthiness, the platform achieves a coordinated improvement in construction efficiency, quality, and safety, forming an intelligent management system from risk warning to closed-loop rectification, and promoting the transformation of the construction industry from extensive management to refined and low-carbon management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is an overall flow chart of an intelligent management platform for construction engineering data information proposed by the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0040] Example:

[0041] like Figure 1 As shown, an embodiment of the present invention provides an intelligent management platform for construction engineering data information, characterized by including an intelligent sensing module, an edge computing module, a data governance module, an AI decision module, a business application module, and a security standard module;

[0042] Intelligent sensing uses smart terminals and sensors to collect real-time data on personnel location, equipment status, and environment, building a digital perception network across the construction site and eliminating blind spots in manual inspections.

[0043] The edge computing module performs data cleaning, lightweight AI inference, and priority transmission locally on the construction site, reducing cloud load and ensuring real-time response capabilities in weak network environments.

[0044] The data governance module standardizes multi-source heterogeneous data and combines it with blockchain to achieve quality traceability and cross-stage data connectivity, breaking down information silos.

[0045] The AI decision-making module is based on machine learning and operations research models to dynamically optimize schedules, resource scheduling, and carbon emission paths, upgrading empirical decision-making to data-driven intelligence.

[0046] The business application module uses digital twin visualization and AR mobile terminals to achieve a closed business loop from risk warning to rectification execution, improving on-site collaboration efficiency;

[0047] The security standard module adopts zero-trust architecture and national encryption algorithms to ensure data security, is compatible with industry standards and government regulatory interfaces, and ensures platform compliance and ecological openness.

[0048] The intelligent sensing module includes a personnel safety monitoring unit, a project quality monitoring unit and a progress tracking unit.

[0049] The personnel safety monitoring unit uses a smart helmet that integrates UWB positioning, heart rate monitoring, posture sensors, and electronic work badges. It records working hours and area permissions, can monitor personnel locations in real time, automatically generates sound and light alarms when entering dangerous areas, and triggers mandatory rest reminders when working continuously for more than 8 hours, reducing the risk of fatigue.

[0050] UWB positioning system: Using the Decawave DW3000 chip, positioning base stations are deployed every 100 meters on the construction site. TDOA (Time Difference of Arrival) algorithms achieve ±10cm positioning accuracy, and the electronic fence dynamically adjusts its range (for example, the lifting area radius automatically expands to 20 meters).

[0051] Vital sign monitoring bracelet: Integrates MAX30102 optical sensor (heart rate / blood oxygen) + MPU6050 six-axis gyroscope (posture monitoring), data is uploaded to the edge node every 5 seconds, and a vibration reminder is triggered if standing continuously for more than 4 hours.

[0052] The project quality monitoring unit includes an AI visual camera equipped with an EdgeTPU chip that supports concrete crack and rebar spacing detection, as well as a wireless stress sensor embedded in key structures to monitor load changes in real time. It can automatically compare construction results with BIM model deviations, issue alarms when thresholds are exceeded, and record the entire hidden construction process for blockchain storage.

[0053] The progress tracking unit includes a drone inspection system that automatically patrols daily and generates point cloud models using LiDAR, as well as IoT progress beacons: RFID tags are deployed at key nodes to automatically record completion times, replacing manual daily reports. It also generates a real-time 3D progress heat map, dynamically calculates the remaining construction period, and triggers warnings when deviations exceed 5%.

[0054] AI camera: Hikvision DeepinView series, equipped with Horizon Rising Sun X3 chip, supports 20 types of safety violation identification (such as not wearing a seat belt, unprotected edges), and has a night infrared mode recognition rate of ≥95%.

[0055] Vibration sensor: PCB Piezotronics 356A32, attached to key parts of the tower crane, monitoring frequency range 5Hz-10kHz, abnormal vibration (such as loose bolts) triggers a three-level warning (yellow / orange / red).

[0056] The edge computing module equipment includes an industrial-grade edge server with built-in lightweight models: a safety helmet / reflective clothing recognition model and an equipment vibration spectrum analysis model. It can still perform local safety monitoring and equipment diagnosis during network interruptions, prioritize uploading of critical data, and reduce bandwidth usage by 70%. The network disconnection emergency mechanism: data caching: Redis streaming storage is used to save 72 hours of data (including video stream compression encoding H.265) during network disconnection, and differential synchronization is performed after the network is restored. The edge server: NVIDIA Jetson AGX Orin (32GB video memory), deploying a lightweight YOLOv8-seg model (safety detection) + 1D-CNN (equipment fault diagnosis), with inference latency ≤ 50ms; communication networking: 5G+LoRa hybrid networking is adopted, the Huawei MH5000 module supports SA / NSA dual-mode, the LoRa gateway (Semtech SX1302) has a coverage radius of 3km, and the packet loss rate in the tunnel is less than 1%.

[0057] Offline AI model: in TensorFlow Lite format, supporting the continuous operation of 10 core functions such as helmet detection and crack recognition;

[0058] The data governance module crosses the system data middle-office unit and the blockchain evidence storage unit, and the standardization engine is as follows: IFC conversion: based on the IfcOpenShell open source library, it realizes lossless conversion of Revit models to IFC4Add2 standards, and supports custom attribute extensions (such as adding a "construction responsible person" field); spatiotemporal database: TimescaleDB (PostgreSQL extension) stores time series data (such as sensor readings), PostGIS manages spatial data (BIM component coordinates), and the query response time is less than 1 second; blockchain evidence storage: node architecture: using Hyperledger Fabric2.4, setting up 4 Orderer nodes (Kafka consensus) + 8 Peer nodes (belonging to construction / construction / supervision parties), with a throughput of ≥500TPS.

[0059] Evidence content: 360° panoramic images of key processes (such as waterproof and water-tightness tests) + temperature and humidity sensor data, hash values are uploaded to the chain, and the original files can be restored through a dedicated decoder during judicial evidence collection.

[0060] The cross-system data middle platform includes an IFC standardization engine: it converts design BIM, construction logs, and sensor data into the ISO 19650 standard format, and a spatiotemporal database: it stores data according to the three-dimensional index of "time-space-responsible person", supports retrieval in seconds, and realizes automatic synchronization of design changes to the construction and operation and maintenance stages, reducing information gaps by 90%. When tracing quality, the full life cycle data of any component can be retrieved within 10 seconds.

[0061] The blockchain evidence storage unit builds a private chain based on Hyperledger Fabric to store key processes. Smart contracts automatically verify data integrity, shortening the quality dispute processing cycle from 30 days to 3 days. It is directly connected to government regulatory data and increases the acceptance pass rate by 25%.

[0062] The AI decision-making module includes a schedule risk prediction unit, a material dynamic management unit, and a carbon accounting and optimization unit;

[0063] The schedule risk prediction unit uses historical schedule data, real-time resources, external factors, Transformer timing model, and Monte Carlo simulation to support multi-scenario deduction and recommend the optimal construction plan.

[0064] The dynamic material management unit uses RFID tags to bind steel bar / concrete batches, automatically writes off usage, and combines this with the BIM quantity calculation model to dynamically calculate loss rates and optimize procurement plans. This has reduced steel waste rates from 6% to 1.5%, increased inventory turnover by 40%, and reduced capital occupation.

[0065] The carbon accounting and optimization unit uses LCA-based AI carbon footprint model to automatically generate carbon emission reports with an error rate of ≤5% based on equipment energy consumption, transportation distance, material carbon factor, etc., in compliance with ISO 14064 standards, and recommends low-carbon processes.

[0066] Business application module digital twin command cabin and mobile collaborative terminal;

[0067] The data twin command cabin can visualize the real-time status of personnel, machinery, and materials in three dimensions, simulate the impact of extreme weather on progress, and rehearse response plans;

[0068] The mobile collaborative terminal uses explosion-proof industrial tablets and AR glasses. Workers receive masonry instructions through AR glasses. When equipment fails, engineers scan the code to retrieve the maintenance manual and call for spare parts.

[0069] The security standard module includes a zero-trust security system and a standard-compliant interface;

[0070] The zero-trust security system uses dynamic access control, the national secret SM9 algorithm to encrypt core data, and quantum key distribution to prevent cracking;

[0071] The standard-compatible interface supports automatic uploading of quality acceptance data to the government regulatory platform, and opens the API for third-party system calls. The data interface complies with the "Building Information Model Data Storage Standard" (JGJ / T 448-2022), provides a RESTful API (Swagger document), and supports third-party systems (such as UFIDA ERP) to call material inventory data; Compliance audit: The built-in log audit module (ELK Stack) automatically generates reports that meet the Level 3 requirements of Information Security Technology 2.0, and supports one-click export for regulatory review.

[0072] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent management platform for construction engineering data information, characterized by: Including intelligent sensing module, edge computing module, data governance module, AI decision module, business application module and security standard module; The intelligent sensing collects personnel location, equipment status and environmental data in real time through intelligent terminals and sensors, builds a digital perception network for the entire construction site, and eliminates blind spots in manual inspections; The edge computing module performs data cleaning, lightweight AI reasoning, and priority transmission locally on the construction site, reducing cloud load and ensuring real-time response capabilities in weak network environments. The data governance module standardizes multi-source heterogeneous data and combines it with blockchain to achieve quality traceability and cross-stage data connectivity, breaking down information silos. The AI decision-making module dynamically optimizes schedule planning, resource scheduling, and carbon emission paths based on machine learning and operations research models, upgrading empirical decision-making to data-driven intelligence. The business application module uses digital twin visualization and AR mobile terminals to achieve a closed business loop from risk warning to rectification execution, improving on-site collaboration efficiency; The security standard module adopts zero-trust architecture and national encryption algorithm to ensure data security, is compatible with industry standards and government regulatory interfaces, and ensures platform compliance and ecological openness.

2. The intelligent management platform for construction engineering data information according to claim 1, characterized in that: The intelligent sensing module includes a personnel safety monitoring unit, a project quality monitoring unit and a progress tracking unit; The personnel safety monitoring unit uses a smart safety helmet: integrated UWB positioning, heart rate monitoring, posture sensor and electronic work badge: it records working hours and area permissions, can monitor personnel positions in real time, automatically sound and light alarms when entering dangerous areas, and triggers forced rest reminders when working continuously for more than 8 hours, thereby reducing the risk of fatigue work.

3. The intelligent management platform for construction engineering data information according to claim 2, characterized in that: The project quality monitoring unit includes an AI visual camera equipped with an EdgeTPU chip that supports concrete crack and rebar spacing detection, as well as wireless stress sensors embedded in key structures to monitor load changes in real time. It can automatically compare construction results with BIM model deviations, issue alarms when thresholds are exceeded, and record the entire construction process of concealed projects and store them on the blockchain. The progress tracking unit includes a drone inspection system: daily automatic patrol, generating point cloud models through lidar, and IoT progress beacons: RFID tags are deployed at key nodes to automatically record completion time, which can replace manual daily reports, generate three-dimensional progress heat maps in real time, dynamically calculate the remaining construction period, and trigger early warnings when the deviation exceeds 5%.

4. The intelligent management platform for construction engineering data information according to claim 1, characterized in that: The edge computing module device includes an industrial-grade edge server with built-in lightweight models: a safety helmet / reflective clothing recognition model and an equipment vibration spectrum analysis model. It can still perform local safety monitoring and equipment diagnosis when the network is interrupted, and key data is uploaded first, reducing bandwidth usage by 70%.

5. The intelligent management platform for construction engineering data information according to claim 1 is characterized by: The data governance module crosses the system data middle platform unit and the blockchain evidence storage unit; The cross-system data middle platform includes an IFC standardization engine: it converts design BIM, construction logs, and sensor data into the ISO 19650 standard format, and a spatiotemporal database: it stores data according to the three-dimensional index of "time-space-responsible person", supports retrieval in seconds, and realizes automatic synchronization of design changes to the construction and operation and maintenance stages, reducing information gaps by 90%. When tracing quality, the full life cycle data of any component can be retrieved within 10 seconds.

6. The intelligent management platform for construction engineering data information according to claim 5, characterized in that: The blockchain evidence storage unit builds a private chain based on Hyperledger Fabric to store key processes, and the smart contract automatically verifies data integrity, shortening the quality dispute processing cycle from 30 days to 3 days. It directly connects to government regulatory data and increases the acceptance pass rate by 25%.

7. The intelligent management platform for construction engineering data information according to claim 1, characterized in that: The AI decision-making module includes a schedule risk prediction unit, a material dynamic management unit, and a carbon accounting and optimization unit; The progress risk prediction unit supports multi-scenario deduction and recommends the optimal construction plan through historical progress data + real-time resources + external factors and Transformer timing model + Monte Carlo simulation; The dynamic material management unit uses RFID tags to bind steel bar / concrete batches, automatically writes off usage, and combines it with the BIM quantity calculation model to dynamically calculate the loss rate and optimize procurement plans. This has reduced the steel waste rate from 6% to 1.5%, increased inventory turnover by 40%, and reduced capital occupation. The carbon accounting and optimization unit automatically generates a carbon emission report based on the AI carbon footprint model of LCA through equipment energy consumption, transportation distance, material carbon factor, etc., with an error rate of ≤5%, in compliance with ISO 14064 standards, and recommends low-carbon processes.

8. The intelligent management platform for construction engineering data information according to claim 1, characterized in that: The business application module digital twin command cabin and mobile collaborative terminal; The data twin command cabin can visualize the real-time status of personnel, machinery, and materials in three dimensions, simulate the impact of extreme weather on progress, and rehearse response plans; The mobile collaborative terminal uses an explosion-proof industrial tablet and AR glasses. Workers receive masonry instructions through the AR glasses. When equipment fails, engineers scan the code to retrieve the maintenance manual and call for spare parts.

9. The intelligent management platform for construction engineering data information according to claim 1, characterized in that: The security standard module includes a zero-trust security system and a standard-compatible interface; The zero-trust security system uses dynamic access control, the national secret SM9 algorithm to encrypt core data, and quantum key distribution to prevent cracking; The standard-compatible interface supports docking with the government regulatory platform to automatically upload quality acceptance data, and opens the API for third-party system calls.

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