Digital twin three-dimensional visual material management system for traffic engineering construction

Abstract

The invention provides a digital twin three-dimensional visual material management system for traffic engineering construction, and relates to the technical field of traffic engineering construction. The traffic engineering construction digital twin three-dimensional visual material management system comprises a data acquisition layer which is connected with a data transmission layer. According to the system, real-time data acquisition and processing are realized through the sensor and the Internet of Things equipment, the material state can be updated in real time, the AI prediction function of the system can make accurate demand prediction according to historical data and real-time data, the material management process, the digital twin technology and the three-dimensional visual model are optimized, and the material management efficiency is improved. A visual monitoring interface is provided for a manager, human intervention is reduced due to the high-automation design of the system, the management efficiency and accuracy are improved, and the system is superior to an existing material management technology in the aspects of real-time performance, intelligence, visualization, automation and system integration. And complex requirements in traffic engineering construction can be better met.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic engineering construction, and in particular to a digital twin three-dimensional visualized material management system for traffic engineering construction. Background Art

[0002] Transportation engineering construction refers to a series of engineering activities carried out to build, maintain and improve transportation infrastructure. The objects of transportation engineering construction include but are not limited to highways, railways, bridges, tunnels, airports, ports and urban roads. This type of construction usually involves complex planning, design, construction and management processes, aiming to improve the safety, efficiency and sustainability of transportation systems. Transportation engineering construction is usually large-scale and involves a large amount of materials and equipment. Effective material management can ensure that the required materials are in place in time and avoid construction delays caused by material shortages. Materials account for a large part of the cost of transportation engineering construction. Through accurate material management, waste can be reduced, procurement and inventory strategies can be optimized, and overall construction costs can be reduced. Reasonable material management can ensure the use of qualified materials and avoid affecting the quality of the project due to material problems, thereby improving the service life and safety of transportation facilities. Through effective management, avoiding over-purchasing and waste can help reduce the impact on the environment and promote sustainable construction.

[0003] Traditional transportation engineering construction material management usually relies on manual records, paper documents and spreadsheets. This method is more common in small-scale projects, but there are problems such as data error, poor real-time performance and low management efficiency. Some large projects use ERP (Enterprise Resource Planning) systems for material management, and use ERP's inventory management, procurement management and other modules to coordinate the purchase, storage and use of materials. This method improves management efficiency, but usually lacks the ability to capture and dynamically adjust real-time data on site. Some projects use RFID or barcode technology to identify and track materials, which improves the accuracy and efficiency of material management. However, this technology still relies on manual scanning in actual applications and lacks the ability to integrate with other construction data.

[0004] Therefore, the present invention proposes a digital twin three-dimensional visualization material management system for traffic engineering construction to solve the above-mentioned problems. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a digital twin three-dimensional visualization material management system for traffic engineering construction, which solves the problem of low efficiency of existing management technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A digital twin three-dimensional visualization material management system for traffic engineering construction, comprising a data acquisition layer, the data acquisition layer is connected to a data transmission layer, the data transmission layer is connected to a data processing and storage layer, the data processing and storage layer is connected to an application layer, and the application layer is connected to a user interface layer;

[0007] The data collection layer includes field sensors, RFID / Barcode scanning equipment, drones and ground-based laser radars, surveillance cameras and other video equipment; the data transmission layer includes IoT gateways, wireless transmission networks, and edge computing equipment; the data processing and storage layer includes real-time data processing platforms, distributed databases and cloud storage, data analysis, and AI model training;

[0008] The application layer includes a dynamic digital twin model system, an intelligent material management engine, a panoramic visualization and collaboration platform, an intelligent decision-making and prediction module, and an IoT-driven automated process management; the user interface layer includes a Web user interface, a mobile application, and an API interface.

[0009] Preferably, the on-site sensors include temperature sensors, humidity sensors, displacement sensors, and vibration sensors; the RFID / Barcode scanning equipment is used for material tracking and management, and collects material entry and exit, inventory, and location data; the drone and ground lidar are used for on-site imaging and laser scanning to obtain three-dimensional model data; the surveillance cameras and other video equipment are used for on-site real-time video monitoring.

[0010] Preferably, the IoT gateway is used to collect field sensor data and transmit it to the data center through the standardized protocol MQTT. The wireless transmission network includes Wi-Fi, LoRa, and 5G technologies. The edge computing device performs local pre-processing on part of the data to reduce transmission delays and central computing pressure.

[0011] Preferably, the real-time data processing platform adopts the big data technology platform Apache Kafka for data stream processing, the distributed database and cloud storage use Hadoop, NoSQL database MongoDB, and Cassandra to store construction data and material data, and the data analysis and AI model training use the big data platform Hadoop for data analysis and AI model training.

[0012] Preferably, the dynamic digital twin model system is a three-dimensional digital twin model that builds and updates the construction site in real time, the intelligent material management engine is AI-based material demand forecasting, adaptive supply chain management, and intelligent warehousing and inventory management, the panoramic visualization and collaboration platform is a platform for high-fidelity three-dimensional visualization, multi-user real-time collaboration, mobile terminals, and remote access, the intelligent decision-making and prediction module is data-driven decision support, risk prediction and emergency plans, automated scheduling and resource optimization, and the IoT-driven automated process management is full-process automated monitoring and management, intelligent scheduling of equipment and personnel, and energy efficiency and environmental protection management.

[0013] Preferably, the Web user interface is a user interface based on the modern Web technology React, the mobile application is a cross-platform mobile application based on React Native, and the API interface is an open standardized API interface.

[0014] The present invention provides a digital twin three-dimensional visualization material management system for traffic engineering construction. It has the following beneficial effects:

[0015] The present invention provides a digital twin 3D visualization material management system for traffic engineering construction. The management system of the present invention collects data from the construction site in real time through sensors, RFID, and drone equipment, and combines big data processing and AI technology to timely and accurately reflect the usage of materials and construction progress. This real-time nature helps to quickly respond to changes and problems in construction and improve overall construction efficiency. The system uses digital twin technology to build and update the 3D model of the construction site in real time, allowing managers to monitor the construction progress and material status in an intuitive way. This visualization capability greatly improves the accuracy and efficiency of decision-making. The system of the present invention uses AI technology to predict the demand for materials, and combines historical data and real-time data to optimize Intelligent material supply chain management, this intelligent material management not only reduces material waste, but also reduces costs and improves construction progress. The present invention uses the Internet of Things and automated process management, and the system can greatly reduce manual intervention and automatically complete data collection, analysis and material scheduling. This automation reduces manual errors and improves management efficiency. The system of the present invention is designed with a standardized API interface, supports integration with existing ERP, SCM and other systems, and has good scalability. New functional modules can be added or existing functions can be expanded as needed. The system of the present invention supports Web and mobile access, and managers can obtain information on the construction site anytime and anywhere, and perform operations, which increases the flexibility and availability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the system architecture flow of the present invention.

[0017] Among them, 1. Data acquisition layer; 2. Data transmission layer; 3. Data processing and storage layer; 4. Application layer; 5. User interface layer. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0019] like Figure 1 , an embodiment of the present invention provides a digital twin three-dimensional visualization material management system for traffic engineering construction, including a data acquisition layer 1, the data acquisition layer 1 is connected to a data transmission layer 2, the data transmission layer 2 is connected to a data processing and storage layer 3, the data processing and storage layer 3 is connected to an application layer 4, and the application layer 4 is connected to a user interface layer 5;

[0020] Data collection layer 1 includes field sensors, RFID / Barcode scanning equipment, drones and ground lidar, surveillance cameras and other video equipment. Data transmission layer 2 includes IoT gateways, wireless transmission networks, and edge computing devices. Data processing and storage layer 3 includes real-time data processing platforms, distributed databases and cloud storage, data analysis, and AI model training.

[0021] The application layer 4 includes a dynamic digital twin model system, an intelligent material management engine, a panoramic visualization and collaboration platform, an intelligent decision-making and prediction module, and IoT-driven automated process management. The user interface layer 5 includes a web user interface, mobile applications, and an API interface.

[0022] On-site sensors include temperature sensors, humidity sensors, displacement sensors, and vibration sensors, which collect real-time environmental and structural status data of the construction site. RFID / Barcode scanning equipment is used for material tracking and management, collecting material entry and exit, inventory, and location data. UAVs and ground-based lidars are used for on-site imaging and laser scanning to obtain three-dimensional model data. Surveillance cameras and other video equipment are used for real-time on-site video monitoring to support visualization of the construction process.

[0023] The IoT gateway is used to collect field sensor data and transmit it to the data center through the standardized protocol MQTT. The wireless transmission network includes Wi-Fi, LoRa, and 5G technologies to ensure real-time and efficient data transmission. The edge computing device pre-processes some data locally to reduce transmission delays and central computing pressure.

[0024] The real-time data processing platform uses the big data technology platform Apache Kafka for data stream processing to ensure the real-time and availability of data. The distributed database and cloud storage use Hadoop, NoSQL database MongoDB, and Cassandra to store construction data and material data to ensure the elasticity and high availability of data storage. Data analysis and AI model training use the big data platform Hadoop for data analysis and AI model training to support intelligent prediction and decision-making.

[0025] The dynamic digital twin model system builds and updates the three-dimensional digital twin model of the construction site in real time, supports multi-scale view switching and historical state playback, the intelligent material management engine is based on AI for material demand forecasting, adaptive supply chain management, intelligent warehousing and inventory management, the panoramic visualization and collaboration platform is a platform for high-fidelity three-dimensional visualization, multi-user real-time collaboration, mobile and remote access, the intelligent decision-making and prediction module is data-driven decision support, risk prediction and emergency plans, automated scheduling and resource optimization, the IoT-driven automated process management is full-process automated monitoring and management, intelligent scheduling of equipment and personnel, and energy efficiency and environmental protection management.

[0026] The web user interface is a user interface based on the modern web technology React, which provides rich interactive functions and good user experience. The mobile application is a cross-platform mobile application based on React Native, which supports on-site managers to view data and perform operations anytime and anywhere. The API interface is an open and standardized API interface that supports integration with external systems ERP and SCM to enhance the system's interoperability and scalability.

[0027] Software and hardware deployment

[0028] According to the layout and monitoring needs of the construction site, select the installation location of the sensor to ensure coverage of key areas. On-site technicians are responsible for the installation of sensors and ensure data accuracy by testing and debugging the working status of the sensors. Install the IoT gateway at the data collection point to ensure that all sensor data can be smoothly transmitted to the central processing system. Configure wireless networks (such as Wi-Fi, LoRa, 5G) to ensure low-latency transmission and efficient coverage of data. Plan the flight path of the drone to ensure coverage of all key areas of the construction site. Install lidar equipment at key locations on site to capture three-dimensional data of the construction site in real time.

[0029] Use React and framework to develop the web user interface to ensure that users can access all functions of the system through the browser. Use React Native to develop mobile applications to support real-time access and operation by on-site managers. Develop standardized API interfaces to achieve data communication between modules and integration with external systems (such as ERP, SCM). Develop real-time data processing pipelines and data storage systems based on the big data platform Spark to ensure the real-time and scalability of data. Use the TensorFlow framework to develop AI models to support material demand forecasting and intelligent scheduling functions.

[0030] Import the BIM model of the construction site into the system as the basic data of the digital twin. Develop a data integration module to integrate the data of sensors, drones and lidar into the digital twin model in real time. Realize multi-scale view switching from macro to micro to support management needs at different levels.

[0031] Although 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 the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital twin three-dimensional visualization material management system for traffic engineering construction, comprising a data acquisition layer (1), characterized in that: The data collection layer (1) is connected to the data transmission layer (2), the data transmission layer (2) is connected to the data processing and storage layer (3), the data processing and storage layer (3) is connected to the application layer (4), and the application layer (4) is connected to the user interface layer (5); The data collection layer (1) includes field sensors, RFID / Barcode scanning equipment, drones and ground laser radars, surveillance cameras and other video equipment; the data transmission layer (2) includes an Internet of Things gateway, a wireless transmission network, and edge computing equipment; the data processing and storage layer (3) includes a real-time data processing platform, a distributed database and cloud storage, data analysis and AI model training; The application layer (4) includes a dynamic digital twin model system, an intelligent material management engine, a panoramic visualization and collaboration platform, an intelligent decision-making and prediction module, and an Internet of Things-driven automated process management; the user interface layer (5) includes a Web user interface, a mobile application, and an API interface.

2. According to claim 1, a traffic engineering construction digital twin three-dimensional visualization material management system is characterized by: The on-site sensors include temperature sensors, humidity sensors, displacement sensors, and vibration sensors. The RFID / Barcode scanning equipment is used for material tracking and management, and collects material entry and exit, inventory, and location data. The drone and ground lidar are used for on-site imaging and laser scanning to obtain three-dimensional model data. The surveillance cameras and other video equipment are used for on-site real-time video monitoring.

3. According to claim 1, a traffic engineering construction digital twin three-dimensional visualization material management system is characterized by: The IoT gateway is used to collect field sensor data and transmit it to the data center through the standardized protocol MQTT. The wireless transmission network includes Wi-Fi, LoRa, and 5G technologies. The edge computing device is used to pre-process some data locally to reduce transmission delays and central computing pressure.

4. According to claim 1, a traffic engineering construction digital twin three-dimensional visualization material management system is characterized by: The real-time data processing platform adopts the big data technology platform Apache Kafka for data stream processing, the distributed database and cloud storage use Hadoop, NoSQL database MongoDB, and Cassandra to store construction data and material data, and the data analysis and AI model training use the big data platform Hadoop for data analysis and AI model training.

5. The digital twin three-dimensional visualization material management system for traffic engineering construction according to claim 1 is characterized by: The dynamic digital twin model system is for real-time construction and updating of three-dimensional digital twin models of construction sites. The intelligent material management engine is for AI-based material demand forecasting, adaptive supply chain management, and intelligent warehousing and inventory management. The panoramic visualization and collaboration platform is for high-fidelity three-dimensional visualization, multi-user real-time collaboration, and mobile and remote access platforms. The intelligent decision-making and prediction module is for data-driven decision support, risk prediction and emergency plans, automated scheduling and resource optimization. The IoT-driven automated process management is for full-process automated monitoring and management, intelligent scheduling of equipment and personnel, and energy efficiency and environmental protection management.

6. A digital twin three-dimensional visualization material management system for traffic engineering construction according to claim 1, characterized in that: The web user interface is a user interface based on the modern web technology React, the mobile application is a cross-platform mobile application based on React Native, and the API interface is an open and standardized API interface.

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