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Land Transport

Proving Ground Vehicle Spatiotemporal Signal Acquisition, Transmission, and Visualization System

 

Solution Overview

The Proving Ground Vehicle Spatiotemporal Signal Acquisition, Transmission, and Visualization project is a comprehensive intelligent management platform for military equipment proving grounds, deeply integrating 3D geographic information, digital twin, artificial intelligence, and big data technologies to achieve comprehensive real-time monitoring, in-depth data analysis, and visual display of test vehicles. The platform constructs a digital mirror of the physical proving ground through high-precision sensors, video surveillance, and intelligent algorithms, providing precise technical support for equipment testing, training optimization, and decision-making, promoting a comprehensive digital and intelligent upgrade of proving ground management.

 

Solution Introduction

Core Technology Highlights

  • Digital Twin Engine
    Based on 3D simulation technology, it achieves high-precision virtual mapping of the proving ground environment, vehicle operating status, and physical entities, supporting dynamic interaction and real-time synchronization.
    It loads massive city-level real-scene 3D data in seconds, offering transparent/solid dual-mode switching, intuitively presenting armored vehicle trajectories and command execution effects.
  • Multi-source Data Fusion
    Integrates multi-dimensional sensing data from lidar, RTK positioning, and video surveillance, acquiring vehicle speed, position, trajectory, and driver behavior information in real-time.
    Supports massive data storage and millisecond-level response, compatible with SQL, NoSQL databases, meeting efficient data processing needs in complex scenarios.
  • AI Intelligent Analysis
    Fatigue Driving Recognition: Real-time warning of abnormal driver status through facial features and physiological signal monitoring.
    Dangerous Action Detection: Uses YOLO algorithm to identify distracting behaviors such as smoking and making phone calls, enhancing test safety.
  • 3D Visualized Cockpit
    Based on a 3D GIS engine, it builds a
    Supports data charts (line charts, radar charts), 3D models, and real-time video linkage, providing multi-dimensional decision support.

Core Functions

  • Real-time Monitoring and Dynamic Mapping
    Real-time tracking of vehicle position, speed, and trajectory, simultaneously drawing strike response time curves, supporting command and control, and situational awareness.
    3D map dynamically displays armored vehicle operating status, linking front-end sensor data to achieve seamless interaction between virtual and physical.
  • Intelligent Early Warning and Risk Control
    Threshold Alarm: Customizes parameter thresholds, triggering audible/visual alarms and marking abnormal data when exceeded.
    Data Traceability: Full-cycle data storage and querying, supporting fault reproduction and optimization analysis.
  • Big Data Management and Visualization
    Displays trend charts of critical component technical parameters, supporting loading of tens of millions of data points in seconds with smooth zooming.
    Centralized management of electronic documents, enabling quick retrieval and sharing of unstructured data such as experimental reports and videos.
  • Driver Behavior Analysis
    In-car cameras record driver operations and instrument status throughout the process, combined with AI algorithms to evaluate driving compliance.
    Wireless video servers transmit data in real-time, supporting post-training review and strategy optimization.

Technical Advantages

  • High Efficiency and Precision
    Interface response speed ≤1000ms, rendering frame rate ≥25 frames/second, ensuring smooth real-time data presentation.
    Fusion of laser point cloud and BIM models, measurement error less than ±0.15 meters, meeting high-precision modeling requirements.
  • Secure and Reliable
    Data encryption transmission and multi-level access control, passed military-grade quality certification (GJB9001C-2017).
    System availability ≥99.9%, supports redundant design and automatic fault switching, ensuring stable operation in extreme environments.
  • Flexible Expansion
    Modular architecture compatible with mainstream IoT devices and data formats, supporting horizontal expansion and customized development.
    Provides multi-language API for Python, Java, C#, seamlessly integrating with third-party platforms and business systems.

Application Cases

Case Study 1: Spatiotemporal Signal Acquisition at a Military Equipment Proving Ground

Pain Points: Offline testing of proving ground vehicles requires on-board detection, which is high-risk, time-consuming, and labor-intensive.
Solution: Vehicle front-end data acquisition + wireless networking transmission + digital twin platform, supported by intelligent sensing, wireless networking, and multi-dimensional visualization technologies, to achieve multi-dimensional data monitoring and display in coordinated armored vehicle tests. This integrates acquisition, transmission, storage, and display throughout the data flow, promoting digital upgrading of equipment testing processes.
Results: Single-vehicle test time saved by 50%, multi-vehicle test time saved by over 70%, and personnel safety risk reduced by over 95%.

 

 

 

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Solution Introduction

Application Cases

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