一种基于大数据云服务的公路机电控制方法及系统
By using big data cloud services and machine learning models to assess the reliability of highway electromechanical equipment, the problem of inaccurate traditional assessments has been solved, enabling real-time monitoring and predictive maintenance of equipment, and improving the accuracy of equipment status and the flexibility of traffic management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING YUGONG ROAD MAINTENANCE CO LTD
- Filing Date
- 2023-10-07
- Publication Date
- 2026-07-17
AI Technical Summary
In traditional highway electromechanical control systems, the reliability assessment of electromechanical equipment is not accurate or timely enough, and real-time traffic flow and traffic conditions do not fully utilize data that affect the working status and lifespan of the equipment.
A big data cloud service-based approach is adopted to acquire location data of electromechanical equipment, traffic flow data, and environmental factor data. Machine learning models are then used for real-time assessment and predictive maintenance. This includes the integration of location identification, data analysis, and machine learning modules to construct an input dataset and perform reliability scoring.
It enables timely understanding of the working status of electromechanical equipment and assessment of wear and tear, reducing unexpected maintenance, extending equipment lifespan, lowering costs, and improving road operation efficiency and traffic management flexibility.
Smart Images
Figure CN117198055B_ABST