Design and Deployment Plan of Elastic Cluster Cloud Platform Architecture for Metro Passenger Flow Analysis Scenarios

Abstract

[Objective] In the rapidly evolving landscape of digital technology, cloud computing is widely utilized in various industries including metro systems. To ensure passenger travel safety and achieve real-time acquisition and efficient analysis of large-scale passenger flow data, it is necessary to propose an elastic cluster cloud platform tailored for passenger flow analysis scenarios. [Method] The core functional requirements of the above platform are analyzed, and the architecture of it is proposed, highlighting the platform unique capabilities. Two deployment plans for the elastic cluster cloud platform are put forward for metro systems at different stages of development, and the pros and cons of each deployment plan are analyzed. Taking Shanghai Metro as example, the investment costs of the deployment plans are compared based on capability requirements. The alignment between the architecture of the elastic cluster cloud platform and the characteristics of metro passenger flow analysis business is also examined. [Result & Conclusion] Metro passenger flow analysis scenarios exhibit characteristics such as multi-system concurrency, high real-time requirements, and large data volume. The elastic cluster cloud platform can meet various demands of passenger flow analysis business.

Keywords

• metro
• passenger flow analysis
• flexible scheduling
• cloud platform