Development and Application of Online Noise Monitoring System for Urban Rail Transit Trains

Abstract

Objective With the rapid development and expansion of urban rail transit, the problem of noise pollution is increasingly prominent due to the continuous extension of train operation lifespan. This not only causes severe harm to passenger riding experience and health, but also directly affects the brand image and service quality of rail transit enterprises. Therefore, it is necessary to collect and monitor noise levels during train operation to implement targeted noise control measures, maximizing the effectiveness of noise mitigation efforts. Method With a combination of hardware and software resources such as noise sensors, STM32 microcontrollers, 4G transmission modules, Keil μVision5, Python, and OneNET cloud platform, an online noise monitoring system based on IoT (Internet of Things) is designed and developed specifically for urban rail transit trains. Result & Conclusion The system is successfully tested and validated on Kunming Metro Line 4, achieving real-time monitoring of train interior noise with advantages such as short sampling cycles, high data accuracy, and low data loss and latency rates. The system can issue timely alerts when noise levels exceed national standards, effectively meeting the design objectives. Additionally, the system can be applied to other environmental noise monitoring scenarios, providing reference for environmental noise treatment, enhancing the quality of life for residents, and promoting sustainable urban development.

Keywords

• urban rail transit
• noise
• online monitoring
• cloud platform