A Framework for Promoting IoT- and Digital Twin-Enabled Intelligent Traffic Light Systems in China: An Empirical Study Based on a Malaysian Smart City Facilities Management Case

Abstract

This study explores the potential for the implementation of an advanced Intelligent Traffic Light System (ITLS) in Chinese urban landscapes, integrating Internet of Things (IoT) and digital twin technologies for sustainable urban development. Using empirical data from the Malaysia Smart Traffic Light Management (MSTLM) program, we assessed the effectiveness of the system on multiple dimensions critical to sustainability. Statistical analysis of eight cities showed significant improvements in vehicle safety programs: average travel time was reduced by 37.7%, congestion index by 38.5%, fuel consumption by 27.3%, and CO2 emissions by 18.4%. In addition, system reliability was significantly improved with 98.3% uptime and 280.5% increase in signal conditioning frequency. The study presents a comprehensive framework tailored to China's urban environment, emphasizing technical architectures, deployment strategies, and policy recommendations aligned with the SDGs. Our findings contribute to the debate on smart city infrastructure management, providing actionable insights for policymakers, urban planners, and stakeholders committed to resilient and sustainable urban growth providing an adaptable roadmap for large-scale deployment in rapidly urbanizing Chinese cities. Our findings bridge Malaysian empirical insights to China’s distinct infrastructure and governance structures.