Design and Real-Time Analytics of a Digital Twin-Based Framework for Intelligent Mobility Management

Abstract

Digital Twin ranks amongst the disruptive digital transformation technologies that permit the modeling of complex systems and their management by creating digital replicas of real-world environments. Digital Twins such as smart city, autonomous car and intelligent transport network operate for real-time monitoring, simulating and upgrading of transport infrastructure and traffic movement. By integrating data from sensors, IoT, connected vehicles, and traffic control systems, It can perpetually mirror the real-world situations and help in making the right decisions for the future. This is about designing and operating a system for mobility environments which will help in traffic reduction, increase safety, and contribute to a cleaner environment. The system relies on data from vehicles, road facilities, environmental sensors, and communication networks to keep track of travel patterns and detect the likelihood of traffic jams or any other types of disruptions. The design allows for large scale integration with edge computing and cloud platforms in order to perform real-time analytics.