Abstract
The development of digital twins for road traffic has garnered significant attention within the scientific community, particularly in the realms of virtualization and the Internet of Things (IoT). The implementation of a digital twin for automobiles offers a virtual replica, capable of discerning the precise location, status, and real-time behavior of each vehicle present in the road traffic network. The primary objective of this endeavor is to create an advanced digital twin of cars that can seamlessly navigate through road traffic. To accomplish this, a meticulously selected technical approach involves employing a platform that simulates virtual sensor networks, accompanied by a purpose-built application that facilitates the access and dissemination of car-related data. Furthermore, this undertaking incorporates the utilization of an existing traffic simulator alongside a robust communication protocol to ensure seamless data transfer between the simulation environment and the sensors responsible for data collection from automobiles.
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Ngadi, H. et al. (2024). Toward A Digital Twin IoT for the Validation of AI Algorithms in Smart-City Applications. In: Renault, É., Boumerdassi, S., Mühlethaler, P. (eds) Machine Learning for Networking. MLN 2023. Lecture Notes in Computer Science, vol 14525. Springer, Cham. https://doi.org/10.1007/978-3-031-59933-0_8
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