Aloupogianni, Eleni and Doctor, Faiyaz and Karyotis, Charalampos and Maniak, Tomasz and Iqbal, Rahat (2024) A Digital Twin Architecture for Intelligent Traffic Management Based on Artificial Intelligence. In: Intelligent Environments 2024: Combined Proceedings of Workshops and Demos & Videos Session. Ambient Intelligence and Smart Environments, 33 . IOS Press, pp. 143-151. ISBN 978-1-64368-521-2. Official URL: http://doi.org/10.3233/AISE240026
Aloupogianni, Eleni and Doctor, Faiyaz and Karyotis, Charalampos and Maniak, Tomasz and Iqbal, Rahat (2024) A Digital Twin Architecture for Intelligent Traffic Management Based on Artificial Intelligence. In: Intelligent Environments 2024: Combined Proceedings of Workshops and Demos & Videos Session. Ambient Intelligence and Smart Environments, 33 . IOS Press, pp. 143-151. ISBN 978-1-64368-521-2. Official URL: http://doi.org/10.3233/AISE240026
Aloupogianni, Eleni and Doctor, Faiyaz and Karyotis, Charalampos and Maniak, Tomasz and Iqbal, Rahat (2024) A Digital Twin Architecture for Intelligent Traffic Management Based on Artificial Intelligence. In: Intelligent Environments 2024: Combined Proceedings of Workshops and Demos & Videos Session. Ambient Intelligence and Smart Environments, 33 . IOS Press, pp. 143-151. ISBN 978-1-64368-521-2. Official URL: http://doi.org/10.3233/AISE240026
Abstract
This work presents a concept for an innovative Digital Twin (DT) framework for urban traffic monitoring and management, tailored for the city of Singapore. The proposed architecture leverages real-time traffic and weather data integration, AI processing, and modular design to offer adaptive and versatile traffic insights. By incorporating live information from various sources and integrating real-time weather data, the framework enables proactive traffic management and enhances safety during adverse weather conditions. The paper discusses the implementation of the framework, and its potential impact on urban mobility, and suggests future directions for research and development to facilitate the framework’s implementation.
Item Type: | Book Section |
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Uncontrolled Keywords: | artificial intelligence; digital twin; Intelligent transportation; real-time data integration; urban traffic monitoring |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 30 Jul 2024 14:05 |
Last Modified: | 03 Oct 2024 12:15 |
URI: | http://repository.essex.ac.uk/id/eprint/38697 |
Available files
Filename: 202406_alleget_slovenia_workshop_digital_twin_sg_short_camera_ready_AISE-33-AISE240026.pdf
Licence: Creative Commons: Attribution-Noncommercial 4.0