Scalable System for Smart Urban Transport Management

Autor: Nauman Ahmad Khan, Jean-Christophe Nebel, Souheil Khaddaj, Vesna Brujic-Okretic
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Advanced Transportation, Vol 2020 (2020)
Druh dokumentu: article
ISSN: 0197-6729
2042-3195
DOI: 10.1155/2020/8894705
Popis: Efficient management of smart transport systems requires the integration of various sensing technologies, as well as fast processing of a high volume of heterogeneous data, in order to perform smart analytics of urban networks in real time. However, dynamic response that relies on intelligent demand-side transport management is particularly challenging due to the increasing flow of transmitted sensor data. In this work, a novel smart service-driven, adaptable middleware architecture is proposed to acquire, store, manipulate, and integrate information from heterogeneous data sources in order to deliver smart analytics aimed at supporting strategic decision-making. The architecture offers adaptive and scalable data integration services for acquiring and processing dynamic data, delivering fast response time, and offering data mining and machine learning models for real-time prediction, combined with advanced visualisation techniques. The proposed solution has been implemented and validated, demonstrating its ability to provide real-time performance on the existing, operational, and large-scale bus network of a European capital city.
Databáze: Directory of Open Access Journals
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