Towards Edge-Based Data Lake Architecture for Intelligent Transportation System
<|reference_start|>Towards Edge-Based Data Lake Architecture for Intelligent Transportation System: The rapid urbanization growth has underscored the need for innovative solutions to enhance transportation efficiency and safety. Intelligent Transportation Systems (ITS) have emerged as a promising solution in this context. However, analyzing and processing the massive and intricate data generated by ITS presents significant challenges for traditional data processing systems. This work proposes an Edge-based Data Lake Architecture to integrate and analyze the complex data from ITS efficiently. The architecture offers scalability, fault tolerance, and performance, improving decision-making and enhancing innovative services for a more intelligent transportation ecosystem. We demonstrate the effectiveness of the architecture through an analysis of three different use cases: (i) Vehicular Sensor Network, (ii) Mobile Network, and (iii) Driver Identification applications.<|reference_end|>
@article{fernandes2024towards,
    title={Towards Edge-Based Data Lake Architecture for Intelligent Transportation
  System},
    author={Danilo Fernandes, Douglas L. L. Moura, Gean Santos, Geymerson S.
  Ramos, Fabiane Queiroz, Andre L. L. Aquino},
    journal={arXiv preprint arXiv:2409.02808},
    year={2024},
    doi={10.1145/3616394.3618270},
    archivePrefix={arXiv},
    eprint={2409.02808},
    primaryClass={cs.DB cs.AI cs.NI}
}