Efficient Sensors Selection for Traffic Flow Monitoring: An Overview of Model-Based Techniques leveraging Network Observability
<|reference_start|>Efficient Sensors Selection for Traffic Flow Monitoring: An Overview of Model-Based Techniques leveraging Network Observability: The emergence of 6G-enabled Internet of Vehicles (IoV) promises to revolutionize mobility and connectivity, integrating vehicles into a mobile Internet-of-Things (IoT)-oriented wireless sensor network (WSN). 5G technologies and mobile edge computing further support this vision by facilitating real-time connectivity and empowering massive access to the Internet. In this context, IoT-oriented WSNs play a crucial role in intelligent transportation systems, offering affordable alternatives for traffic monitoring and management. This paper's contribution is twofold: (i) surveying state-of-the-art model-based techniques for efficient sensor selection in traffic flow monitoring, emphasizing challenges of sensor placement; and (ii) advocating for data-driven methodologies to enhance sensor deployment efficacy and traffic modeling accuracy. Further considerations underscore the importance of data-driven approaches for adaptive transportation systems aligned with the IoV paradigm.<|reference_end|>
@article{fabris2024efficient,
    title={Efficient Sensors Selection for Traffic Flow Monitoring: An Overview of
  Model-Based Techniques leveraging Network Observability},
    author={Marco Fabris, Riccardo Ceccato and Andrea Zanella},
    journal={Presented at the Special Session 8 "Challenges and advanced
  technologies for crowd mobility monitoring: a 5G/6G approach" of the EuCNC &
  6G Summit, Antwerp, Belgium, 3-6 June, 2024},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.08588},
    primaryClass={cs.NI cs.SY eess.SY}
}