Distributed Data Acquisition

Distributed Data Acquisition is a data acquisition system architecture in which multiple spatially separated data acquisition nodes, interconnected through a network, independently collect and process sensor data in synchronized or asynchronous fashion to enable scalable, fault-tolerant, and geographically dispersed real-time data gathering, particularly in Internet of Things (IoT) and large-scale industrial monitoring environments.

77

Publications

2.3K

Citations

393

Authors

117

Institutions

Publications per year

2017–2026

16

Authors

393

  1. EB
    E. Barrera

    Universidad Politécnica de Madrid, Spain

    3 publications · 72 citations

    3

    h-index

  2. MR
    M. Ruíz

    Universidad Politécnica de Madrid, Spain

    3 publications · 72 citations

    3

    h-index

  3. JV
    J. Vega

    National Agency for New Technologies, Energy and Sustainable Economic Development, Italy

    3 publications · 72 citations

    3

    h-index

  4. LS
    L. Stevanato

    University of Padua, Italy

    2 publications · 41 citations

    2

    h-index

  5. GF
    Giancarlo Fortino

    University of Calabria, Italy

    2 publications · 50 citations

    2

    h-index

1–5 of 393

Venues

  1. IEEE Transactions on Nuclear Science

    11 publications · 217 citations

    10

    h-index

  2. 3

    h-index

  3. Human Brain Mapping

    2 publications · 360 citations

    2

    h-index

  4. Sensors

    2 publications · 43 citations

    2

    h-index

  5. Journal of Physics Conference Series

    2 publications · 27 citations

    2

    h-index

1–5