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An Architecture for the Real-Time Data Stream Monitoring in IoT

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Multimedia Big Data Computing for IoT Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 163))

Abstract

The IoT allows a new kind of monitoring strategy based on the heterogeneity of the devices and its lower cost. It implies a challenge in terms of the data interoperability and the associated semantic when they must support the real-time decision making. In this chapter, an integrated and interdisciplinary view of the data processing in the heterogeneous contexts is presented at the light of the Processing Architecture based on Measurement Metadata (PAbMM). The processing architecture gathers the data stream processing with the batch processing related to the Big Data repositories under the umbrella of the measurement projects. Thus, the integration between the measurement and evaluation (M&E) framework and the real-time processing is detailed. Followed, the interoperability is addressed from the M&E project definitions and the data interchanging related to PAbMM. The decision-making support is strengthened by a similarity mechanism which allows looking for similar experiences when a given situation lack of a specific knowledge. Finally, an application of the processing architecture based on Arduino technology for the “Bajo Giuliani” (La Pampa, Argentina) lagoon monitoring is shown.

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Notes

  1. 1.

    http://www.bpmn.org.

  2. 2.

    https://github.com/mjdivan/cincamipd.

  3. 3.

    https://www.w3.org/XML/.

  4. 4.

    https://www.json.org.

  5. 5.

    http://www.opengeospatial.org/standards/gml.

  6. 6.

    https://github.com/mjdivan/cincamimis.

  7. 7.

    https://github.com/google/gson.

  8. 8.

    https://kafka.apache.org.

  9. 9.

    https://www.raspberrypi.org.

  10. 10.

    https://www.arduino.cc.

  11. 11.

    https://kafka.apache.org.

  12. 12.

    https://spark.apache.org/streaming/.

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Author information

Authors and Affiliations

  1. Economics and Law School, National University of La Pampa, Coronel Gil 353. 1st Floor, 6300, Santa Rosa, Argentina

    Mario José Diván & María Laura Sánchez Reynoso

Authors
  1. Mario José Diván
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  2. María Laura Sánchez Reynoso
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Corresponding author

Correspondence to Mario José Diván .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

  2. Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Sudhanshu Tyagi

  3. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Neeraj Kumar

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Diván, M.J., Sánchez Reynoso, M.L. (2020). An Architecture for the Real-Time Data Stream Monitoring in IoT. In: Tanwar, S., Tyagi, S., Kumar, N. (eds) Multimedia Big Data Computing for IoT Applications. Intelligent Systems Reference Library, vol 163. Springer, Singapore. https://doi.org/10.1007/978-981-13-8759-3_3

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