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A Predictive System for IoTs Reconfiguration Based on TensorFlow Framework

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Industrial Networks and Intelligent Systems (INISCOM 2020)

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Abstract

IoTs are rapidly growing with the addition of new sensors and devices to existing IoTs. The demand of IoT nodes keeps increasing to adapt to changing environment conditions and application requirements, the need for reconfiguring these already existing IoTs is rapidly increasing. It is also important to manage the intelligent context to execute when it will trigger the appropriate behavior. Yet, many algorithms based on different models for time-series sensor data prediction can be used for this purpose. However, each algorithm has its own advantages and disadvantages, resulting in different reconfiguration behavior predictions for each specific IoTs application. Developing an IoTs reconfiguration application has difficulty implementing many different data prediction algorithms for different sensor measurements to find the most suitable algorithm. In this paper, we propose IoTs Reconfiguration Prediction System (IRPS), a tool that helps IoT developers to choose the most suitable time-series sensor data prediction algorithms for trigger IoTs reconfiguration actions.

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Notes

  1. 1.

    https://teachablemachine.withgoogle.com/.

  2. 2.

    https://www.tensorflow.org/tfx/guide/serving.

  3. 3.

    https://www.tensorflow.org/js/tutorials.

  4. 4.

    https://reactjs.org/.

  5. 5.

    https://www.kaggle.com/saikatchoudhury/starter-smart-home-dataset-with-a8895cb2-c.

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Author information

Authors and Affiliations

  1. Faculty of Computer Networks and Communications, University of Information Technology, Vietnam National University, Ho Chi Minh City, Vietnam

    Tuan Nguyen-Anh & Quan Le-Trung

  2. Vietnam - Korea University of Information Technology and Communications, The University of Danang, Danang City, Vietnam

    Tuan Nguyen-Anh

Authors
  1. Tuan Nguyen-Anh
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  2. Quan Le-Trung
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Corresponding author

Correspondence to Tuan Nguyen-Anh .

Editor information

Editors and Affiliations

  1. Faculty of Electrical and Electronics Engineering, Duy Tan University, Da Nang, Vietnam

    Nguyen-Son Vo

  2. Le Quy Don Technical University, Hanoi, Vietnam

    Van-Phuc Hoang

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Nguyen-Anh, T., Le-Trung, Q. (2020). A Predictive System for IoTs Reconfiguration Based on TensorFlow Framework. In: Vo, NS., Hoang, VP. (eds) Industrial Networks and Intelligent Systems. INISCOM 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 334. Springer, Cham. https://doi.org/10.1007/978-3-030-63083-6_16

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  • DOI: https://doi.org/10.1007/978-3-030-63083-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-63082-9

  • Online ISBN: 978-3-030-63083-6

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