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Machine Learning Powered IoT for Smart Applications

Author

Listed:
  • Zhala Jameel Hamad

    (Information System Engineering, Erbil Polytechnic University, Erbil, Iraq)

  • Shavan Askar

    (Erbil Polytechnic University, Erbil, Iraq)

Abstract

With the coming of fast advancements, with the assistance of IoT, a great percentage of heterogeneous devices can be connected with each other. The technology with the relationship of different devices through the internet is named the internet of things (IoT), makes a wide number of different characteristics and qualities of data. IoT and Machine learning (ML) guarantees the widespread advancement to grow the insights of the IoT devices and applications. Over the final few years, artificial intelligence and machine learning have advanced very significantly. It allows a machine or system to learn more effectively than people learn on their own. When we learn some kind of system about the concept of our trial or the knowledge obtained after evaluating it. Combining IoT with rapidly advancing ML technologies can make ‘smart machines’ that mimic smart action to do well-informed resolve with little or no human involvement. There are at least two fundamental reasons, why machine learning is a suitable solution for the IoT world? The primary has got to do with the volume of data and the automation openings. The second is related to the prescient investigation. Therefore, this paper focuses on ML in different techniques and different domains that motivate and support IoT applications. Many previous works related to this subject and examples have been addressed, explained in detail. The results showed that ML plays a vital role in monitoring, processing, systematic investigation, and smart use of the expansive measure of data in several fields. It was also beneficial for helping users’ process massive data.

Suggested Citation

  • Zhala Jameel Hamad & Shavan Askar, 2021. "Machine Learning Powered IoT for Smart Applications," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 92-100.
  • Handle: RePEc:aif:journl:v:5:y:2021:i:3:p:92-100
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    References listed on IDEAS

    as
    1. Glena Aziz Qadir & Shavan Askar, 2021. "Software Defined Network Based VANET," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 83-91.
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    Citations

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    Cited by:

    1. Shavan Askar & Kurdistan Ali & Tarik A. Rashid, 2021. "Fog Computing Based IoT System: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 183-196.
    2. Shavan Askar & Faris Keti, 2021. "Performance Evaluation of Different SDN Controllers," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 67-80.
    3. Shavan Askar & Glena Aziz Qadir & Tarik A. Rashid, 2021. "SDN Based 5G VANET: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 131-147.
    4. Shavan Askar & Kosrat Dlshad Ahmed & Shahab Wahhab Kareem, 2021. "Deep learning Utilization in SDN Networks: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 174-182.
    5. Shavan Askar & Ibrahim Shamal Abdulkhaleq & Shahab Wahhab Kareem, 2021. "Blockchain systems: analysis, applications, & risks," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 163-173.
    6. Shavan Askar & Baydaa Hassan Husain & Tarik A. Rashid, 2021. "SDN Based Fog Computing: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 117-130.
    7. Shavan Askar & Zhwan Mohammed Khalid & Tarik A. Rashid, 2021. "Blockchain For Securing IoT Devices: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 209-224.
    8. Shavan Askar & Zhala Jameel Hamad & Shahab Wahhab Kareem, 2021. "Deep Learning and Fog Computing: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 197-208.
    9. Shavan Askar & Chnar Mustaf Mohammed & Shahab Wahhab Kareem, 2021. "Deep Learning in IoT systems: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 131-147.

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    6. Shavan Askar & Kosrat Dlshad Ahmed & Shahab Wahhab Kareem, 2021. "Deep learning Utilization in SDN Networks: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 174-182.
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