Deep Learning in IoT systems: A Review
Shavan Askar, Chnar Mustafa Mohammed, Shahab Wahhab Kareem
The expansion of the internet, along with its interconnection of devices has made it possible to increase the world’s interconnectedness in these days, with the growth in internet connectivity capabilities and quality, a lot of items are interconnected, which means they communicate with each other using new and powerful techniques. Innovative sensor systems are spreading their consumers are strongly connected to the internet. The growth of linked sensors and systems has an incremental impact on the quantity of data. Regardless of its purpose, it is accumulating whole data. The Internet of Things (IoT) has a practical use for industries such as obtaining field data, tracking it and keeping them, all connected. To imitate the human intelligence level, the machine or software is made smarter by using advanced deep learning. In the paper, several diverse types of IoT technologies will be referenced, including intelligent cities, smart health care, mobility networks, and educational systems, among others. In addition, a range of novel deep learning algorithms that were implemented to simplify the intelligent usage of the machines without involving human control has been reviewed and good results of each algorithm in different categories are demonstrated as a table of comparison. This paper gives an overview of the applications that need to combine deep learning to serve IoT applications in an efficient and automated manner.
Keywords: Internet of Things (IoT), Deep Learning (DL), IoT Applications, Challenges, DL Algorithms, DL Platforms.
|Title:||Deep Learning in IoT systems: A Review|
|Author:||Shavan Askar, Chnar Mustafa Mohammed, Shahab Wahhab Kareem|
|Journal Name:||International Journal of Science and Business|
|ISSN:||ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)|
|Date of Publication:||19/08/2021|
|Paper Type:||Literature review|
Cite This Article:
Shavan Askar, Chnar Mustafa Muhammed, Shahab Wahhab Kareem (2021). Deep Learning in IoT systems: A Review. International Journal of Science and Business, 5(6), 131-147. doi: https://doi.org/10.5281/zenodo.5221646
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About Author (s)
Shavan Askar (Corresponding Author), Assistant Professor, CEO of Arcella Telecom, College of Engineering, Erbil Polytechnic University, Erbil, Iraq. Email: firstname.lastname@example.org
Chnar Mustaf Mohammed, Information System Engineering, Erbil Polytechnic University, Erbil, Iraq.
Shahab Wahhab Kareem, Lecturer, Erbil Polytechnic University, Erbil, Iraq.