scholarly journals Survey On The application of Deep Learning in Internet of Things (IoT)

2021 ◽  
Author(s):  
shabnam shadroo ◽  
Amir Masoud Rahmani ◽  
Ali Rezaee
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Large Body ◽  
The Internet ◽  
Journal Articles ◽  
Network Computing ◽  
Computing Environment ◽  
Survey Paper ◽  
Software Sensors ◽  
The Internet Of Things

Abstract The Internet of Things (IoT) is a network of physical instruments, software, sensors that all are connected to the Internet. The IoT produces massive data, where, this enormous volume of data allows the use of deep learning algorithms (DLAs). Recently, the increase of the large body of data and their availability has been one of the main reasons for paying attention to this issue. Further, the recent upgrade of the hardware boosting the computational power has resulted in the utilize of deep learning alongside the IoT. Therefore, the purpose of the present research is to review the relevant conference and journal articles in IoT and deep learning from 2012 to July 2019. To review the publications, a composition of Systematic Mapping and systematic literature review has been employed for creating a survey paper. Accordingly, some questions have been raised; to answer which, 32 articles have been investigated. The papers have been categorized into four sections including a focus on data, network, computing environment, application with each being examined, and analyzed. This article would be beneficial for researchers who want to investigate the field of deep learning and IoT.

Role of the Internet of Things and deep learning for the growth of healthcare technology

2021 ◽  
pp. 113-127
Author(s):  
Dinesh Bhatia ◽  
S. Bagyaraj ◽  
S. Arun Karthick ◽  
Animesh Mishra ◽  
Amit Malviya
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
The Internet ◽  
Healthcare Technology ◽  
The Internet Of Things

scholarly journals Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1977 ◽  
Author(s):  
Geethapriya Thamilarasu ◽  
Shiven Chawla
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Learning Algorithm ◽  
Detection System ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Systems ◽  
The Internet Of Things

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.

scholarly journals Human Activity Recognition with Deep Learning: Overview, Challenges & Possibilities

2021 ◽  
Author(s):  
Pranjal Kumar
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Activity Recognition ◽  
Human Activity ◽  
Recognition System ◽  
The Internet ◽  
Learning Approaches ◽  
The Public ◽  
Sensory Data ◽  
The Internet Of Things

The growing use of sensor tools and the Internet of Things requires sensors to understand the applications. There are major difficulties in realistic situations, though, that can impact the efficiency of the recognition system. Recently, as the utility of deep learning in many fields has been shown, various deep approaches were researched to tackle the challenges of detection and recognition. We present in this review a sample of specialized deep learning approaches for the identification of sensor-based human behaviour. Next, we present the multi-modal sensory data and include information for the public databases which can be used in different challenge tasks for study. A new taxonomy is then suggested, to organize deep approaches according to challenges. Deep problems and approaches connected to problems are summarized and evaluated to provide an analysis of the ongoing advancement in science. By the conclusion of this research, we are answering unanswered issues and providing perspectives into the future.

scholarly journals Internet of things - A Survey

2021 ◽  
pp. 417-438
Author(s):  
Pranjal Upadhyay ◽  
Prof. Deepak Upadhyay
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Detailed Knowledge ◽  
Network Layer ◽  
Survey Paper ◽  
The Internet Of Things

In the survey paper we defined all the topics related to the Internet of Things. All the components related to the internet of things in Details. You will get detailed knowledge about the Internet of things ecosystem, Internet of things Elements, Internet of things Architecture. Also, we will cover all the internet of things protocols and brief about protocols. In this we will provide the details of attack based on Protocols and at the end we justify why RPL is useful over 6Low-PAN in the internet on things network layer.

Fog-Embedded Deep Learning for the Internet of Things

2019 ◽  
Vol 15 (7) ◽  
pp. 4206-4215 ◽  
Author(s):  
Lingjuan Lyu ◽  
James C. Bezdek ◽  
Xuanli He ◽  
Jiong Jin
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
The Internet ◽  
The Internet Of Things
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