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Deep Learning for Edge Computing Applications: A State-of-the-art Survey

Fangxin Wang, Miao Zhang, Xiangxiang Wang, Xiaoqiang Ma, Jiangchuan Liu
2020 IEEE Access  
In this article, we provide a comprehensive survey of the latest efforts on the deep-learning-enabled edge computing applications and particularly offer insights on how to leverage the deep learning advances  ...  Besides, the recent breakthroughs in deep learning have greatly facilitated the data processing capacity, enabling a thrilling development of novel applications, such as video surveillance and autonomous  ...  EMPOWERING EDGE APPLICATIONS WITH DEEP LEARNING A.  ... 
doi:10.1109/access.2020.2982411 fatcat:43atfhktujbuxns2bsl2cfpnay

Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things [article]

Jing Zhang, Dacheng Tao
2020 arXiv   pre-print
This paper presents a comprehensive survey on AIoT to show how AI can empower the IoT to make it faster, smarter, greener, and safer.  ...  Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing.  ...  By contrast, we conduct this survey on deep learning for IoT data processing using a new taxonomy, i.e., how deep learning improves the ability of IoT systems to perceive, learn, reason, and behave.  ... 
arXiv:2011.08612v1 fatcat:dflut2wdrjb4xojll34c7daol4

Deep learning and Big Data Analysis: Challenges, Opportunities and Applications

Mehroush Banday
2018 International Journal of Trend in Scientific Research and Development  
With the approach of IoT, there are tremendous changes going in the measure of information. and deep learning are the two most critical concentration focuses in this universe of computerized science.  ...  A key favourable position of Deep Learning is Big Data investigation examination that it can pick up from huge mass of unsupervised data.  ...  Among the numerous machine learning approaches, Deep learning has been effectively used in numerous Unstructured data format IoT applications in late years [22].  ... 
doi:10.31142/ijtsrd12710 fatcat:dlcynhlqlfdsvfgk3jdkohglwm

Machine learning and Artificial Intelligence for Cyber security In Internet of Things Perspective

Dr. Santosh Kumar Sharma*, Dr. K. Narasimha Raju**, P. Praveen Kumar***, D. Satish, K.L.Prasad****
2021 Zenodo  
To study the security breaches, in IOT we have conducted a comprehensive and complete survey of machine learning techniques and scope of artificial intelligence in IOT security.  ...  At present, to the finest work of our knowledge to many research survey searching are published but there is a rare evidences which focus on the integrated concept of machine learning and artificial intelligences  ...  Security Challenges Machine Learning Techniques(Surveyed References) e.  ... 
doi:10.5281/zenodo.5752135 fatcat:3npkqinm7zfuji7hqgzxmd6cfy

Blockchain-Enabled Edge Intelligence for IoT: Background, Emerging Trends and Open Issues

Yao Du, Zehua Wang, Victor C. M. Leung
2021 Future Internet  
Blockchain, a distributed ledger technology (DLT), refers to a list of records with consecutive time stamps.  ...  This decentralization technology has become a powerful model to establish trust among trustless entities, in a verifiable manner.  ...  a practical decentralized deep learning approach for IoT applications based on the FL and blockchain.  ... 
doi:10.3390/fi13020048 fatcat:2j6xvdr5hrckxeb5aku2zjzuba

Guest Editorial: Special Issue on Blockchain and Edge Computing Techniques for Emerging IoT Applications

Victor C. M. Leung, Xiaofei Wang, F. Richard Yu, Dusit Niyato, Tarik Taleb, Sangheon Pack
2021 IEEE Internet of Things Journal  
Focusing on the research of social-aware cloud computing, cooperative cell caching, and mobile traffic offloading, he has authored over 100 technical papers in  ...  Li et al., in "NOMA-enabled cooperative computation offloading for blockchain-empowered Internet of Things: A learning approach," propose a multiagent deep reinforcement learning framework to achieve long-term  ...  In addition, a survey on state-of-the-arts security and privacy, and scalability of IIoT critical infrastructures is provided.  ... 
doi:10.1109/jiot.2021.3050050 fatcat:rux57gjppjdqla556myxnvp4ve

Table of contents

2019 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)  
Azam, A.Rahman, K.Paul, Md.S.Bari 118 25 Intrusion Detection in Internet of Things (IoTs) Based Applications using Blockchain Technology Shashvi Mishra, Amit Kumar Tyagi 123 26 A Survey on  ...  Ajay A. Gidd, Mr. Shekhar A. Molaj, Mr. Ajinkya S. Shewale 556 Study on Machine learning based Social Media and Sentiment analysis for medical data applications R. Meena, Dr. V.  ... 
doi:10.1109/i-smac47947.2019.9032470 fatcat:ofhwmgnicvct7hbgax2zhnyp2e

Role of Internet of Things (IoT) in Retail Business and Enabling Smart Retailing Experiences

Md. Shakawat Hossain, Nur Mohammad Ali Chisty, Ruhul Amin
2021 Asian Business Review  
This paper surveys and arranges the most common applications of IoT and solutions for successful marketing at retail from the point of retailers and customers as well as from the point of manufacturers  ...  Internet of Things (IoT) is anticipated to be one of the primary megatrends up in innovation.  ...  The infrastructure of Amazon Go is significantly based on machine learning, deep learning, IoT sensors, and computer vision methodologies.  ... 
doi:10.18034/abr.v11i2.579 fatcat:quzy4tntq5ckfies7ule73icti

Special Issue on Deep Reinforcement Learning for Emerging IoT Systems

Jia Hu, Peng Liu, Hong Liu, Obinna Anya, Yan Zhang
2020 IEEE Internet of Things Journal  
Guest Editorial Special Issue on Deep Reinforcement Learning for Emerging IoT Systems N OWADAYS we are witnessing the formation of a massive Internet-of-Things (IoT) ecosystem that integrates a variety  ...  The article titled "FDC: A secure federated deep learning mechanism for data collaborations in the Internet of Things" presents a secure data collaboration framework based on federated deep learning technology  ... 
doi:10.1109/jiot.2020.2998256 fatcat:rct75tsesbh7lkjmhuyogfi4ym

Anomalies Detection in Fog Computing Architectures Using Deep Learning

Dr. Subarna Shakya, Dr. Smys S.
2020 Journal of Trends in Computer Science and Smart Technology  
The experimental analysis showed that the deep learning models are highly grander compared to the rest of the basic detection structures on the terms of the accuracy in detecting, false-alarm and elasticity  ...  A novel platform of dispersed streaming is developed by the fog paradigm for the applications associated with the internet of things.  ...  Bashar et al [15] has elaborated the "Survey on Evolving Deep Learning Neural Network Architectures." Ananthi, J.  ... 
doi:10.36548/jtcsst.2020.1.005 fatcat:ljogji3kpfdgfmbb2kwygwppeq

Edge Network Optimization Based on AI Techniques: A Survey

Mitra Pooyandeh, Insoo Sohn
2021 Electronics  
AI is becoming a key component in many edge devices, including cars, drones, robots, and smart IoT devices. This paper describes the role of AI in a network edge.  ...  The network edge is becoming a new solution for reducing latency and saving bandwidth in the Internet of Things (IoT) network.  ...  This is the first survey paper that concentrates on intelligence study on edge networks, which is in contrast to past surveys, which focused on general edge network technologies.  ... 
doi:10.3390/electronics10222830 fatcat:kddhl7usq5aj5g3mr623lb24hm

Internet of Things Based Intelligent Techniques in Workable Computing: An Overview

Jiayi Guo, Shah Nazir, Zhongguo Yang
2021 Scientific Programming  
The influence of the proposed study is to offer a wide-ranging overview of the current literature related to the Internet of Things based on intelligent techniques in workable computing.  ...  The network of IoT is generally interconnected with different devices through the Internet.  ...  base [27] . e study provides an efficient audit on progressed IoT empowered personalized healthcare systems (PHS). e analysis surveys the current investigations of IoT empowered PHS, essential empowering  ... 
doi:10.1155/2021/6805104 fatcat:o7vhob2ihneuffg5qrxhjv3ace

Federated Deep Learning for Cyber Security in the Internet of Things: Concepts, Applications, and Experimental Analysis

Mohamed Amine Ferrag, Othmane Friha, Leandros Maglaras, Helge Janicke, Lei Shu
2021 IEEE Access  
All these related surveys did not cover the application of federated deep learning for cyber security in IoT applications with focusing on experimental analysis. Lyu et al.  ...  As shown in Tab. 1, we classify the federated learning surveys based on the following dimensions: • IoT application: It indicates whether the survey presented a taxonomy for federated learning-based frameworks  ...  He has been conducting several research projects with international collaborations on these topics. He was a recipient of the 2021 IEEE TEM BEST PAPER AWARD.  ... 
doi:10.1109/access.2021.3118642 fatcat:222fgsvt3nh6zcgm5qt4kxe7c4

An Overview on Analyzing Deep Learning and Transfer Learning Approaches for Health Monitoring

Yiting Wang, Shah Nazir, Muhammad Shafiq, Jude Hemanth
2021 Computational and Mathematical Methods in Medicine  
A detailed report of the existing literature in terms of deep learning and transfer learning is the dire need and facilitating of modern healthcare.  ...  To overcome these limitations, therefore, the proposed study presents a comprehensive review of the existing approaches, techniques, and methods associated with deep learning and transfer learning for  ...  The approach presented a smart patient monitoring and recommendation as a new framework based on cloud-oriented analytics and deep learning.  ... 
doi:10.1155/2021/5552743 fatcat:zglmxp2x4ff6xadqkuqzjb4fca

Machine Learning in IoT Security: Current Solutions and Future Challenges [article]

Fatima Hussain, Rasheed Hussain, Syed Ali Hassan, Ekram Hossain
2019 arXiv   pre-print
The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives.  ...  Therefore, Machine Learning (ML) and Deep Learning (DL) techniques, which are able to provide embedded intelligence in the IoT devices and networks, are leveraged to cope with different security problems  ...  Deep Learning (DL) and Deep Reinforcement Learning (DRL) Deep Learning: DL is a machine learning technique originated from ANN.  ... 
arXiv:1904.05735v1 fatcat:k5v6zad7lfhdrjngjmxgroafz4
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