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Deep learning for Internet of things infrastructure - Baco Raton CRC Press 2021 - 248p.

Table of Contents:

Chapter 1 Data Caching at Fog Nodes under IoT Networks: Review of Machine Learning Approaches
Chapter 2 ECC-Based Privacy-Preserving Mechanisms Using Deep Learning for Industrial IoT: A State-of-the-Art Approaches
Chapter 3 Contemporary Developments and Technologies in Deep Learning-Based IoT
Chapter 4 Deep Learning-Assisted Vehicle Counting for Intersection and Traffic Management in Smart Cities
Chapter 5 Toward Rapid Development and Deployment of Machine Learning Pipelines across Cloud-Edge
Chapter 6 Category Identification Technique by a Semantic Feature Generation Algorithm
Chapter 7 Role of Deep Learning Algorithms in Securing Internet of Things Applications
Chapter 8 Deep Learning and IoT in Ophthalmology
Chapter 9 Deep Learning in IoT-Based Healthcare Applications
Chapter 10 Authentication and Access Control for IoT Devices and Its Applications
Chapter 11 Deep Neural Network-Based Security Model for IoT Device Network.


This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)-based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end-users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end-users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.


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Machine learning
Internet of things

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