Details

Introduction.- Introduction to Fog data analytics for IoT applications.- Fog Data Analytics:  Systematic Computational Classification and Procedural Paradigm.- Fog Computing: Building a Road to IoT with Fog Analytics.- Data Collection in Fog Data Analytics.- Mobile FOG Architecture Assisted Continuous Acquisition of Fetal ECG Data for Efficient Prediction.- Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT applications.- Fog Data Based Statistical Analysis to Check Effects of Yajna and Mantra Science: Next Generation Health Practices.- Process Model for Fog Data Analytics for IoT Applications.- Medical Analytics Based on Artificial Neural Networks Using Cognitive Internet of Things.

<p>Dr. Sudeep Tanwar is an Associate Professor at the Computer Engineering Department at the Institute of Technology of Nirma University, India, and was a Visiting Professor at Jan Wyzykowski University in Polkowice, Poland, and the University of Pitesti, Romani. He received his Ph.D. in Wireless Sensor Networks from the Faculty of Engineering and Technology, Mewar University, India, in 2016. He has received three best research paper awards, including two from top-tier international conferences (IEEE-ICC and IEEE-GLOBECOM). His current interests include routings issues in WSN, blockchain technology, smart grid, and fog computing. He has authored/edited six books: Routing in Heterogeneous Wireless Sensor Networks (ISBN: 978-3-330-02892-0), Big Data Analytics (ISBN: 978-93-83992-25-8), Mobile Computing (ISBN: 978-93-83992-25-6), Energy Conservation for IoT Devices: Concepts, Paradigms and Solutions (ISBN: 978-981-13-7398-5), and Multimedia Big Data Computing for IoT Applications: Concepts, Paradigms and Solutions (ISBN: 978-981-13-8759-3). He is an Associate Editor of the Security and Privacy Journal and is a member of IAENG, ISTE, and CSTA.​<br></p>

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDAin IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.<br>

Presents case studies to demonstrate the process model for tackling future challenges associated with FDA Discusses the layered architecture of FDA and also compares the life cycle of both big data and FDA Focuses on FDA in IoT and requirements related to Industry 4.0