Skip to main content

Energy Conservation for IoT Devices

Concepts, Paradigms and Solutions

  • Book
  • © 2019

Overview

  • Focuses on energy efficiency concerns in IoT
  • Discusses detailed approaches to conserving energy in IoT using comparative case studies
  • Addresses the needs of researchers, practitioners, and students alike

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 206)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (14 chapters)

Keywords

About this book

This book addresses the Internet of Things (IoT), an essential topic in the technology industry, policy, and engineering circles, and one that has become headline news in both the specialty press and the popular media. The book focuses on energy efficiency concerns in IoT and the requirements related to Industry 4.0. It is the first-ever “how-to” guide on frequently overlooked practical, methodological, and moral questions in any nations’ journey to reducing energy consumption in IoT devices.

The book discusses several examples of energy-efficient IoT, ranging from simple devices like indoor temperature sensors, to more complex sensors (e.g. electrical power measuring devices), actuators (e.g. HVAC room controllers, motors) and devices (e.g. industrial circuit-breakers, PLC for home, building or industrial automation). It provides a detailed approach to conserving energy in IoT devices, and comparative case studies on performance evaluation metrics, state-of-the-art approaches, and IoT legislation. 

Editors and Affiliations

  • Department of Computer Science and Engineering, G.B. Pant Government Engineering College, New Delhi, India

    Mamta Mittal

  • Department of Computer Science and Engineering, Nirma University, Ahmedabad, India

    Sudeep Tanwar

  • Swami Keshvanand Institute of Technology Management and Gramothan, Jaipur, India

    Basant Agarwal

  • Department of Computer Engineering, J.C. Bose University, YMCA, Faridabad, India

    Lalit Mohan Goyal

About the editors

Dr. Mamta Mittal graduated with a degree in Computer Science & Engineering from Kurukshetra University in 2001 and received her Master’s degree from YMCA, Faridabad. She subsequently completed Ph.D. at Thapar University Patiala and is currently teaching at GB PANT Government Engineering College, New Delhi. She has filed two patents: for a human surveillance system, and for a wireless copter for handling and defusing explosives. She is the editor of the books “Data Intensive Computing Application for Big Data” by IOS press, and “Big Data Processing Using Spark in Cloud” by Springer. Her research interests include Data Mining, Big Data, Soft Computing and Machine learning.

Dr. Sudeep Tanwar is an Associate Professor of Computer Engineering at Nirma University, Ahmedabad, India. He holds an M.Tech. in Information Technology from Guru Gobind Singh Indraprastha University, Delhi and later completed his Ph.D. in Computer Science & Engineering with a specialization in Wireless Sensor Networks. He has authored more than 50 technical research papers published in peer-reviewed international journals and conference proceedings. An Associate Editor for “Security and Privacy Journal” (Wiley), his current research interests include Routing Issues in WSN, IoT, Integration of Sensors with the Cloud, Computational Aspects of Smart Grids, and Assessment of Fog Computing in BASN.  

Dr. Basant Agarwal is an Associate Professor at Swami Keshvanand Institute of Technology, India. He received his M.Tech. and Ph.D. in Computer Engineering from Malaviya National Institute of Technology, Jaipur, India. He was awarded the prestigious ERCIM PostDoc Fellowship through the “Alain Bensoussan Fellowship Programme” in 2016. Having worked as a postdoctoral fellow at the NTNU, Norway, his current research interests include Artificial Intelligence, NLP, Machine Learning, and related areas.  

Dr. Lalit Mohan Goyal received his M.Tech. in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi, and his Ph.D. in Computer Engineering from Jamia Millia Islamia University, New Delhi. Currently, he is an Assistant Professor at the Department of Computer Engineering, JC Bose University of Science & Technology, YMCA, Faridabad. He has 16 years of academic experience, and has published research papers in SCI-indexed & Scopus-indexed journals and conference proceedings.

 

 


Bibliographic Information

Publish with us