Green Internet of Things and Machine Learning: Towards a Smart Sustainable World

Health Economics and Financing explores the use of green-IOT and machine learning to improve the quality of life and sustainable environment. It outlines various green ICT technologies, explores the potential for diverse real-time areas, and highlights challenges and obstacles to implementing G-IoT. The book is helpful for research scholars and researchers in computer science and engineering, information technology, electronics and electrical engineering, and industry experts.

Format: Hardback
Length: 400 pages
Publication date: 04 February 2022
Publisher: John Wiley & Sons Inc

The Internet of Things (IoT) is a rapidly evolving concept that enables the connection of billions of devices, enabling them to collect, perceive, and transmit data from their environment. This data transmission, however, consumes substantial energy, making it a crucial area of research to enhance energy efficiency in IoT devices. The green Internet of Things (G-IoT) emerges as a solution, leveraging intelligent processing and analysis to create energy-efficient smart IoT applications with large data sets. Machine learning (ML) algorithms play a pivotal role in predicting sustainable energy consumption, aiding in the development of guidelines for easier IoT device implementation.

Green Internet of Things and Machine Learning delves into an in-depth examination of the principles of G-IoT through the lens of machine learning. It provides a comprehensive overview of various green ICT technologies, explores their potential applications in diverse real-time domains, and highlights the challenges and obstacles associated with implementing G-IoT in the real world. Additionally, the book offers insights into how machine learning and G-IoT will impact various sectors, including green-IOT and ML-based smart computing, energy-efficient ML techniques for IoT devices, case studies of G-IoT and ML in agriculture, smart farming, smart transportation, banking, and healthcare.

The target audience for this book includes research scholars and researchers in the fields of computer science and engineering, information technology, electronics, and related disciplines. It serves as a valuable resource for those seeking to advance their knowledge and understanding of the intersection of G-IoT and machine learning, paving the way
way for innovative solutions and applications that contribute to a more sustainable and quality of life.

Weight: 670g
Dimension: 243 x 152 x 26 (mm)
ISBN-13: 9781119792031