Demystifying Emerging Trends in Green Technology explores the transformative intersection of computational intelligence, disruptive technologies, and green innovations. This volume offers insights into diverse fields such as blockchain, IoT, artificial intelligence, machine learning, and sustainable development. Each chapter presents cutting-edge research and practical solutions addressing environmental sustainability, energy efficiency, and eco-friendly technologies.
With contributions from leading researchers, this book discusses advancements like blockchain-based security, green marketing, smart waste management, sustainable agriculture, and innovative healthcare solutions. It emphasizes the role of interdisciplinary approaches in driving a greener and smarter future.
 
Key Features:
- Integration of AI, IoT, and blockchain in sustainable systems
- Applications in healthcare, agriculture, energy, and environmental science
- Practical and innovative solutions for real-world challenges
- Insights into future trends in green technology and disruptive innovation
 
Readership:
Ideal for academics, researchers, professionals, and enthusiasts seeking to advance green technology practices.

Demystifying Emerging Trends in Green Technology

End User License Agreement (for non-institutional, personal use)

Trust-Based Neighbor Selection Protocol to Elect Leader in Blockchain using zk-SNARKs Algorithms

Electronic Healthcare Data Security Using Blockchain

E-cops - An Online Crime Reporting System

Limitations of Traditional Feature Extraction Methods

Diabetic Eye Disease Classification by Residual Network based Feature Mapping with Support Vector Machine

Evaluation of Performance of a Person using Virtual Stock Market

GIS Mapping of High Sewage Areas in India and Sustainable Design of Sewage Disposal System

Examining the Viability of Integrating Blockchain Technology into IoT Devices for the Supply Chain

Blockchain-Based Secure Storage for IoT Management with Edge Computing

The Benefits of Automation Using Blockchain and AI

A Review of Applications Combining Blockchain Technology with Artificial Intelligence

Decentralized Application for Fundraising in Healthcare Using Blockchain Technology

Investigating Technology Adoption and Consumer Behaviour in Digital Age

Total Life Cycle Consideration toward Product Metrics Development

Challenges in Sustainable Product to Create Product Metrics

Comprehensive Life Cycle Methodology for the Development of Product Metrics

Detailed Overview of the Internet of Things and Its Amalgamation with Artificial Intelligence

A Dual Transfer Learning Based Model for Mammogram Images Enhancement and Classification

Empirical Analysis of Face Mask Detection Using Deep Learning

Estimation of the Price of Used Cars Using Machine Learning

A Smart System for Tracking and Analyzing Human Hand Movements using MediaPipe Technology and TensorFlow

Challenges in green growth and sustainable development

Initiatives to Overcome the Challenges in Green Growth and Sustainable Development

Initiatives for Challenges Faced By Developed Countries and India on Green Growth and Sustainable Development in the World

The Impact of Green Marketing on Consumer Purchasing Behaviour: A Study of the Attitudes, Beliefs, and Behaviours of Consumers towards Environmentally-Friendly Products

An IoT Based RFID Enabled Automatic Waste Segregator and Monitoring System

How to Reduce Environmental Cost by Green Accounting

Comparison of the Efficiency of K-Means, GMM and EM Algorithms in Image Processing

Green Technology to Achieve Environmental Safety and Sufficient Development

Electrical Insulating Properties of Epoxy Modified Shellac Polyamide Resin Blends

Electrical Insulating Properties of Epoxy-Modified Shellac Alkyd Resin Blends

Recognition of Characters of New-born Baby's Fingerprinting Using Machine Learning

Exploring Deep Learning Techniques for Accurate 3D Facial Expression Recognition

Health Screening Analysis Using Machine Learning

Blockchain Based Academic Certificate Authentication System

An Augmentation in Energy Efficiency for Grid-Coupled PV System by IT3FLC Controller-Based MPPT

Python in Finance: Introduction and Basic Strategy

Leveraging Green Technology in Organizational Behavior

Relationship between Green Technology and Organizational Behavior

Benefits of Green Technology and Challenges to Overcome

Empowering Sustainability: Leveraging Green Technology to Drive Environmental Responsibility in Organizational Behavior

IoT Based on Accident Detection and Alert System

Performance Evaluation of Tools Made of Super Hard Material CBN during the Renovation of Components of Harvester Machinery

A Comparative Study of Worklife Balance Trends and Challenges

Chronic Kidney Disease Prediction Using Machine Learning: Feature Selection

DIFFERENCE BETWEEN EXISTING SYSTEM AND PROPOSED SYSTEM

A Systematic Review: Technology for Battery Management System

An Intuitionistic Fuzzy EOQ Model Based on Trapezoidal Intuitionistic Fuzzy Numbers to Maintain a Green Environment by Disposing of Waste

Foliar Disease Detection Using ML and Deep Learning

Bentham Science Publishers

Demystifying Emerging Trends in Machine Learning (Volume 2) offers a deep dive into emerging and trending topics in the field of machine learning (ML). This edited volume showcases several machine learning methods for a variety of tasks. A key focus of this volume is the application of text classification for cybersecurity, E-commerce, sentiment analysis, public health and web content analysis.
 
 The 49 chapters highlight a wide variety of machine learning methods including SVNs, K-Means Clustering, CNNs, DCNNs, among others. Each chapter includes accessible information through summaries, discussions and reference lists. This comprehensive volume is essential for students, researchers, and professionals eager to understand the emerging trends reshaping machine learning today.
 
Readership
 
Scholars and professionals interested in machine learning trends and research.
 

Demystifying Emerging Trends in Machine Learning

Pankaj Kumar Mishra

Satya Prakash Yadav

"Pragmatic Internet of Everything (IOE) has emerged as a powerful paradigm for representing and solving complex problems. This reference demonstrates how to coordinate behaviour among a collection of semi-autonomous problem-solving agents: how they can coordinate their knowledge, goals and plans to act together, to solve joint problems, or to make individually or globally rational decisions in the face of uncertainty and multiple, conflicting perspectives. 
 
 
 
The book presents a collection of articles surveying several major recent developments in Pragmatic Internet of Everything (IOE). The book focuses on issues and challenges that arise in building IOE systems for smart cities in real-world settings. It also presents solutions to the issues faced by system architects. The synthesis of recent thinking, both theoretical and applied, on major IOE problems makes this essential reading for anyone involved in the design and planning of IOT systems for smart cities.  
 
 
 
Key Features
 
-          Summarizes available literature and practical ventures with references
 
-          Merges different perspectives on IoT technology thereby giving a 360-degree perspective to the reader
 
-          Gives some tips for implementation of practical ventures in this space
 
-          Includes an analysis of information gathered from citizens of smart cities"


Pragmatic Internet of Everything (IOE) for Smart Cities: 360-Degree Perspective

"The book aims to provide a deeper understanding of the synergistic impact of Artificial intelligence (AI) and the Internet of Things (IoT) for disease detection. It presents a collection of topics designed to explain methods to detect different diseases in humans and plants. Chapters are edited by experts in IT and machine learning, and are structured to make the volume accessible to a wide range of readers.
 
 
 
Key Features:
 
-          17 Chapters present information about the applications of AI and IoT in clinical medicine and plant biology
 
-          Provides examples of algorithms for heart diseases, Alzheimer’s disease, cancer, pneumonia and more
 
-          Includes techniques to detect plant disease
 
-          Includes information about the application of machine learning in specific imaging modalities
 
-          Highlights the use of a variety of advanced Deep learning techniques like Mask R-CNN
 
-          Each chapter provides an introduction and literature review and the relevant protocols to follow
 
 
 
The book is an informative guide for data  and computer scientists working to improve disease detection techniques in medical and life sciences research. It also serves as a reference for engineers working in the healthcare delivery sector."


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Demystifying Emerging Trends in Green Technology

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Pankaj Kumar Mishra

Demystifying Emerging Trends in Machine Learning

Pankaj Kumar Mishra

Satya Prakash Yadav

Satya Prakash Yadav