Explainable AI (XAI) for Sustainable Development

Trends and Applications

Lakshmi D,Ravi Shekhar Tiwari,Rajesh Kumar Dhanaraj,Seifedine Kadry

• Publisher: Chapman and Hall/CRC
• Year: 2024
• ISBN:
  9781040038871
• Edition: 1
• Topic: Tecnologia e ingegneria
• Subtopic: Automazione in ingegneria

This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain.

• Focuses on virtual machine placement and migration techniques for cloud data centres

• Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services

• Includes application of placement techniques for quality of service, performance, and reliability improvement

• Explores data centre resource management, load balancing and orchestration using machine learning techniques

• Analyses dynamic and scalable resource scheduling with a focus on resource management

The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Editor Biographies
• Contributors
• Chapter 1 Sustainable AI: Environmental Implications, Challenges, and Opportunities
• Chapter 2 Artificial Intelligence of Things (AIoT) in Agriculture 4.0
• Chapter 3 EXAI for Computational Sustainability – Models, Services in Smart City, and Challenges
• Chapter 4 Impact of Artificial Intelligence and Emotional Intelligence in Autonomous Operation and MSME Entrepreneurs’ Performance in the Waste Management Industry
• Chapter 5 Artificial Intelligence Governance and Comprehensibility in Renewable Energy Systems
• Chapter 6 Exploring EEG Characteristics and Machine Learning Classifiers for Accurate Detection of Eye-Blink Mistakes
• Chapter 7 Machine Learning Advancements in Polymer Material Creation: Successful Prediction of Glass Transition Temperature
• Chapter 8 Smart Greenhouse Management System Using AIoT for Sustainable Agriculture
• Chapter 9 CardioSegNet Meets XAI: A Breakthrough in Left Ventricle Delineation within Cardiac Diagnostics
• Chapter 10 Artificial Intelligence-Based Techniques for Early Detection of Chiari Malformation
• Chapter 11 AI-Driven Restoration: Enhancing Biodiversity Conservation and Ecosystem Resilience
• Chapter 12 Improvised DenseNet and Faster RCNN for Assisting Agriculture 4.0
• Chapter 13 Libraries for Explainable Artificial Intelligence (EXAI): Python
• Chapter 14 Trends and Advancements of AI and XAI in Drug Discovery
• Chapter 15 An In-Depth Analysis of the Potential of AIoT to Improve Agricultural Productivity and Long-Term Sustainability
• Chapter 16 Introduction to Deployable AI for Cutting-Edge Technologies: An Overview, Scope, Opportunities, and Challenges
• Chapter 17 The Role of AIoT in Reshaping the Farming Sector
• Chapter 18 Unleashing the Power of XAI (Explainable Artificial Intelligence): Empowering Decision-Making and Overcoming Challenges in Smart Healthcare Automation
• Index