Call for Chapters: Artificial Intelligence and Data Science for Sustainability: Applications and Methods

Editors

Muhammad Syafrudin, Department of Artificial Intelligence and Data Science, Sejong University, Korea, Republic Of
Norma Latif Fitriyani, Department of Artificial Intelligence and Data Science, Sejong University, Korea, Republic Of
Muhammad Anshari, Universiti Brunei Darussalam School of Busines, Brunei Darussalam

Call for Chapters

Proposals Submission Deadline: July 31, 2024
Full Chapters Due: September 15, 2024
Submission Date: September 15, 2024

Introduction

The proposed publication, titled "Artificial Intelligence and Data Science for Sustainability: Applications and Methods," aims to explore the applications of artificial intelligence (AI) and Data Science (DS) techniques and methodologies in addressing various sustainability challenges. The book will bring together cutting-edge research, case studies, and practical applications that demonstrate how AI can be leveraged to promote sustainable development across diverse domains, such as energy, transportation, agriculture, waste management, urban planning, and environmental protection. The publication will delve into the intersection of AI, DS, and sustainability, showcasing how AI and DS technologies, including machine learning, deep learning, computer vision, natural language processing, and optimization algorithms, can be harnessed to develop innovative solutions for environmental, economic, business, and social sustainability challenges.

Objective

This publication will have a significant impact on the research community by bringing together researchers and practitioners from various fields, including business & economics, management, computer science, environmental science, engineering, urban planning, and sustainable development, the book will promote cross-pollination of ideas and facilitate interdisciplinary collaborations.

Target Audience

The primary intended audience for this publication includes Researchers and scholars from various disciplines, such as computer science, environmental science, engineering, urban planning, and sustainable development, who are interested in exploring the applications of AI and DS for sustainability. Professionals working in industries related to sustainability, such as energy, transportation, agriculture, waste management, and urban planning, who seek to understand and implement AI-driven solutions for sustainable practices. Government officials, policymakers, and decision-makers involved in sustainability initiatives and environmental policies, who can benefit from insights and recommendations on leveraging AI and DS for sustainable development. Students pursuing advanced degrees in relevant fields, such as computer science, environmental science, engineering, and sustainable development, who are interested in exploring the intersection of AI and sustainability.

Recommended Topics

Recommended topics include, but are not limited to, the following:


1. AI or DS for Energy Efficiency and Renewable Energy Management
• Predictive modeling and optimization for energy systems
• AI or DS-driven smart grids and demand-side management
• AI or DS for renewable energy forecasting and integration
• Machine learning for energy storage and distribution

2. AI or DS-driven Smart Cities and Sustainable Urban Planning
• AI or DS for urban traffic management and transportation optimization
• Machine learning for urban environmental monitoring and modeling
• AI or DS-enabled smart buildings and energy-efficient infrastructure
• AI or DS for urban waste management and circular economy

3. AI or DS in Sustainable Agriculture and Food Production
• Machine learning for precision agriculture and crop yield optimization
• AI or DS for sustainable water management and irrigation systems
• Computer vision for plant disease detection and monitoring
• AI or DS-driven supply chain optimization and food waste reduction

4. AI or DS for Waste Management and Circular Economy
• Machine learning for waste sorting and recycling optimization
• AI or DS-driven waste management and resource recovery systems
• Predictive modeling for waste generation and disposal patterns
• AI or DS for sustainable product design and lifecycle management

5. AI or DS for Sustainable Transportation and Logistics
• AI or DS-enabled route optimization and fleet management
• Predictive modeling for transportation demand and emissions
• Machine learning for autonomous and electric vehicle optimization
• AI or DS for sustainable last-mile delivery and logistics

6. AI or DS in Environmental Monitoring and Protection
• Remote sensing and computer vision for environmental monitoring
• Machine learning for air, water, and soil quality monitoring
• AI or DS-driven biodiversity conservation and habitat management
• AI or DS for climate change modeling and mitigation strategies

7. Ethical Considerations and Responsible AI or DS for Sustainability
• AI or DS governance and ethical frameworks for sustainable development
• Bias and fairness in AI or DS systems for sustainability applications
• Privacy and security implications of AI or DS in sustainability contexts
• Responsible AI or DS for inclusive and equitable sustainable development



Submission Procedure

Researchers and practitioners are invited to submit on or before July 31, 2024, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by August 16, 2024 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by September 15, 2024, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Artificial Intelligence and Data Science for Sustainability: Applications and Methods. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.



Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2025.



Important Dates

July 31, 2024: Proposal Submission Deadline
August 16, 2024: Notification of Acceptance
September 15, 2024: Full Chapter Submission
November 17, 2024: Review Results Returned
December 29, 2024: Final Acceptance Notification
January 12, 2025: Final Chapter Submission



Inquiries

Muhammad Syafrudin
Department of Artificial Intelligence and Data Science, Sejong University
udin@sejong.ac.kr

Norma Latif Fitriyani
Department of Artificial Intelligence and Data Science, Sejong University
norma@sejong.ac.kr

Muhammad Anshari
Universiti Brunei Darussalam School of Business
anshari.ali@ubd.edu.bn



Classifications


Business and Management; Computer Science and Information Technology; Education; Life Sciences; Library and Information Science; Medicine and Healthcare; Media and Communications; Security and Forensics; Government and Law; Social Sciences and Humanities; Physical Sciences and Engineering
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