Key and enabling digital tools and solutions can boost the digital transformation of economies and societies and support achieving the Sustainable Development Goals (SDGs) by 2030. The outcomes of digital innovation must be in line with responsible research and innovation. How can advanced information technologies, including artificial intelligence, blockchain, edge computing, the next generation of the internet of things (NGIoT), IoT, machine learning, and robotics, create digital tools and solutions to build more resilient, climate-neutral, and green economies and societies?

5G, Artificial Intelligence, and Next Generation Internet of Things: Digital Innovation for Green and Sustainable Economies offers innovative conceptual frameworks and theories, case studies, and empirical studies to understand digital innovation and how digital and industrial technologies can accelerate the digital and green transition with multidisciplinary and trans-disciplinary approaches. The book studies how digital tools and solutions can impact the achievement of the Sustainable Development Goals (SDGs) worldwide, focusing on the Asian region. Featuring research on topics such as 5G, artificial intelligence, blockchain, circular economy, green economy, climate-neutral economy, human-centered approach, robotics, geographical focus, and methodologies, this book is ideally designed for academics, researchers, industry players, policymakers, students, academics, experts on IT, CEOs, policymakers, and other relevant stakeholders worldwide.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

5G/6G Networks
Applications in Key Sectors (Agriculture, Education, Energy, Manufacturing, Mobility, Healthcare, Smart Cities).
Artificial Intelligence
Asia-EU/Africa/Gulf Region/Latin America Collaboration
Business
Case Studies and Comparative Studies
Circular Economy
Climate Neutral Economies
Data
Data Economy
Digital Connectivity
Digital Connectivity Infrastructures
Digital Economy
Edge Computing
Ethics
Green Growth
Human-Centered Approach
Inclusion
Information Technologies
Internet of Things
Knowledge Management for Different Economic Sectors
Machine Learning
Management
Next Generation of Internet of Things (NGIoT)
Open Innovation
Privacy and Security Issues
Robotics
Smart Communities
Sustainable Development Goals (SDGs)

Reviews & Statements

The chapter presents a groundbreaking exploration of how machine learning-enhanced text mining can revolutionize climate change research. It delves into the intricate process of analyzing climate disclosures, employing advanced techniques like natural language processing (NLP) and machine learning (ML) to extract meaningful insights from vast textual data. The chapter highlights the critical role of text mining in identifying and managing climate-related risks, showcasing its potential as a tool for environmental analysis and policy-making. It also illuminates how knowledge graphs, in conjunction with NLP and ML, can play a transformative role in climate change research. By integrating knowledge graphs, the research goes beyond traditional data analysis, creating a dynamic, interconnected data structure that enhances the understanding of complex climate information. This synergy of NLP, ML, and knowledge graphs not only improves data analytics but also opens new avenues for insightful environmental research, making this work a vital addition to the AI and machine learning domain. This work stands as a significant contribution to the field of AI, offering novel methodologies and insights for tackling one of the most pressing global challenges.

– Dr. Nikodem Rybak, Artificial Intelligence Program Leader, University of Queensland, Australia

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Editor/Author Biographies

Patricia Ordóñez de Pablos is a professor in the Department of Business Administration in the Faculty of Business and Economics at The University of Oviedo, Spain. She completed her education in The London School of Economics, UK. Her teaching and research interests focus on the areas of strategic management, knowledge management, organizational learning, human resource management, intellectual capital, information technologies, with special interest in Asia (Bhutan, China, Laos, Myanmar). She is Editor-in-Chief of the International Journal of Learning and Intellectual Capital (IJLIC) and International Journal of Asian Business and Information Management (IJABIM), respectively. She has edited books for IGI Global, Elsevier, Routledge, and Springer. In 2021, she earned placement on Stanford University’s “Ranking of the World Scientists: World’s Top 2% Scientists” list.

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