Advancing the Clean Energy Frontier Through AI-Powered Green Innovation: 9798337355405: Physical Sciences & Engineering Books

Publication Status: E-Book and Print Version Available for Purchase

ISBN13: 9798337355405

ISBN13 Softcover: 9798337355412

EISBN13: 9798337355429

DOI: 10.4018/979-8-3373-5540-5

Description:

The convergence of artificial intelligence (AI) and clean energy innovation transforms global sustainability efforts. As climate challenges and growing energy demands increase, AI-powered technologies emerge as catalysts for efficiency, scalability, and smart decision-making for green energy. From optimizing renewable energy to predict fluctuations and accelerating materials discovery, AI redefines the clean energy frontier. By integrating data-driven intelligence with sustainable engineering, this new wave of innovation may reduce carbon emissions while reshaping the way organizations harness and manage energy for a cleaner, smarter planet.

Advancing the Clean Energy Frontier Through AI-Powered Green Innovation explores how AI accelerates the development and deployment of clean energy technologies, serving as a catalyst for a sustainable energy transition. It examines AI-driven innovations, addressing ethical imperatives like data equity, algorithmic bias, and inclusive access. This book covers topics such as renewable energy, machine learning, and sustainable transport, and is a useful resource for engineers, business owners, academicians, researchers, and data scientists.

Coverage:

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

Artificial Intelligence (AI)
Clean Energy
Climatology
Data Science
Electric Vehicles
Energy Engineering
Ethics and Law
Financial Literacy
Green Technology
Grid Optimization
Machine Learning
Remote Sensing
Renewable Energy
Satellite Technology
Smart Cities
Sustainable Development
Sustainable Transport
Waste Management

Search this Book:

Reset

Indexing

Ben Othman Soufiene is an Assistant Professor of computer science at the Applied College, King Faisal University, Saudi Arabia. He received his Ph.D. degree in computer science from Manouba University in 2016 for his dissertation on “Secure data aggregation in wireless sensor networks. He also holds M.S. degrees from the Monastir University in 2012. My research interests focus on the Internet of Medical Things, Wireless Body Sensor Networks, Wireless Networks, Artificial Intelligence, Machine Learning and Big Data. Dr. Ben Othman has published more than 160 papers at reputed international journals, conferences, and book chapters. He is an Editorial Board Member in the different Journals and Conferences. He serves as an associate editor/academic editor for international journals including IEEE Access, IEEE Sensors, IEEE Internet of Things, Elsevier, Springer, Taylor & Francis, IGI, IET, Telecommunication Computing Electronics and Control, and Wiley. Dr. Ben Othman is a Technical Program Committee Member for more than a dozen of international conferences.

Dr. Mohieddine Rahmouni , Ph.D., is an Associate Professor of Economics at the Applied College, King Faisal University (Al-Ahsa, Saudi Arabia), and at the High School of Economic and Commercial Sciences of Tunis (ESSECT), University of Tunis, Tunisia. He earned his Ph.D. in Economics through a joint doctoral program between the University of Montesquieu Bordeaux IV (now the University of Bordeaux), France, and the University of Tunis. His research lies at the intersection of innovation economics, applied econometrics, productivity analysis, and industrial dynamics, with a particular focus on economic development and structural transformation in emerging economies. Dr. Rahmouni’s scholarly work has been published in reputable international journals such as Structural Change and Economic Dynamics, the Journal of Industrial and Business Economics, and the International Journal of Innovation and Technology Management. His research explores the role of external knowledge sources, the determinants of innovation performance, and the policy mechanisms that influence firm-level productivity and competitiveness. Through rigorous empirical analysis, he contributes to advancing the understanding of how innovation systems and policy frameworks shape economic growth and industrial development in transitioning and emerging markets.

All IGI Global Scientific Publishing content is archived via the CLOCKSS and LOCKSS initiative. Additionally, all IGI Global Scientific Publishing published content is available in the IGI Global Scientific Publishing InfoSci® platform.

We are committed to continually improving our platform to meet WCAG standards. We have used automated scans as well as manual review to identify and resolve compatibility issues. Our goal is to ensure all of our content is easily accessible to all users.

Current Accessibility Implementations
Screen reader compatible web pages with properly labeled elements.
Text alternatives for non-text content so it can be changed into large print, braille, speech, symbols, or simpler language.
User interface can be navigated using only a keyboard - no keyboard traps.
Consistent navigation on all web pages.
Meaningful section heading are used to organize content in a logical manner.
Logical focus order of elements on each web page.
No web pages contain any flashing, or design elements that are known to cause seizures or physical reactions.
Text has high contrast, with a contrast ratio of at least 4.5:1.
Responsive design, with text that can be resized without loss of content or functionality.

Learn More