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Green Artificial Intelligence and Machine Learning: Strategies for Sustainable Development
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Author(s): E. Indra (Mailam Engineering College, India), I. Vasudevan (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), M. Arthy (SRM Institute of Science and Technology, India), K. Hemakumar (Adhiparasakthi Engineering College, India), S. Deepa (R.M.D. Engineering College, India), A. Rizwanbasha (Panimalar Engineering College, India)and P. Girija (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India)
Copyright: 2025
Pages: 28
Source title:
Energy Efficient Algorithms and Green Data Centers for Sustainable Computing
Source Author(s)/Editor(s): P.J. Beslin Pajila (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), Belfin Robinson Vimala (University of North Carolina, USA), Y. Harold Robinson (Francis Xavier Engineering College, India)and C. Gopala Krishnan (GITAM University, India)
DOI: 10.4018/979-8-3373-0766-4.ch014
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Abstract
AI and Machine Learning technologies have been on the rise in the recent past, and as this happens, there have been growing concerns over the energy they consume and their carbon footprint. This paper offers a systematic literature review of Green AI and ML, which discusses approaches deployed to reduce the environmental impact of these technologies without compromising their effectiveness. We address the environmental impacts of largescale AI models and data centers categorizing energy efficient algorithms, model compression, and low power hardware as the main ways to approach the energy issue. Moreover, we discuss different aspects of AI usage for environmental protection with examples in renewable energy management, climate change tracking, and eco-friendly farming. Data management best practices including federated learning and sustainable dataset creation are also highlighted. Lastly, we discuss future research areas and trends that hold potential to improve the sustainability of AI and ML.
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