Current Volume 9
Green Artificial Intelligence: Energy-Efficient and Sustainable Approaches for Modern AI Systems
Abstract
The rapid advancement of Artificial Intelligence (AI) has significantly increased the computational power and energy required to train and deploy large-scale machine learning models. This growing demand contributes to higher electricity consumption and carbon emissions, raising concerns about the environmental sustainability of AI technologies. Green AI has emerged as a research paradigm that focuses on developing energy-efficient AI models, algorithms, and computing infrastructures while maintaining high performance and accuracy. This research project examines the principles of Green AI and explores techniques for reducing the environmental impact of AI systems, including model optimization, efficient hardware utilization, and sustainable data center practices. The study also evaluates the trade-off between model performance, computational cost, and energy consumption. By promoting energy-aware AI development, Green AI aims to create environmentally sustainable and cost-effective intelligent systems for future technological applications.
Citations
IRE Journals:
Isha Jagdale, Samreen Shaikh, Snehal Tajanpure, Abrashmeena Saikh "Green Artificial Intelligence: Energy-Efficient and Sustainable Approaches for Modern AI Systems" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 2172-2174 https://doi.org/10.64388/IREV9I11-1717851
IEEE:
Isha Jagdale, Samreen Shaikh, Snehal Tajanpure, Abrashmeena Saikh
"Green Artificial Intelligence: Energy-Efficient and Sustainable Approaches for Modern AI Systems" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717851
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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