Special Issue: Envisioning Eco-Friendly Artificial Intelligence for a Sustainable Computing Environment

Green AI mainly focuses on the energy efficiency aspect of AI systems. This will lead the way for environmentally friendly scientific research with more innovative applications. However, AI research can be computationally expensive in several ways. And each provides tremendous opportunities for efficiency improvements. At the same time, AI has the required capabilities to solve computational sustainability problems. Even though the world has witnessed numerous advances in AI capabilities, it still has a long way to go regarding energy usage. Green AI enables smart decision-making across the decarbonizing industrial sectors and offers the best way to allocate alternative energy sources for the computing environment. Furthermore, the training of the AI models results in larger emissions, which may significantly impact the environment and climate change. The research on green AI aims to find novel approaches with reduced computational cost and rapidly reducing carbon emissions. It promotes energy efficiency, promotes carbon transparency, reduces the environmental impact, and finally leads to sustainable computing practices.

This special issue aims to investigate the use of green AI for a sustainable computing environment, its applications, and future research directions. We welcome researchers and practitioners working in this discipline to present their novel and unpublished research findings. The scope of the special issue includes, but is not limited to the following topics.


  1. Green AI and sustainable computing
  2. Challenges and opportunities of green AI for sustainable computing
  3. Effective ways of promoting energy efficiency in real-time AI applications
  4. Green AI for reducing carbon footprints
  5. Green algorithms for sustainable computing
  6. Energy efficient green AI for the future era
  7. Energy-efficient design systems for green AI applications
  8. Green algorithms for enhancing energy efficiency measures
  9. Low-power AI computing architectures for the future era
  10. Green AI for a sustainable future


→ Manuscript Submission Due: November 1, 2023

→ First-Round Acceptance Notification: January 15, 2024

→ Submission of Revised Version: March 15, 2024

→ Notification of Final Decision: April 15, 2024

→ Tentative publication date: To be defined later in accordance with CIT's publication schedule



Hamid Reza Rahbari, Department of Energy, Aalborg University, Denmark

Emails: hrr@energy.aau.dk, hamidrezarahbari16@gmail.com

Jiaqi Ruan, School of Science and Engineering, The Chinese University of Hong Kong, China

Email: jiaqiruan@link.cuhk.edu.cn



Prospective authors are directed to submit their manuscripts only through the Guest Editors, contacting them by the above e-mail(s). When submitting the manuscripts, it is imperative to follow the respective requirements listed on the following link:


The submitted manuscripts will be reviewed by at least two independent experts and the review process will be conducted through CIT's journal management system OJS