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Achieving Green Sustainability in Computing Devices in Machine Learning and Deep Learning Techniques
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Author(s): S. Sharanya (Data Science and Business Systems, SRM Institute of Science and Technology, India), V. Vijayalakshmi (Data Science and Business Systems, SRM Institute of Science and Technology, India)and R. Radha (Data Science and Business Systems, SRM Institute of Science and Technology, India)
Copyright: 2024
Pages: 15
Source title:
Computational Intelligence for Green Cloud Computing and Digital Waste Management
Source Author(s)/Editor(s): K. Dinesh Kumar (Amrita Vishwa Vidyapeetham, India), Vijayakumar Varadarajan (The University of New South Wales, Australia), Nidal Nasser (College of Engineering, Alfaisal University, Saudi Arabia)and Ravi Kumar Poluru (Institute of Aeronautical Engineering, India)
DOI: 10.4018/979-8-3693-1552-1.ch009
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Abstract
The accelerated growth in artificial intelligence, internet of devices, machine learning (ML), and deep learning at breakneck speed has attracted the attention of researchers in developing novel green solutions for reclaiming the green society. The intersection of these technologies with green sustainability will greatly impact the deployment of cutting-edge technologies with green solutions. Leveraging ML technologies to improve engineering techniques to reduce the toxins released in the environment in various forms is discussed in this work. The predominant area of focus is applying is developing green AI-based solutions with sustainability measures and metric in mind. The primary contribution of this work is the holistic analysis of the employment of green ML and deep learning techniques in fostering a sustainable environment. The potential scope of this research is to benefit the research community in developing novel ML and deep learning technologies for improving green sustainability.
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