Role of machine learning in attaining environmental sustainability

P. Asha; Kasiprasad Mannepalli; Rashmita Khilar; N. Subbulakshmi; R. Dhanalakshmi; Vikas Tripathi; V. Mohanavel; Ravishankar Sathyamurthy; M. Sudhakar

Energy Reports (Nov 2022)

Role of machine learning in attaining environmental sustainability

P. Asha,
Kasiprasad Mannepalli,
Rashmita Khilar,
N. Subbulakshmi,
R. Dhanalakshmi,
Vikas Tripathi,
V. Mohanavel,
Ravishankar Sathyamurthy,
M. Sudhakar

Affiliations

P. Asha: Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu 600119, India
Kasiprasad Mannepalli: Department of Electronics & Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram Guntur, Andhra Pradesh 522502, India
Rashmita Khilar: Department of Information Technology, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu 600124, India
N. Subbulakshmi: Post Doc Fellow, Department of CSE, Indian Institute of Technology Guwahati, Assam, India
R. Dhanalakshmi: Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu 600124, India
Vikas Tripathi: Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand 248002, India
V. Mohanavel: Centre for Materials Engineering and Regenerative Medicine, Bharath Institute of Higher Education and Research, Chennai-600073, Tamil Nadu, India; Department of Mechanical Engineering, School of Technology, Glocal University, Delhi-Yamunotri Marg, Uttar Pradesh, 247121, India
Ravishankar Sathyamurthy: Department of Mechanical Engineering, KPR Institute of Engineering and Technology, Coimbatore, Arasur 641407, Tamil Nadu, India; Department of Mechanical Engineering, University Centre for Research & Development, Chandigarh University, Gharuan, Mohali, Punjab, India
M. Sudhakar: Department of Mechanical Engineering, Sri Sai Ram Engineering College, Chennai 600044, Tamil Nadu, India; Corresponding author.

Journal volume & issue: Vol. 8
pp. 863 – 871

Abstract

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Climate change and sustainable development are significant challenges that must be addressed as soon as possible. As a result of this vision, the renewable energy (RE) industry has experienced great growth, with artificial intelligence being applied to improve its overall efficiency (AI). However, when it comes to achieving the sustainable development goals (SDGs), they are not sufficiently explored or considered. Countries all across the world are seeking to achieve 100% renewable energy by 2050, and this is a goal shared by a large number of other nations. More research is needed to evaluate whether renewable energy (RE) can assist us in meeting our sustainable development goals, given that it has lately experienced a considerable increase in popularity and is having an increasing impact on the global energy industry. In addition, an assessment of AI potential contribution to the achievement of the Sustainable Development Goals is being carried out. In this paper, we develop a machine learning model using Regression Kriging to classify the radiative energy flux at the earth surface in order of attaining environmental sustainability using solar panels. Various factors are given as input to the model that takes into account the modelling of data in obtaining the environmental sustainability. The simulation is conducted to test the efficacy of the model in obtaining the environmental sustainability and the results shows improved sustainability than other methods.

Published in Energy Reports

ISSN: 2352-4847 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: http://www.journals.elsevier.com/energy-reports/

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