Energy efficiency and conservation using machine learning

Title

Energy efficiency and conservation using machine learning

Creator

Ramakrishnan A.B.; Murugesh T.S.; Pulari S.R.; Vasudevan S.K.; G.K. A.

Description

This chapter explores the fascinating nexus between machine learning (ML), energy efficiency, and conservation, concentrating on a captivating case study that makes use of the oneAPI framework. Optimizing energy consumption has become crucial due to the increased interest in sustainable practices. By investigating the use of oneAPI in energy efficiency projects, we examine the possibility of ML techniques to overcome this difficulty. We demonstrate how ML algorithms can accurately model and anticipate energy usage patterns through a thorough analysis of real-world data. Additionally, we discuss the importance of feature engineering, algorithm selection, and data pretreatment in creating accurate energy consumption models. The case study emphasizes the wider implications of utilizing ML to support energy-saving initiatives in addition to demonstrating the effectiveness of oneAPI. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.

Source

Green Machine Learning and Big Data for Smart Grids: Practices and Applications, pp. 69-78.

Date

2024-01-01

Publisher

Elsevier

Subject

computational intelligence; conservation; data preprocessing; energy consumption; energy efficiency; energy management; energy sustainability; Machine learning; modeling; oneAPI; optimization; prediction; sustainable development; sustainable practices

Coverage

Ramakrishnan A.B., Deparment of Computer Science and Engineering, SASTRA Deemed to be University, SASTRA University Thanjavur Campus, Tamil Nadu, Thanjavur, India; Murugesh T.S., Department of Electronics and Communication Engineering, Government College of Engineering Srirangam, Tamil Nadu, Tiruchirappalli, India; Pulari S.R., Tutor, Bahrain Polytechnic, Bahrain; Vasudevan S.K., Technical Evangelist, APJ, SP&E - Developer Platform and Evangelism, Software and Advanced Technology Group, Intel India Pvt. Ltd., Karnataka, Bengaluru, India; G.K. A., Master of Computer Aplications, Christ University, Karnataka, Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 978-044328951-4; 978-044328952-1

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1016/B978-0-443-28951-4.00006-X

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214175965&doi=10.1016%2fB978-0-443-28951-4.00006-X&partnerID=40&md5=4c6cc7ef7c3b5991f3194de12b989916