Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2582-8185 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

AI-driven innovations in energy efficiency: Transforming smart buildings and urban areas through technology and digital transformation

Breadcrumb

  • Home
  • AI-driven innovations in energy efficiency: Transforming smart buildings and urban areas through technology and digital transformation

Adua Habeebullah Tunde 1, Samuel Omokhafe Yusuf 2, *, Akerele Isaac Taiwo 3, Godbless Ocran 4, Peprah Owusu 4 and Adedamola Hadassah Paul-Adeleye 5

1 Independent Researcher, Maryland, USA.
2 Independent Researcher, Massachusetts, USA.
3 Independent Researcher, Texas, USA.
4 School of Business, Worcester Polytechnic Institute, Massachusetts, USA.
5 Independent Researcher, Alimosho, Lagos, Nigeria.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(01), 141–152
Article DOI: 10.30574/wjarr.2024.24.1.2921
DOI url: https://doi.org/10.30574/wjarr.2024.24.1.2921
 
Received on 15 August 2024; revised on 28 September 2024; accepted on 30 September 2024
 
This study explores AI's transformative role in enhancing urban energy efficiency. Focusing on AI-driven innovations in smart grids, renewable energy integration, and predictive energy management, it evaluates AI's potential to optimize energy distribution, reduce waste, and improve sustainability. A comprehensive literature review and case studies are employed to analyze the application.
The findings indicate that AI technologies, including machine learning and predictive analytics, are crucial for optimizing energy consumption, managing renewable energy variability, and improving smart grid efficiency. AI enhances sustainability by forecasting energy demand and optimizing storage systems. However, challenges such as data privacy concerns, integration complexities with existing infrastructure, and the need for specialized AI expertise pose barriers to broader adoption of these technologies.
The study recommends that future research focus on advancing AI technologies for real-time optimization and explainability, as well as addressing the skills gap in AI development. Policymakers and energy stakeholders should invest in AI-driven solutions and establish supportive regulations to promote AI adoption in urban energy systems. In the long term, AI will be pivotal in creating more sustainable, resilient, and energy-efficient cities.
 
Artificial Intelligence; Energy efficiency; Smart buildings; Digital Transformation
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-2921.pdf

Preview Article PDF

Adua Habeebullah Tunde, Samuel Omokhafe Yusuf, Akerele Isaac Taiwo, Godbless Ocran, Peprah Owusu and Adedamola Hadassah Paul-Adeleye. AI-driven innovations in energy efficiency: Transforming smart buildings and urban areas through technology and digital transformation. World Journal of Advanced Research and Reviews, 2024, 24(1), 141-152. Article DOI: https://doi.org/10.30574/wjarr.2024.24.1.2921

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 International Journal of Science and Research Archive - All rights reserved

Developed & Designed by VS Infosolution