An AI-Driven Framework for Optimizing Energy Consumption

The increasing demand for energy, coupled with the need for sustainable development, has necessitated the development of innovative solutions to optimize energy consumption. This paper presents an AI-driven framework designed to enhance energy efficiency across various sectors, including residential, commercial, and industrial environments. The framework leverages machine learning algorithms, Internet of Things (IoT) devices, and big data analytics to monitor, predict, and control energy usage in real-time. By integrating these technologies, the proposed framework aims to reduce energy waste, lower operational costs, and minimize environmental impact. The paper discusses the architecture of the framework, its key components, and the potential benefits of its implementation. Additionally, case studies and experimental results are presented to demonstrate the effectiveness of the framework in optimizing energy consumption

Authors

Institutions

Publication Details

Journal
International Journal of Advances in Engineering and Management
Published
2025-02-01
DOI
https://doi.org/10.35629/5252-07022124
Primary Topic
Energy Efficiency and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An AI-Driven Framework for Optimizing Energy Consumption

Olayinka Akinbolajo
International Journal of Advances in Engineering and Management
Energy Efficiency and Management
article

An AI-Driven Framework for Optimizing Energy Consumption

Olayinka Akinbolajo
article en

Abstract

The increasing demand for energy, coupled with the need for sustainable development, has necessitated the development of innovative solutions to optimize energy consumption. This paper presents an AI-driven framework designed to enhance energy efficiency across various sectors, including residential, commercial, and industrial environments. The framework leverages machine learning algorithms, Internet of Things (IoT) devices, and big data analytics to monitor, predict, and control energy usage in real-time. By integrating these technologies, the proposed framework aims to reduce energy waste, lower operational costs, and minimize environmental impact. The paper discusses the architecture of the framework, its key components, and the potential benefits of its implementation. Additionally, case studies and experimental results are presented to demonstrate the effectiveness of the framework in optimizing energy consumption

International Journal of Advances in Engineering and ManagementVol. 7(2)
Klinik und Poliklinik für Psychosomatik und Psychotherapie (DE)
Openalex Percentile: Top 98%
Energy Efficiency and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An AI-Driven Framework for Optimizing Energy Consumption — Olayinka Akinbolajo · International Journal of Advances in Engineering and Management (2025) | TGRS Research Map | TGRS