Year: 2025
Type: article
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
Author: Olayinka Akinbolajo
Institution: Texas A&M University – Kingsville
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407592180