Work

Application of Deep Learning in Monitoring Environmental Risks in Renewable Energy Projects

Year: 2025

Type: conference-paper

Abstract: The integration of renewable energy sources like solar and wind is vital for sustainable energy, but these systems carry environmental risks that require advanced monitoring. Traditional methods often fail in real-time assessment, prompting the need for more accurate predictive models. This literatu

DOI: 10.4108/eai.3-10-2024.2356242

Authors: Suhendra Suhendra, Asmida Herawati

Institution: National Chung Hsing University

Language: English

Topic: Environmental and Industrial Safety

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action, Industry, innovation and infrastructure

Open Access status: gold

OpenAlex ID: W4414706457

FWCI:

Cites:

Cited by:

Related to: