Inteligencia artificial y sostenibilidad: innovación para el desarrollo sustentable y la eficiencia energética

The convergence between Artificial Intelligence (AI) and sustainable technologies is redefining the efficiency of energy and environmental systems. This study examines the impact of AI on renewable energy optimization, waste management and carbon footprint reduction. Using a mixed research approach, combining systematic literature review, quantitative data analysis and predictive modeling, key trends and emerging opportunities are identified. The findings confirm that AI improves operational efficiency by up to 35%, reduces resource waste by 30%, and contributes to the smart management of power grids and recycling systems. Challenges related to the high energy consumption of AI models and the need for adequate infrastructure for large-scale deployment are also discussed. It is shown that the use of machine learning algorithms can increase the operational efficiency of energy systems and improve waste management through computer vision techniques. Statistical analysis has also revealed a significant reduction in resource waste through the application of AI in the prediction and optimization of energy consumption.

Authors

Publication Details

Journal
Revista Metropolitana de Ciencias Aplicadas
Published
2025-03-26
DOI
https://doi.org/10.62452/whgwy586
Citations
1
Primary Topic
Environmental and Ecological Studies
Type
article
Field-Weighted Citation Impact
0.36
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article

Inteligencia artificial y sostenibilidad: innovación para el desarrollo sustentable y la eficiencia energética

Eduardo Samaniego Mena, Byron Oviedo, Ángel Iván Torres Quijije, Cristian Zambrano‐Vega
1 citations
Revista Metropolitana de Ciencias Aplicadas
Environmental and Ecological Studies
0.36
article

Inteligencia artificial y sostenibilidad: innovación para el desarrollo sustentable y la eficiencia energética

Eduardo Samaniego Mena, Byron Oviedo, Ángel Iván Torres Quijije, Cristian Zambrano‐Vega
article en
1 citations

Abstract

The convergence between Artificial Intelligence (AI) and sustainable technologies is redefining the efficiency of energy and environmental systems. This study examines the impact of AI on renewable energy optimization, waste management and carbon footprint reduction. Using a mixed research approach, combining systematic literature review, quantitative data analysis and predictive modeling, key trends and emerging opportunities are identified. The findings confirm that AI improves operational efficiency by up to 35%, reduces resource waste by 30%, and contributes to the smart management of power grids and recycling systems. Challenges related to the high energy consumption of AI models and the need for adequate infrastructure for large-scale deployment are also discussed. It is shown that the use of machine learning algorithms can increase the operational efficiency of energy systems and improve waste management through computer vision techniques. Statistical analysis has also revealed a significant reduction in resource waste through the application of AI in the prediction and optimization of energy consumption.

Revista Metropolitana de Ciencias AplicadasVol. 8(S1)
Openalex Percentile: Top 45%
Environmental and Ecological Studies
0.36
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