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
- Eduardo Samaniego Mena (ORCID: https://orcid.org/0000-0002-6196-2014)
- Byron Oviedo (ORCID: https://orcid.org/0000-0002-5366-5917)
- Ángel Iván Torres Quijije (ORCID: https://orcid.org/0000-0002-7037-7191)
- Cristian Zambrano‐Vega (ORCID: https://orcid.org/0000-0001-8568-8024)
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