Ecological sustainability based on artificial intelligence and green technologies

Main Article Content

Asmar Sadikhova

Abstract

The rapid development of artificial intelligence (AI) and green technologies has created new opportunities for addressing global environmental challenges and promoting ecological sustainability. This article explores the role of AI-driven solutions in enhancing the efficiency of green technologies, optimizing resource management, reducing environmental risks, and supporting sustainable development strategies. Particular attention is given to the application of AI in renewable energy systems, environmental monitoring, waste management, and climate change mitigation. The study emphasizes that the integration of artificial intelligence with green technologies not only improves technological performance but also contributes to informed decision-making, long-term environmental protection, and the transition toward a sustainable and resilient ecological system.


Google Scholar


Article Details

How to Cite
Sadikhova , A. (2026). Ecological sustainability based on artificial intelligence and green technologies. Scientific Collection «InterConf», (282), 210–215. Retrieved from https://archive.interconf.center/index.php/conference-proceeding/article/view/7888

References

Bolón-Canedo, V., Morán-Fernández, L., Cancela, B., & Alonso-Betanzos, A. (2024). A review of green artificial intelligence: Towards a more sustainable future. Neurocomputing, 599, 128096. https://doi.org/10.1016/j.neucom.2024.128096

Dhiman, R., Miteff, S., Wang, Y., Ma, S.-C., Amirikas, R., & Fabian, B. (2024). Artificial Intelligence and Sustainability—A Review. Analytics, 3(1), 140–164. https://doi.org/10.3390/analytics3010008

Shoaei, M., Noorollahi, Y., Hajinezhad, A., & Moosavian, S. F. (2024). A review of the applications of artificial intelligence in renewable energy systems: An approach-based study. Energy Conversion and Management, 306, 118207. https://doi.org/10.1016/j.enconman.2024.118207

Judge, M. A., Franzitta, V., Curto, D., Guercio, A., Cirrincione, G., Khattak, H. A. (2024). A comprehensive review of artificial intelligence approaches for smart grid integration and optimization. Energy Conversion and Management: X, 24, 100724. https://doi.org/10.1016/j.ecmx.2024.100724

Raut, S., Hossain, N. U. I., Kouhizadeh, M., & Fazio, S. A. (2025). Application of artificial intelligence in circular economy: A critical analysis of the current research. Sustainable Futures, 9, 100784. https://doi.org/10.1016/j.sftr.2025.100784

Deng, Y., Zhang, Y., Pan, D., Yang, S. X., & Gharabaghi, B. (2024). Review of Recent Advances in Remote Sensing and Machine Learning Methods for Lake Water Quality Management. Remote Sensing, 16(22), 4196. https://doi.org/10.3390/rs16224196

United Nations Environment Programme (UNEP). (2024, September 21). Artificial Intelligence (AI) end-to-end: The Environmental Impact of the Full AI Lifecycle Needs to be Comprehensively Assessed (Issue note).

Rao, R., Singh, S., Salas, M., Sarker, A., Kumar, R., Wang, Y., Lucia, L., Mittal, A., Yarbrough, J., Barlaz, M. A., Singh, A., & Pal, L. (2025). AI-powered municipal solid waste management: a comprehensive review from generation to utilization. Frontiers in Energy Research, 13. https://doi.org/10.3389/fenrg.2025.1670679.