2026-04-13T15:09:02Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4600642026-04-06T01:03:11Zcom_2072_1033col_2072_452950

A review on green deployment for edge AI - Abstract Rey Juárez, Santiago del Martínez Fernández, Silverio Juan Franch Gutiérrez, Javier Universitat Politècnica de Catalunya. Doctorat en Computació Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Services, Information and Data Engineering Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial Edge computing Energy-efficiency Deployment Edge AI Green AI The convergence of edge computing and Artificial Intelligence, namely Edge AI, offers many opportunities to the industry for building competitive and innovative business models. However, this new paradigm has its own challenges in terms of latency, privacy, and energy. The latter is relevant considering that current AI requires expensive computation that is hard to achieve in existing edge devices. This work reviews 20 studies published between December 2018 and March 2023 on the subject of energy efficiency for the deployment of Edge AI. Most of the publications are devoted to improving the efficient deployment of Edge AI, while only a few focus on measuring the carbon footprint and energetic impact. Our work can help researchers quickly understand the state-of-the-art and learn which topics need more research. This work is part of the GAISSA project (TED2021-130923B-I00), which is funded by MCIN/AEI/10.13039/501100011033 and by the European Union ”NextGenerationEU”/PRTR. Peer Reviewed Postprint (published version) 2023 Conference lecture Del Rey, S.; Martínez-Fernández, S.; Franch, X. A review on green deployment for edge AI - Abstract. A: International Conference on ICT for Sustainability. «Joint Proceedings of ICT4S 2023 Doctoral Symposium, Demonstrations & Posters Track and Workshops: co-located with 9th International Conference on Information and Communications Technology for Sustainability (ICT4S 2023): Rennes, France, June 05-09, 2023». CEUR-WS.org, 2023, p. 64-67. ISSN 1613-0073. 1613-0073 https://hdl.handle.net/2117/460064 eng https://ceur-ws.org/Vol-3562/ info:eu-repo/grantAgreement/AEI/PLAN ESTATAL DE INVESTIGACIÓN CIENTÍFICA Y TÉCNICA Y DE INNOVACIÓN 2021-2023/TED2021-130923B-I00/GAISSA. Transición hacia sistemas de software verdes basados en IA: un enfoque centrado en arquitectura http://creativecommons.org/licenses/by/4.0/ Open Access Attribution 4.0 International 4 p. application/pdf CEUR-WS.org