Universitat Politècnica de Catalunya
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
2023
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)
Conference lecture
English
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
CEUR-WS.org
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
E-prints [72986]
