학술논문

Rural AI: Serverless-Powered Federated Learning for Remote Applications
Document Type
Periodical
Source
IEEE Internet Computing IEEE Internet Comput. Internet Computing, IEEE. 27(2):28-34 Apr, 2023
Subject
Computing and Processing
Artificial intelligence
Computational modeling
Urban areas
Federated learning
Data models
Computer architecture
Serverless computing
Rural areas
cyber-physical infrastructure
computing continuum
federated learning
Rural AI.
Language
ISSN
1089-7801
1941-0131
Abstract
With increasing connectivity to support digital services in urban areas, there is a realization that demand for offering similar capability in rural communities is still limited. To unlock the potential of artificial intelligence (AI) within rural economies, we propose rural AI—the mobilization of serverless computing to enable AI in austere environments. Inspired by problems observed in New Zealand, we analyze major challenges in agrarian communities and define their requirements. We demonstrate a proof-of-concept rural AI system for cross-field pasture weed detection that illustrates the capabilities serverless computing offers to traditional federated learning.