Translational Edge and Cloud Computing to Advance Lake Water Quality Forecasting
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TR Number
Date
2024-11-20
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
In this article, we report on our experiences with interdisciplinary projects at the intersection of freshwater ecology, data science, and computer science. The translational research process has progressively led to the development of distributed systems that apply both edge computing and function-as-a-service (FaaS) cloud computing to support end-to-end water quality forecasting workflows across the edge-to-cloud continuum.
Description
Keywords
Cloud computing, Collaboration, Forecasting, Lakes, Next generation networking, Prototypes, Training, Translational research, Water quality