Translational Edge and Cloud Computing to Advance Lake Water Quality Forecasting
Published in IEEE Computing in Science & Engineering, 2024
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.
Recommended citation: Renato J. Figueiredo, Cayelan C. Carey, R. Quinn Thomas, “Translational Edge and Cloud Computing to Advance Lake Water Quality Forecasting”, IEEE Computing in Science & Engineering, 2024 10.1109/MCSE.2024.3430148