Privacy-Preserving Water Quality Forecasting Using Federated Learning Across Distributed Water Monitoring Nodes and Optimized RPART Modelling | Synapse
Utilizing federated learning enhances water quality prediction accuracy while preserving data privacy.
Forecasting results from optimized RPART modelling show significant improvements in prediction efficiency.
Distributed monitoring nodes play a critical role in managing water quality by providing real-time data.
This privacy-preserving technique could revolutionize environmental management practices in polluted areas.
Abstract
Water quality prediction is a highly important task in the anticipation and management of a polluted environment. An accurate prediction can help to assist the water quality environment to make...