Water Quality
Water quality research focuses on accurately monitoring and predicting water quality parameters to ensure safe and sustainable water resources. Current research employs diverse methods, including advanced sensor technologies for in-situ and remote sensing data collection, and sophisticated machine learning models such as LSTM networks, Random Forests, and hybrid deep learning architectures (CNN-RNN) for prediction and analysis of complex datasets. These advancements improve water quality monitoring and management, impacting public health, environmental protection, and resource allocation in various sectors like aquaculture and drinking water distribution. The integration of AI and IoT technologies is also enhancing real-time monitoring and predictive capabilities.
Papers
3D Water Quality Mapping using Invariant Extended Kalman Filtering for Underwater Robot Localization
Kaustubh Joshi, Tianchen Liu, Alan Williams, Matthew Gray, Xiaomin Lin, Nikhil Chopra
WaterQualityNeT: Prediction of Seasonal Water Quality of Nepal Using Hybrid Deep Learning Models
Biplov Paneru, Bishwash Paneru