Low-cost Sensing Methods and Hybrid Learning Approaches for Water Quality Monitoring (Old ID 27164)
Role
Principal Investigator
Description
This project aims to investigate innovative solutions for low-cost water quality monitoring by utilising state-of-the-art Internet of Things and Artificial Intelligence technologies. This project expects to generate new knowledge in the area of artificial intelligent Internet of Things using interdisciplinary approaches. Expected outcomes of this project include novel low-cost alternative sensing methods and new hybrid learning network models for sensory data predictive analytics. This should provide significant national benefits, such as substantially reduced costs and improved accuracy for real-time monitoring of the Great Barrier Reef.
Date
01 Jan 2022 - 31 Dec 2024
Project Type
GRANT
Keywords
Water Quality
Funding Body
Australian Research Council (ARC)
Amount
50000
Project Team
N/A