Theme 3
Advanced Analysis and Visualisation of Integrated Datasets
Researching advanced analytical methodologies and develop models to help validate, interpret and visualise integrated datasets. We will design a digital twin platform, empowering decision-makers to conduct simulations and enabling fully informed scenario-based planning and asset optimization
About the Project
Theme 3 focuses on developing advanced analytical tools, models and visualisation methods to make sense of the diverse and complex data generated across the IoT water system. This includes building a digital twin platform that mirrors real-world environments, enabling simulated testing, scenario planning and interactive engagement with sensor networks and communication technologies. Through this integrated digital environment, we support sensor development, evaluate communication performance and provide communities and stakeholders with intuitive ways to explore, understand and trust the data.
A key component of this theme is strengthening the reliability, trustworthiness and governance of sensor data. This involves creating frameworks for validating data quality, detecting anomalies using machine learning and ensuring robust cross-validation between sensors. The theme also works to unify data governance across operational technology (OT), IT and IoT systems, establishing consistent standards and scalable models for managing data across the water sector. Together, these efforts enable accurate insights, stronger decision-making and effective, whole-of-system digital integration.
Project Objectives
Digital Twin Development
Create an interactive digital twin platform that mirrors real-world water systems, enabling simulation, testing and scenario-based planning for improved decision-making.
Advanced Data Visualisation
Design intuitive visual tools that transform complex, multi-source datasets into clear, actionable insights for researchers, operators and community stakeholders.
Data Trust & Quality Assurance
Implement robust frameworks to validate sensor data, detect anomalies and ensure the accuracy and reliability of information used across IoT water applications.
Integrated Knowledge Discovery
Use machine learning and cross-validation methods to uncover patterns, trends and operational insights from integrated datasets, supporting smarter asset management.
Unified Data Governance
Develop a scalable governance framework that aligns OT, IT and IoT systems, ensuring consistent data handling, secure information flows and industry-wide interoperability.
Real-Time Risk & Response Tools
Build rapid decision-support tools that integrate live data to support emergency response, operational resilience and proactive management of water system risks.
Key Milestones
No milestones available
Meet Our Visionary Team
Prof Michael Sheng
Deputy Director
Prof. Michael Sheng's research interests include Web of Things, Internet of Things, Big Data Analytics, Web Science, Service-oriented Computing, Pervasive Computing, and Sensor Networks. He is ranked ...