This project develops a distributed digital twin framework for smart grid data monitoring and analytics. The research focuses on simulating and emulating smart grid environments to enable real-time monitoring, intelligent data processing, and predictive analytics. By integrating distributed computing, digital twin technology, and adaptive resource management, the framework aims to improve the scalability, reliability, and efficiency of smart grid operations while supporting data-driven decision-making and proactive system maintenance.
Honours and Masters project
Displaying 71 - 80 of 305 honours projects.
UrbanTwin-AT: A YOLO-Powered Digital Twin for Air Traffic Monitoring
This project aims to develop a lightweight YOLO-powered digital twin framework for real-time air traffic monitoring using airport surveillance cameras. The research investigates how computer vision techniques can be integrated into a digital twin capable of representing aircraft locations, movement trajectories and traffic flow in near real time.
The Learn Lens: Inclusive Adaptive Agentic AI for Measuring Learning as It Happens
LearnLens is an inclusive adaptive agentic AI learning system designed to support students while they learn complex and unfamiliar concepts. Its central purpose is to measure and support how learning develops, rather than evaluating students mainly through a final answer, program, circuit, assessment submission, or completed product.
Human-Centred Quantum Optimisation for Fair and Trustworthy Sustainable Energy Systems
This project asks how quantum and hybrid quantum-classical optimisation can be used not just to solve energy management problems more efficiently, but to solve them in ways that are fair, transparent, and usable by real people. The student will build simplified sustainable energy scheduling and resource allocation models as QUBO problems, then solve them with classical and quantum-inspired methods using Qiskit.
Cybersecurity, Privacy and Cryptography in the Quantum Age
Motivation: The Unseen Bedrock of Modern Life
Cybersecurity and cryptography are the invisible, essential foundations of the modern digital world. Every day, billions of transactions and communications rely on complex mathematical puzzles to ensure confidentiality, integrity, authenticity, privacy and even more security features.
An Explainable Epidemiology System for Vaccine Safety and Proactive Care
This project aims to develop an explainable epidemiology system that combines generative AI, biostatistics, and epidemiological reasoning to support healthcare analysis and decision-making. The system will take structured health data as input, analyse it multimodally, and build a knowledge base that can be queried by epidemiologists and health researchers.
Designing Human-Centred Digital Twins for Reliable and Resilient Energy Networks
Future electricity networks are becoming increasingly complex due to the rapid growth of distributed energy resources (DERs), batteries, renewable generation and intelligent infrastructure. Although modern networks collect large volumes of operational, asset and maintenance data, this information is often distributed across multiple systems, making it difficult for engineers and operators to understand the true reliability and resilience of the network or identify emerging risks before failures occur.
Deep Self-Supervised Learning of Bayesian Network Structures through Graph and Data Masking
Bayesian Networks (BNs) are widely used for modelling uncertainty and causal relationships in domains such as healthcare, finance, cyber security and decision support. However, learning the optimal BN structure directly from observational data remains computationally challenging due to the super-exponential search space of possible graphs.