The Department of Communications and Computer Engineering, through Principal Investigator Prof. Ing. Gianluca Valentino, will be leading two €125,000 research projects funded through the MCST Space Upstream Programme.
Detecting anomalies in telemetry data captured on-board a spacecraft is critical to ensure its safe operation, and enables operators to respond to various failures and hazards more quickly. The first project, “Anomaly detection for Spacecraft TelemetRy dAta using Artificial Intelligence” (ASTRA-AI) will focus on developing advanced deep learning neural network architectures to detect these anomalies in a precise manner. A surrogate model will also be developed to build a digital twin, to be used for diagnostic and prognostic purposes. The project will be in collaboration with Dr Robert Camilleri from the Institute for Aerospace Technologies.
Space biology research aims to understand the fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration and ultimately bioengineer spacecraft and habitats to stabilise the ecosystem of plants, crops, microbes, animals and humans for sustained multi-planetary life. AI techniques can offer key solutions towards space biology challenges by facilitating predictive modelling and analytics, and supporting autonomous and reproducible experiments.
DNA double-strand breaks (DSBs), marked by ionizing radiation-induced (repair) foci (IRIFs), are the most serious DNA lesions and are dangerous to human health. IRIF quantification based on confocal microscopy represents the most sensitive and gold-standard method in radiation biodosimetry and allows research on DSB induction and repair at the molecular and single-cell levels. In the “Deep learning for automatic foci quantification” (DeepAFQ) project, deep learning based computer vision techniques will be developed to perform such microscopy image segmentation and IRIF quantification. This project will be in collaboration with Prof. Joseph Borg from the Department of Applied Biomedical Science.
Prof. Ing. Saviour Zammit will be leading the third €125,000 research project, in collaboration with CCE academics Prof. Ing. Victor Buttigieg, Prof. Franco Davoli, Dr Hector Fenech, Ing. Antoine Sciberras, Ing. Etienne Depasquale, Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT) and the Malta Communications Authority. Next Generation Mobile Networks, from 5G Advanced to 6G, will incorporate non-terrestrial networks (NTNs) comprising Satellites, High Altitude Platforms (HAPs) and Unmanned Aerial Vehicles (UAVs), to extend range and achieve more uniform coverage over the face of the Earth. At the same time, Artificial Intelligence and Machine Learning (AI/ML) techniques are being studied to achieve the increased performance planned for these networks. These AI/ML techniques will be deployed at the edge of next generation networks and need to be energy efficient to meet mission goals and sustainable development goals. The Smart Energy Efficient Non-Terrestrial-Networks for 6G (SMARTEN6G) project will thus build a testbed to allow research into how AI/ML techniques, deployed at the edge, will allow NTNs to meet performance targets and energy efficiency goals. The non-terrestrial part of the testbed will be both physical (UAVs) and virtual (Satellites and HAPs), the latter using Digital Twin methodology to simulate satellites and HAPs whose physical realisation is too expensive for low to medium cost testbeds. The testbed will then be used to study two advanced use cases, the first focusing on augmented and mixed reality applications and the second on connected vehicle applications.
The Department would like to thank the MCST and ESA for making the funding available.
