C-SpaRC Project: Modeling large solar flares via AI


In recent years, the global space economy has experienced a tremendous growth. Humanity is heavily dependent on critical space ICT services (e.g., Earth Observation/Weather Monitoring, GNSS/GPS, Sat-Communications, etc.). Space Weather (SWx) has an adverse impact to these space services and to critical infrastructures on the ground. In Feb 2022, SpaceX lost 40 of 49 launched Starlink satellites due to SWx, costing them over $50 million in losses. SWx 11-year cycle has its next peak in 2025.

In this project, we aspire to develop a system that will predict the events of severe disruptions of Earth’s magnetic field caused primarily by flares and Coronal Mass Ejections (CMEs). The system will start by predicting such events at least 5-6 hours in advance providing adequate time for issuing a geomagnetic storm alarm. Aim is to then increase this notice to more hours or days. The goal is to get an initial prediction as soon as a CME bursts in space by monitoring the sun’s activity and analysing active regions of the sun.

Furthermore, the structure of the proposed project enables the combination of SWx data and hospital data from the Aretaeio Hospital that can be integrated for the computational analysis resulting in the study of possible corelations between the two topics. The undertaking of such an interdisciplinary study will qualitatively and quantitively relate health issues such as e.g., heart, lung and circulatory diseases, different kinds of cancers, and other ones with space weather patterns. Part of the project will focus on the study and prevention of the harmful effects of space radiation on living assets (i.e., humans as represented by human organs-on-a-chip). By correlating the effects of space weather on both living and non-living assets using the same datasets, we may be able to develop non-living ‘sentinels’ that predict damage to our living ‘sentinel’ and eventually, the living human.

Official Website: https://www.spaceexploration.org.cy/

Techniques used: Satellite Imagery, Hyperspectral Sensing, Artifical Intelligence, Computer Vision, Multi-modal Deep Learning, 3D modelling.

Collaboration with: CSEO (Coordinator) Space Systems Solutions (S3) Ltd, CYENS Centre of Excellence, University of Cyprus, Aretaeion Hospital, Cyprus Institute of Neurology & Genetics

Started: January 2024

Status: On-going

Funding: C-SpaRC is funded by the Cyprus Research and Innovation Foundation (RIF), which is the national authority in charge of supporting and promoting research, technological development and innovation in Cyprus. The project is coordinated by CSEO.