Innovating Space Operations with AI: The AISHGO Project

Abstract

Artificial Intelligence (AI) is increasingly permeating and improving various aspects of our daily lives; but can it also revolutionize how spacecraft are operated? This is the central question driving the project "AI for Automation of Satellite Health Monitoring and Ground Operations (AISHGO)." The project aims to integrate AI into mission control environments, such as the European Space Agency's European Space Operations Centre (ESOC) DLR's GSOC, to automate and optimize satellite health monitoring and ground operations. AISHGO is structured around four pivotal use cases, each addressing distinct aspects of satellite operations. These include machine learning-based incident classification and root-cause analysis assistance, AI-based predictive maintenance, intelligent telemetry data anomaly detection, and AI-based long-term satellite health monitoring. The research leverages both structured and unstructured data to develop data-driven AI solutions that surpass classical models in efficiency and effectiveness. By utilizing advanced AI techniques and models such as transformers, large language models (LLM), and long-short-term memory (LSTM) networks, the project demonstrates the capability of AI to predict system behaviors, flag potential issues, and enable operators to take preventative measures. The solutions proposed have been validated through both simulations and real-world scenarios, confirming their practical value and highlighting the feasibility of adopting AI technologies in modern space operations.