Titulo Estágio
Transforming Space Debris Management: AI-Powered ETL and Dynamic Visual Representation for Collision Avoidance
Áreas de especialidade
Sistemas Inteligentes
Engenharia de Software
Local do Estágio
CISUC
Enquadramento
Our reliance on space-based infrastructure across various domains, including transportation, finance, and communication, has grown substantially. However, this infrastructure faces a critical challenge in the form of space debris, which has accumulated over decades of space exploration and utilization, resulting in congestion in near-Earth orbital space. Space debris encompasses many shapes and sizes, from large rocket stages to tiny paint flakes.
Neuraspace is a Space Traffic Management Platform planned to have all the
tools a satellite operator needs to perform space operations. Each tool available through
the Neuraspace platform will be available as a stand-alone product. Customers who choose
an integrated use of all the products offered by the Neuraspace platform will experience a
higher added value. Space as a market, especially new space, will present new
challenges and needs requiring new tools. Neuraspace is the first of a new type
of product we can call SpaceOps.
Objetivo
This project explores the feasibility of developing automated mechanisms for the extraction, transformation, and loading (ETL) process of space debris information. The goal is to create a versatile framework capable of collecting, processing, and storing different types of space debris data. Additionally, the research will investigate the application of AI techniques to enhance data transformation in the ETL process and generate visual representations of space object data.
In addition to the ETL process, this project will investigate integrating artificial intelligence (AI) techniques to enhance space debris management. AI can assist in detecting patterns, anomalies, and relationships within the collected space debris data, thereby improving the efficiency and accuracy of data processing and transformation. One potential research direction involves leveraging AI algorithms to optimize and automate the data transformation stage of the ETL process.
Moreover, the project will explore the use of AI for generating visual representations of space object data. The framework can create informative visualizations that comprehensively understand space debris characteristics, trajectories, and potential collision risks by employing machine learning and data visualization techniques. These visual representations can aid decision-making processes regarding space debris management and collision avoidance.
Plano de Trabalhos - Semestre 1
1. Literature Review: Conduct an in-depth review of relevant literature on space debris, data collection methods, ETL processes, AI-based data transformation, and data visualization techniques.
2. Framework Proposal: Develop a comprehensive framework integrating AI algorithms for data transformation in the ETL process and visual representation generation.
3. Preliminary Implementation: Begin implementing the framework, focusing on integrating AI techniques for efficient data transformation and visual representation generation.
4. Intermediate Report: Compile the progress made during the first semester into an intermediate report.
Plano de Trabalhos - Semestre 2
5. Results Analysis: Evaluate the effectiveness of AI-based data transformation in the ETL process and analyze the quality and usefulness of the generated visual representations.
6. Framework Refinement: Enhance the framework based on the analysis and feedback, addressing any limitations or shortcomings discovered during the evaluation.
7. Results Validation: Validate the accuracy and reliability of the AI-driven data transformation and visual representation generation by comparing them with established methods and expert knowledge.
8. Scientific Article: Prepare a scientific article highlighting the main findings and contributions of the research project, focusing on AI-based data transformation and visual representation.
9. Thesis Writing: Compile all the research findings, methodologies, and conclusions into a comprehensive thesis.
Condições
The student will work within the interdisciplinary project NEURASPACE - AI FIGHT SPACE DEBRIS, conducted at the ECOS and SSE groups of CISUC. The project provides a dedicated workspace and necessary computational resources. Additionally, eligible students may have the opportunity to receive a scholarship (Bolsa de Investigação para Licenciado) for a minimum duration of six months, following the monthly stipend guidelines set by Fundação para a Ciência e Tecnologia (FCT).
Orientador
Nuno Lourenço / Bruno Cabral
naml@dei.uc.pt 📩