Team LionTech is a student technology team from Colegiul National "Mihai Eminescu" Oradea, Romania. We are passionate about space science, programming, robotics, and applying technology to solve real-world problems. Our team consists of dedicated high school students guided by experienced mentor teachers.
To inspire and educate the next generation of scientists, engineers, and innovators through hands-on experience with cutting-edge technology and participation in international competitions.
We have been proud participants in the European Space Agency's AstroPi Mission Space Lab competition for multiple years. This prestigious program allows students to write code that runs on Raspberry Pi computers aboard the International Space Station.
Our current mission focuses on calculating the orbital speed of the ISS through image processing and feature tracking between sequential photographs of Earth.
2022/2023 Mission - AstroPi-MSL-Report-LionTech-2023.pdf
Our mission focused on the analysis of cloud patterns and detection of atmospheric gravity waves using machine learning. We:
- Collected 1,389 images and over 103,870 sensor data samples during a 3-hour run on the ISS
- Built and trained a Convolutional Neural Network (CNN) to identify atmospheric wave patterns
- Applied spectral analysis using 2D Fast Fourier Transform to study wave characteristics
- Used TensorFlow and image processing techniques to analyze cloud formations
2021/2022 Mission - AstroPi-MSL-Report-LionTech-2022.pdf
Our mission extended previous work to explore albedo measurement and advanced cloud classification. We:
- Measured Earth's average albedo (0.099543) by categorizing surfaces into cloud, land, and sea
- Enhanced image quality using CLAHE and Brightness-Contrast techniques
- Collected 740 images and 28,620 sensor data samples during a 3-hour run (May 7-8, 2022)
- Focused on differentiating snow from clouds and detecting storm formation over oceanic regions
- Measured ISS velocity (6.68-9.82 km/s) using KAZE 2D Features detection algorithm
2020/2021 Mission - AstroPi-MSL-Report-LionTech-2021.pdf
Our award-winning mission focused on:
- Determining ISS orbital speed using OpenCV with KAZE 2D Features detection algorithm
- Developing advanced cloud classification using CNN with Keras
- Creating smoke and pollution detection algorithms for land images
- Analyzing cloud patterns over both land and sea
- Collecting 1,376 images and 29,373 sensor data samples during a 3-hour run (April 24, 2021)
- Using specialized metrics like Red-Blue Ratio (RBR) and Normalized Red-Blue Ratio (NRBR)
- Successfully measuring ISS velocity between 6.4-8.8 km/s using Ground Sampling Distance method
- Advanced to final phase of ESA AstroPi Mission Space Lab 2021/2024 (achieved Flight Status)
- Highly Commended Award in the European Astro Pi Challenge Mission Space Lab 2021
- Successfully measured the velocity of the ISS in orbit
- Created an algorithm to detect smoke, pollution, and types of cloud coverage in captured images
- Developed a CNN classifier for cloud type identification
- Official ESA Recognition
- Highly Commended Award in the European Astro Pi Challenge Mission Space Lab 2023
- The mission focused on cloud patterns and atmospheric gravity waves
- Successfully trained a CNN to identify atmospheric gravity waves
- Applied spectral analysis with 2D Fast Fourier Transform
- Official ESA Recognition
- Python
- OpenCV and Computer Vision
- Raspberry Pi and SenseHat
- Machine Learning and AI
- Robotics
- School Website: Colegiul National "Mihai Eminescu" Oradea
We are grateful for the support of our sponsors and partners who make our projects possible:
- Colegiul National "Mihai Eminescu" Oradea
- Asociatia CoderDojo Oradea
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