Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites
Nanosatellites increasingly produce more data than can be downlinked within a reasonable time due to their limited bandwidth and power. Therefore, an on-board system is required to prioritize scientifically significant data for downlinking, as described by scientists. This paper determines whether n...
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MDPI AG
2024-10-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/11/11/888 |
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| author | Ezra Fielding Akitoshi Hanazawa |
| author_facet | Ezra Fielding Akitoshi Hanazawa |
| author_sort | Ezra Fielding |
| collection | DOAJ |
| description | Nanosatellites increasingly produce more data than can be downlinked within a reasonable time due to their limited bandwidth and power. Therefore, an on-board system is required to prioritize scientifically significant data for downlinking, as described by scientists. This paper determines whether natural language processing can be used to prioritize remote sensing images on CubeSats with more flexibility compared to existing methods. Two approaches implementing the same conceptual prioritization pipeline are compared. The first uses YOLOv8 and Llama2 to extract image features and compare them with text descriptions via cosine similarity. The second approach employs CLIP, fine-tuned on remote sensing data, to achieve the same. Both approaches are evaluated on real nanosatellite hardware, the VERTECS Camera Control Board. The CLIP approach, particularly the ResNet50-based model, shows the best performance in prioritizing and sequencing remote sensing images. This paper demonstrates that on-orbit prioritization using natural language descriptions is viable and allows for more flexibility than existing methods. |
| format | Article |
| id | doaj-art-29bd95484a5a4e85bcd712f69231662b |
| institution | Kabale University |
| issn | 2226-4310 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj-art-29bd95484a5a4e85bcd712f69231662b2024-11-26T17:42:49ZengMDPI AGAerospace2226-43102024-10-01111188810.3390/aerospace11110888Flexible Natural Language-Based Image Data Downlink Prioritization for NanosatellitesEzra Fielding0Akitoshi Hanazawa1Department of Space Systems Engineering, Kyushu Institute of Technology, Kitakyushu 804-8550, JapanDepartment of Space Systems Engineering, Kyushu Institute of Technology, Kitakyushu 804-8550, JapanNanosatellites increasingly produce more data than can be downlinked within a reasonable time due to their limited bandwidth and power. Therefore, an on-board system is required to prioritize scientifically significant data for downlinking, as described by scientists. This paper determines whether natural language processing can be used to prioritize remote sensing images on CubeSats with more flexibility compared to existing methods. Two approaches implementing the same conceptual prioritization pipeline are compared. The first uses YOLOv8 and Llama2 to extract image features and compare them with text descriptions via cosine similarity. The second approach employs CLIP, fine-tuned on remote sensing data, to achieve the same. Both approaches are evaluated on real nanosatellite hardware, the VERTECS Camera Control Board. The CLIP approach, particularly the ResNet50-based model, shows the best performance in prioritizing and sequencing remote sensing images. This paper demonstrates that on-orbit prioritization using natural language descriptions is viable and allows for more flexibility than existing methods.https://www.mdpi.com/2226-4310/11/11/888orbital edge computingartificial intelligencemachine learningnanosatelliteCubeSatprioritization |
| spellingShingle | Ezra Fielding Akitoshi Hanazawa Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites Aerospace orbital edge computing artificial intelligence machine learning nanosatellite CubeSat prioritization |
| title | Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites |
| title_full | Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites |
| title_fullStr | Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites |
| title_full_unstemmed | Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites |
| title_short | Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites |
| title_sort | flexible natural language based image data downlink prioritization for nanosatellites |
| topic | orbital edge computing artificial intelligence machine learning nanosatellite CubeSat prioritization |
| url | https://www.mdpi.com/2226-4310/11/11/888 |
| work_keys_str_mv | AT ezrafielding flexiblenaturallanguagebasedimagedatadownlinkprioritizationfornanosatellites AT akitoshihanazawa flexiblenaturallanguagebasedimagedatadownlinkprioritizationfornanosatellites |