A survey of next-generation computing technologies in space-air-ground integrated networks

Z Shen, J Jin, C Tan, A Tagami, S Wang, Q Li… - ACM Computing …, 2023 - dl.acm.org
Space-air-ground integrated networks (SAGINs) are key elements for facilitating high-speed
seamless connectivity to the devices/users in infrastructure-less environments, where the …

A critical review on the state-of-the-art and future prospects of Machine Learning for Earth Observation Operations

P Miralles, K Thangavel, AF Scannapieco… - Advances in Space …, 2023 - Elsevier
Abstract The continuing Machine Learning (ML) revolution indubitably has had a significant
positive impact on the analysis of downlinked satellite data. Other aspects of the Earth …

Hypso-1 cubesat: First images and in-orbit characterization

S Bakken, MB Henriksen, R Birkeland, DD Langer… - Remote Sensing, 2023 - mdpi.com
The HYPSO-1 satellite, a 6U CubeSat carrying a hyperspectral imager, was launched on 13
January 2022, with the Goal of imaging ocean color in support of marine research. This …

{StarryNet}: empowering researchers to evaluate futuristic integrated space and terrestrial networks

Z Lai, H Li, Y Deng, Q Wu, J Liu, Y Li, J Li… - … USENIX Symposium on …, 2023 - usenix.org
Futuristic integrated space and terrestrial networks (ISTN) not only hold new opportunities
for pervasive, low-latency Internet services, but also face new challenges caused by satellite …

Federated learning in satellite constellations

B Matthiesen, N Razmi, I Leyva-Mayorga… - IEEE …, 2023 - ieeexplore.ieee.org
Empowered by their exceptional versatility and autonomy, unmanned vehicles (UxVs),
including ground, aerial, surface and underwater vehicles, are emerging as promising tools …

Benchmarking deep learning inference of remote sensing imagery on the qualcomm snapdragon and intel movidius myriad x processors onboard the international …

E Dunkel, J Swope, Z Towfic, S Chien… - IGARSS 2022-2022 …, 2022 - ieeexplore.ieee.org
Deep space missions can benefit from onboard image analysis. We demonstrate deep
learning inference to facilitate such analysis for future mission adoption. Traditional space …

Wildfire segmentation analysis from edge computing for on-board real-time alerts using hyperspectral imagery

D Spiller, K Thangavel, ST Sasidharan… - … on Metrology for …, 2022 - ieeexplore.ieee.org
This paper investigates the opportunity to use artificial intelligence methodologies and edge
computing approaches for wildfire detection directly from satellite platforms. The test case for …

In-orbit demonstration of a re-trainable machine learning payload for processing optical imagery

G Mateo-Garcia, J Veitch-Michaelis, C Purcell… - Scientific Reports, 2023 - nature.com
Cognitive cloud computing in space (3CS) describes a new frontier of space innovation
powered by Artificial Intelligence, enabling an explosion of new applications in observing …

Taking artificial intelligence into space through objective selection of hyperspectral earth observation applications: To bring the “brain” close to the “eyes” of satellite …

AM Wijata, MF Foulon, Y Bobichon… - … and Remote Sensing …, 2023 - ieeexplore.ieee.org
Recent advances in remote sensing hyperspectral imaging and artificial intelligence (AI)
bring exciting opportunities to various fields of science and industry that can directly benefit …

RaVÆn: unsupervised change detection of extreme events using ML on-board satellites

V Růžička, A Vaughan, D De Martini, J Fulton… - Scientific reports, 2022 - nature.com
Applications such as disaster management enormously benefit from rapid availability of
satellite observations. Traditionally, data analysis is performed on the ground after being …