“Low Power & Low Latency Cloud Cover Detection in Small...

“Low Power & Low Latency Cloud Cover Detection in Small Satellites Using On-board Neuromorphic ProcessorsChetan Kadway, Sounak Dey, Arijit Mukherjee, Arpan Pal, Gilles Bézard2023
International Joint Conference on Neural Networks (IJCNN), 1-8, 2023.

Emergence of small satellites for earth observation missions has opened up new horizons for space research but at the same time posed newer challenges of limited power and compute resource arising out of the size & weight constraints imposed by these satellites. The currently evolving neuromorphic computing paradigm shows promise in terms of energy efficiency and may possibly be exploited here. In this paper, we try to prove the applicability of neuromorphic computing for on-board data processing in satellites by creating a 2-stage hierarchical cloud cover detection application for multi-spectral earth observation images.

We design and train a CNN and convert it into SNN using the CNN2SNN conversion toolkit of Brainchip Akida neuromorphic platform. We achieve 95.46% accuracy while power consumption and latency are at least 35x and 3.4x more efficient respectively in stage-1 (and 230x & 7x in stage-2) compared to the equivalent CNN running on Jetson TX2.
View at ieeexplore.ieee.org”

Having regard also to this earlier work by Tata and Brainchip I agree and would add at this moment in time there are clearly many more Nvidia Jetsons in use across the globe than there are AKD1000 chips.”

What is the easier market to crack replacing every Jetson with AKD1000 or making every Jetson currently in use 4.07 times more energy efficient? You are the marketing man but I would think efficiency is a much easier sell.

My opinion only DYOR

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