Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Optimised Satellite Constellation for Bushfire Detection through Edge Computing

Version 1 : Received: 28 February 2021 / Approved: 2 March 2021 / Online: 2 March 2021 (10:24:16 CET)

How to cite: Wijayatunga, M.; Wu, X. An Optimised Satellite Constellation for Bushfire Detection through Edge Computing. Preprints 2021, 2021030071 (doi: 10.20944/preprints202103.0071.v1). Wijayatunga, M.; Wu, X. An Optimised Satellite Constellation for Bushfire Detection through Edge Computing. Preprints 2021, 2021030071 (doi: 10.20944/preprints202103.0071.v1).

Abstract

The end of 2019 marked a bushfire crisis for Australia that affected more than 100000km2 of land and destroyed more than 2000 houses. Here, we propose a method of in-orbit bushfire detection with high efficiency to prevent a repetition of this disaster. An LEO satellite constellation is first developed through NSGA-II (Nondominated Sorting Genetic Algorithm II), optimising for coverage over Australia. Then edge computing is adopted to run a bushfire detection algorithm using several constellation satellites as edge nodes to reduce fire detection time. A geostationary satellite is used for inter-satellite communications, such that an image taken by a satellite can be distributed among several satellites for processing. The geostationary satellite also maintains a constant link to the ground, so that a bushfire detection can be reported back without any significant delay. Overall, this system is able to detect fires that span more than 5m in length, and can make detections in 1.39s per image processed. This is faster than any currently available bushfire detection method.

Keywords

Bushfire Detection; Edge computing; Satellite constellation; Cubesats

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