Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission
This article presents our research in the prelaunch phase of the Kanyini mission, which aims to implement an energy-efficient, AI-based system onboard for early fire smoke detection using hyperspectral imagery. Our approach includes three key components: developing a diverse hyperspectral training d...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Journal Article |
| Published: |
2024
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| Online Access: | http://hdl.handle.net/20.500.11937/96324 |
| _version_ | 1848766136909299712 |
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| author | Lu, S. Jones, Eriita Zhao, L. Sun, Y. Qin, K. Liu, J. Li, J. Abeysekara, P. Mueller, N. Oliver, S. O'Hehir, J. Peters, S. |
| author_facet | Lu, S. Jones, Eriita Zhao, L. Sun, Y. Qin, K. Liu, J. Li, J. Abeysekara, P. Mueller, N. Oliver, S. O'Hehir, J. Peters, S. |
| author_sort | Lu, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This article presents our research in the prelaunch phase of the Kanyini mission, which aims to implement an energy-efficient, AI-based system onboard for early fire smoke detection using hyperspectral imagery. Our approach includes three key components: developing a diverse hyperspectral training dataset from VIIRS imagery, groundwork in band selection and AI model preparation, and developing an emulation system. We adapted and evaluated our previously developed lightweight convolutional neural network model, VIB_SD, to meet the computational constraints of satellite deployment. The emulation system tests various onboard AI tasks and processes. Our comprehensive experiments demonstrate the feasibility and benefits of employing onboard AI for fire smoke detection, significantly improving downlink efficiency, energy consumption, and detection speed. |
| first_indexed | 2025-11-14T11:46:21Z |
| format | Journal Article |
| id | curtin-20.500.11937-96324 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:46:21Z |
| publishDate | 2024 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-963242025-01-07T05:48:08Z Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission Lu, S. Jones, Eriita Zhao, L. Sun, Y. Qin, K. Liu, J. Li, J. Abeysekara, P. Mueller, N. Oliver, S. O'Hehir, J. Peters, S. This article presents our research in the prelaunch phase of the Kanyini mission, which aims to implement an energy-efficient, AI-based system onboard for early fire smoke detection using hyperspectral imagery. Our approach includes three key components: developing a diverse hyperspectral training dataset from VIIRS imagery, groundwork in band selection and AI model preparation, and developing an emulation system. We adapted and evaluated our previously developed lightweight convolutional neural network model, VIB_SD, to meet the computational constraints of satellite deployment. The emulation system tests various onboard AI tasks and processes. Our comprehensive experiments demonstrate the feasibility and benefits of employing onboard AI for fire smoke detection, significantly improving downlink efficiency, energy consumption, and detection speed. 2024 Journal Article http://hdl.handle.net/20.500.11937/96324 10.1109/JSTARS.2024.3394574 http://creativecommons.org/licenses/by/4.0/ fulltext |
| spellingShingle | Lu, S. Jones, Eriita Zhao, L. Sun, Y. Qin, K. Liu, J. Li, J. Abeysekara, P. Mueller, N. Oliver, S. O'Hehir, J. Peters, S. Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission |
| title | Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission |
| title_full | Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission |
| title_fullStr | Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission |
| title_full_unstemmed | Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission |
| title_short | Onboard AI for Fire Smoke Detection Using Hyperspectral Imagery: An Emulation for the Upcoming Kanyini Hyperscout-2 Mission |
| title_sort | onboard ai for fire smoke detection using hyperspectral imagery: an emulation for the upcoming kanyini hyperscout-2 mission |
| url | http://hdl.handle.net/20.500.11937/96324 |