Faculty Mentor Name
David Conte
Format Preference
Poster
Abstract
The Reconnaissance and Documentation (RAD) mission aims to utilize a Low Earth Orbit satellite using machine learning enabled image recognition and optical remote sensing to observe countries currently experiencing Stage Nine of the United Nations’ Ten Stages of Genocide. The primary objective of the RAD satellite, Leza, is to observe high-risk countries at adequate spatial and temporal resolutions to capture evidence of genocide. The secondary objective of Leza is to process images on-board, so flagged images serving as evidence may be distributed to proper authorities, the United Nations, and mainstream media outlets as soon as possible. Using remote sensing to survey the surface of the planet is far from a new concept but using it to uphold current international human rights laws is revolutionary. Evidence gathered during the operational lifetime of the satellite could be used not only to persecute those inflicting chaos, but also to push for new policies on the international level.
A prototype system that will test the machine learning software on the ground before utilization aboard Leza includes a drone, Olorun, and testing payload, OWL. The Olorun drone will act as a testing platform for image recognition software developed as part of the OWL payload. OWL will use a pre-trained neural net to evaluate if 3D modeled test beds of simulated evidence of genocide can be identified. This prototype will also analyze the capability to downlink images of interest and discard irrelevant photos. Testing of the Olorun and OWL will be completed in April 2022.
Included in
Reconnaissance and Documentation (RAD)
The Reconnaissance and Documentation (RAD) mission aims to utilize a Low Earth Orbit satellite using machine learning enabled image recognition and optical remote sensing to observe countries currently experiencing Stage Nine of the United Nations’ Ten Stages of Genocide. The primary objective of the RAD satellite, Leza, is to observe high-risk countries at adequate spatial and temporal resolutions to capture evidence of genocide. The secondary objective of Leza is to process images on-board, so flagged images serving as evidence may be distributed to proper authorities, the United Nations, and mainstream media outlets as soon as possible. Using remote sensing to survey the surface of the planet is far from a new concept but using it to uphold current international human rights laws is revolutionary. Evidence gathered during the operational lifetime of the satellite could be used not only to persecute those inflicting chaos, but also to push for new policies on the international level.
A prototype system that will test the machine learning software on the ground before utilization aboard Leza includes a drone, Olorun, and testing payload, OWL. The Olorun drone will act as a testing platform for image recognition software developed as part of the OWL payload. OWL will use a pre-trained neural net to evaluate if 3D modeled test beds of simulated evidence of genocide can be identified. This prototype will also analyze the capability to downlink images of interest and discard irrelevant photos. Testing of the Olorun and OWL will be completed in April 2022.