Cloud-Based Tool Aids Meteorite Recovery Using Drones and ML

This paper presents a cloud-based tool that utilizes drones and machine learning to facilitate the recovery of instrumentally observed meteorite falls. The tool incorporates improvements over previous iterations and details its application to observed meteorite falls in South and Western Australia. The system's cloud-based architecture allows for accessibility and collaboration among researchers in the meteoritics community. The use of drones enables efficient searching of large areas, while machine learning algorithms aid in identifying potential meteorite locations based on visual data. This technology has implications for in-situ resource utilization (ISRU) research, as it demonstrates the potential for automated systems to locate and retrieve valuable resources on other planetary bodies. The tool could be adapted for use in lunar or Martian exploration, where it could assist in identifying and collecting samples of interest. The integration of drone technology and machine learning represents a significant advancement in meteorite recovery and planetary science.

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