Deploying autonomous environmental monitoring hardware on Gateway is challenging because of the harsh radiation environment. Existing unmanned aerial vehicles (UAVs) used for environmental monitoring on the International Space Station (ISS) use commercial-off-the-shelf (COTS) components. To enable continuous unsupervised environmental monitoring at Gateway, Nanohmics Inc., in collaboration with Dr. Maria Gorlatova at Duke University, proposes to demonstrate SPace-Qualified Environmental Evaluation Drones with Wireless Intelligent Networked Data Processing (SPEEDWINDs). Each SPEEDWIND will have four key components: 1) a core control system built with inherently radiation hardened components, 2) a high performance COTS embedded system to enable machine learning, 3) an environmental monitoring payload with customized mission specific sensors, and 4) a wireless transceiver with adaptive networking to enable distributed operation. In Phase I, Nanohmics proposes to design a benchtop SPEEDWIND testbed combines space qualified and COTS components and demonstrate the ability of the testbed to perform distributed machine learning, such as processing fluorescence spectroscopy data, in a simulated Gateway environment.
The SPEEDWIND platform can enable rapid deployment of autonomous, intelligent UAVs with mission specific payloads. The ability to perform complex machine learning tasks on system decreases uplink and downlink bandwidth requirements.
The SPEEDWIND platform has multiple applications in the medical, defense, and industrial markets. For example, this technology could be applied to healthcare environments to perform autonomous, real-time microbial mapping with the goal of reducing healthcare-associated infections (HAIs).