Aerial AId: Visual data processing with AI in emergency scenarios for quick decision making
Description
The Aerial AId activity enables the use of perception engines – primarily classification and object detection algorithms – in small uncrewed aerial systems (sUAS) for sUAS medical emergency response service providers. The goal of Aerial AId is to demonstrate a prototype optimized and trained perception engine, application specific datasets, and assurance framework.
Detailed example
This project aims to provide the initial steps to safely enabling artificial intelligence/machine learning (AI/ML) technology for aerial emergency medical response with the potential to drastically improve emergency medical operations by increasing efficiency, reducing mission time, and reducing the strain on humans involved in the operations. The vision for a future fully automated capability addresses the primary challenge to adoption for sUAS into the emergency medical response sector, and this technology development overlaps significantly with ARMD goals by creating a framework for assured autonomy.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
This work will specifically enable stakeholders in the commercial sUAS sector that are well positioned to develop sUAS concepts for emergency medical response applications.
Controls / human review
ATO: Not reported; PIA: Not published