- May 31, 2017
- Posted by: Jeff Kish
- Categories: AI & Advanced Computing News, AI Transportation Systems News, Complex System Analysis News, Latest News, Modeling, Simulation & Visualization News, Research & Development News
Maintaining safety in the National Airspace (NAS) faces new challenges due to projected increases in manned traffic and the introduction of the Unmanned Air System (UAS) in the near future. This increased traffic within the same airspace volume will overwhelm currently used safety mechanisms that are event based and human centric. To assure safe operations in the NAS, IAI will continue the development of a tool that uses Data Analytics for Assurance of Safety (DAAS), and provides real-time monitoring of a variety of systems simultaneously. The DAAS architecture will ensure safe operations in the NAS while embracing its complexity and leveraging advancements in machine learning through one simple architecture. This single architecture can spawn tools focused on ensuring safety in different areas of operation, while enabling information sharing among them. The tools developed using DAAS will provide invaluable support to NASA and industry researchers in identifying, diagnosing, and discovering the impacts of NextGen technologies on NAS safety and efficiency. The distributed network of tools in DAAS will offer a robust solution that can take advantage of the equally distributed nature of Big Data storage and cloud computing. DAAS can be used for a wide range of remote sensing applications for NASA and other government organizations, including safety analytics for SMART-NAS Test Bed, big data repository for aviation data, and decision support for controllers and pilots. DAAS can also be applied as a safety analytics plugin for ACES, FACET, and other legacy simulation tools. It can provide safety analytics for future commercial technologies, and real-time assessment of airline networks for safety and efficiency.