Advancing Rail Safety with Computer Vision and Human Factors
Mosaic ATM developed a scalable, camera-based framework to better understand fatigue progression in safety-critical transportation operations.
Mosaic ATM developed a scalable, camera-based framework to better understand fatigue progression in safety-critical transportation operations.
Artificial intelligence in aviation tends to attract two competing narratives. In one, AI solves congestion, delays, staffing challenges, and nearly every other operational problem. In the other, it is an unproven technology that threatens to remove experienced professionals from safety-critical decisions. Neither version accurately describes where AI is headed today in air traffic control.
Airport operators and aviation stakeholders already have access to more operational data than ever before. The challenge is turning that data into a shared, accurate, and forward-looking understanding of airport operations. That is where digital twins are becoming increasingly valuable.
Mosaic ATM’s drone services company, Aerial Vantage, developed OLYMPUS, which uses ML models to drastically reduce weather prediction data computational time while extending forecast horizons significantly.
Mosaic ATM partnered with Touchstone Evaluations (Touchstone) to complete Phase I of the Visual Integration of Language Models in Automotive Safety (VILMAS) Small Business Innovation Research (SBIR) project, funded through the National Highway Traffic Safety Administration (NHTSA).
Mosaic is proud to support the development and release of the FAA’s Maintenance Management Information Exchange Model (MMIXM) 4.0.0, a vital data standard that enhances the communication of operations and maintenance information across the NAS.
Mosaic ATM is proud to have been prominently featured in the FAA’s PMO Team Talk: All Looks Clear in the Cloud Webinar. The Mosaic FMDS program received enthusiastic recognition for its outstanding contributions to the Flow Management Data and Services (FMDS) program, particularly its work in advancing cloud-based modernization for FAA traffic flow management systems.
Aerial missions are becoming indispensable across industries, and optimizing operations for uncrewed aircraft and their supporting ground crews is critical. Mosaic ATM’s Uncrewed Aircraft Fleet & Flight Operations Optimization (UA-FFOpt) was designed to investigate this challenge by creating a proof-of-concept system aimed at optimizing large-region missions in terms of both aircraft flight time and ground crew costs.
The Federal Aviation Administration (FAA) has publicly released a detailed technical report on Mosaic ATM’s pioneering project, conducted in collaboration with the Virginia Tech Mid-Atlantic Aviation Partnership (VT MAAP) and the Wireless Research Center of North Carolina (WRC). This twelve-month joint effort marks a significant step toward safely integrating small uncrewed aircraft systems (sUAS) into the National Airspace System (NAS).
In this paper, we provide a high-level description of the approach taken to provide real-time predictions and decision support for operators monitoring complex tactical situations.