Mosaic ATM Case Study | ATD-2 Addressing Inefficiency in Today’s Air Transportation System According to NASA1, many of today’s air transportation system issues can be attributed to a lack of information sharing amongst the operators responsible for managing air traffic in busy terminal environments. Concepts and technologies to improve the Read more…
As part of the ATD-2 effort, Mosaic, in conjunction with NASA, evaluated an ML-driven approach against the controller-derived assignments, hypothesizing that the performance would be equivalent to that of an expert air traffic controller.
We decided to approach this problem as a similarity learning modeling effort. We used convolutional neural networks to train a model that takes an image or video as input and outputs a vector representation of the input, such that similar inputs will be close to each other in the vector space. The vector learning is driven by a triplet loss function.
This white paper explores how traditional models of the value of information (VoI) can be extended effectively to account for uncertainties presently inherent in gathering and analyzing big data. To illustrate the challenge, we explore the VoI an automobile manufacturer may derive by engineering a telematics system into its vehicles.
The proposed system, composed of components that have been developed for other Air Force, Navy, and NASA projects. The proposed system is called the Artificial Intelligence System for Human Health Support, or AIS-HHS. Mosaic Space and Aptima are on a defense contract with the Air Force to conduct R&D Technical Read more…
Mosaic is thrilled to announce that we will be supporting the Federal Aviation Administration to integrate machine learning & artificial intelligence into their Enterprise Information Management System. Mosaic will leverage a decade of expertise in designing & deploying custom #machinelearning & #AI algorithms that influence strategic & operational decision making. Read more…
Designing and deploying machine vision is a powerful technology that humans can employ to improve their decision making. These deep learning and AI techniques are not easily developed, and trained data scientists need to be involved in the translation of analytics to business insights.
Computer vision is a powerful AI technique with vast business applications. In this white paper, Mosaic examines how to use machine vision for detecting airport layouts from the sky.
Mosaic ATM is excited to share the work of our team supporting FAA’s successful Paired Approach Demonstration, conducted in February 2019 at San Francisco International Airport (SFO) and Tucson International Airport (TUS). Under an SE2025 Research and Mission Analysis contract task order, Mosaic ATM led a multi-organizational team that developed Read more…
This video provides an overview of the Management by Trajectory (MBT) concept that Mosaic is developing as part of a NASA Research Announcement (NRA). It follows a flight from Seattle to Atlanta and shows the differences that flight’s experience between the current National Airspace System (NAS) environment and the MBT Read more…