White Papers
Using FAA SkyDataSentry to Extract Valuable ERAM Data for Aviation Use Cases
Mosaic analyzes operational data for aviation to improve trajectory prediction, management of special activity airspace, and conflict detection.
Mosaic analyzes operational data for aviation to improve trajectory prediction, management of special activity airspace, and conflict detection.
COMETTS is designed to address training on all of the TFM systems that currently exist in the NAS, including TFMS, TBFM, NTML, En Route Automation Modernization (ERAM), Voice Switching and Control System (VSCS), plus the Corridor Integrated Weather System (CIWS), Integrated Terminal Weather System (ITWS), Weather and Radar Processor (WARP), and other weather displays.
Having an autonomous artificial intelligence (AI) system that can monitor individuals via facial mood recognition, vocal tonality analysis, proximity to one another, performance, biosensors, surveys, and more, and predict conflict before it is problematic could improve a unit’s cohesion and performance in missions both in space and in isolated environments on Earth.
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.
Weather has a high impact on operations in many industries, and therefore is of great value to integrate into strategic decision making. Mosaic has roots in aviation research & development, giving us deep expertise in combining weather data streams with planning applications to facilitate efficient resource allocation.
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.
In our white paper, Mosaic examines fresh machine learning based approaches to more accurately forecast airline seat demand.