To realize the full power of machine learning, organizations need to focus on operations and delivery of the predictions as much as the development of the algorithm itself. In the case of NASA and ATD-2, not being able to trust the projections generated could be a life-or-death situation. Air traffic controllers must trust the recommendations presented by them, and validation is essential towards building trust.
Mosaic sought to provide an open and accessible model to predict the impacts of wind on air miles flown under an SBIR contract with NASA. Ultimately, this effort has developed a model that the broader aviation community can use as a publicly available data service.
Mosaic is excited to announce our support for the FAA NextGen Office, working with ATCorp. Mosaic will examine how AI and ML can improve trajectory modeling in TBFM, and how these improvements could be applied to other automation systems or a common trajectory modeler.
The taxi-out time predictions help pilots decide when to “single-engine taxi”: taxi most of the way to the runway with only a single-engine turned on, turning on the second engine just a few minutes before take-off. The single-engine taxi decision is typically made by pilots within an hour of push back. Still, our customer asked for predictions up to four hours in advance of the expected push back time.
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…
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.
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…
Working in conjunction with subject matter experts, data scientists can swiftly apply statistical tools and uncover emerging trends. This is extremely valuable for companies trying to operate in a disruption. Not only will executives have an accurate representation of their present situation, but new products & services can be devised from these insights.
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.
Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain.