Case Studies
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.
Case Studies
Contingency Planning Toolkit for Advanced Air Mobility (CPT AAMO)Â
This case study explores how the Contingency Planning Toolkit for Advanced Air Mobility (CPT AAMO) equips NASA and industry with innovative software and AI solutions to enhance safety, resilience, and scalability in future cooperative airspace operations.
Aviation Machine Learning
Transforming Weather Forecasting with AI: A Case Study of the OLYMPUS SBIR ProjectÂ
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.Â
Case Studies
Using Real-Time Data and Machine Learning to Improve Air Traffic Management Operations
Building on 20+ years of expertise in air traffic management and system optimization, Mosaic ATM collaborated with NASA to develop the Alternate Route Availability Tool (ARAT). The project aimed to boost operational efficiency and reduce delays in the National Airspace System (NAS) by providing advanced, data-driven alternate routing solutions.Â
Case Studies
Enhancing FAA Counter UAS Detection and Mitigation Efforts
In this case study, Mosaic supports the FAA’s Counter UAS Detection and Mitigation project, a critical initiative aimed at enhancing the safety and security of airspace around sensitive locations such as launch sites and airports.
Case Studies
Explanations in Lunar Surface Exploration (ELSE) for Machine Learning Models to Assist in NASA Rover Exploration
Mosaic ATM is supporting NASA by developing explainable machine learning models to assist with lunar rover exploration.
Case Studies
ATD-2 Machine Learning Model Validation Framework Design
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, building trust in the machine learning predictions is essential to expanding their use to improve inefficient operations and unused capacity. Air traffic controllers must trust the recommendations presented by them, and validation is essential towards building trust.
Case Studies
Wind Miles Model Development
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.
Case Studies
Taxi Time Predictions
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.
Case Studies
TBFM in the Cloud
Use of the Cloud has allowed commercial and Government systems to leverage the flexibility, scalability, reliability, and security of Cloud infrastructure to achieve significant efficiencies, and rapid innovation, in complex operational environments. The associated move to a micro-services Service Oriented Architecture (SOA) in the Cloud has further enhanced modularity, re-use of system capabilities, and simplification of verification and validation testing.