Analysing Aircraft Black Box Data for Predicting Adverse Effects
A world leader in the analysis of aircraft flight data recorders (FDRs) wanted to leverage the power of ML to analyze the massive amounts of data from FDRs and identify safety-critical events. Zetane's team of industrial AI experts worked on the project from data preparation to model design and training to debugging and optimization. The final result was used by the client to apply for an important R&D grant.
Object Detection and Model Testing for Autonomous Trains Analysing Aircraft Black Box Data for Predicting Adverse Effects
Sometimes the last mile is the most difficult one to complete. A global aerospace and transportation client was against a tight deadline to demonstrate the results of an object detection project. With the critical deadline looming, Zetane worked with the client to understand and explain how the data was influencing the ML model to arrive at the output. This identified a major flaw in the model that was rectified on time and led to a very successful demo.
Satellite Image Analysis and Labelling
Presagis, a world leader in commercial off the shelf software (COTS) for modeling and simulation had developed a working prototype of a ML solution to label roof-tops from satellite images. This project was not getting internal traction or support from the decision makers. The most important conference of the year was 7 weeks away and excel spreadsheets, graphs and powerpoints would not cut it. Zetane worked with the team to bring their solution into the Zetane 3D environment, bringing their work to life. Management was convinced and the demo was used at the conference, receiving lots of attention.
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Predictive Maintenance For Heavy Vehicles
A global company that delivers heavy transport vehicles to the defense industry wanted to demonstrate the use of ML to predict the failure of critical systems in heavy vehicles. They had made good progress but struggled to bring the project to a working MVP and had a difficult time explaining how AI would be used in an operational context. Zetane industrial AI experts assisted the clients' AI team to understand and explain the inner workings of the model, pinpoint where improvements could be made, created real-time dashboards that operators could understand, and created a demo that impressed the Board of Directors and received funding.
Human Understandable Demo of ML Solution for Energy Grid Optimization
An up and coming company specializing in the use of ML to optimize energy management in cities and optimize the use of renewable energies, was struggling to convey the benefits of their groundbreaking work to potential clients. With an important global conference on renewable energy fast approaching, Zetane was tasked to convert their complex data and solution into a powerful and convincing demonstration showing dollar savings and environmental benefits of using their solution, leading to new customers.
Predicting Patient Outcomes of Brain Surgery on Simulators
Canada's National Research Council had done great work developing a simulator to train surgeons in complex brain surgery procedures and had amassed large data sets in the process. The research team had created ML models to predict patient outcomes and needed to validate their results and demonstrate their findings. Zetane collaborated to help bring the ML solutions to the real world, helping to create 3D simulations of the operations linked to the ML models. In so doing, certain model errors were identified and fixed and a powerful demo created.