Moderator : Sarah Graham, Nav Canada / AEAC
From drivetrain design to airport safety, predictive maintenance, and wind profiling, this session highlights how artificial intelligence is reshaping the way drones are built, flown, and integrated into real-world applications. These four presentations showcase innovative uses of machine learning and intelligent systems to improve performance, reduce operational fatigue, and unlock new capabilities across the RPAS ecosystem.
By Bhavya Patel and Ehsan Hashemi, University of Alberta
Designing efficient RPAS systems often requires extensive physical testing of motor-propeller combinations—an expensive and time-consuming process. This presentation introduces a machine learning approach to predict drivetrain performance using a Multilayer Perceptron (MLP) trained on Tyto Robotics’ thrust stand data.
🧠 What you’ll learn:
By Abby Logan, Wavionix Technologies Inc.
Drone technology has revolutionized how airports inspect runways, monitor wildlife, and assess perimeter conditions—but the real value lies in what happens after data collection. This presentation explores how integrating drone-captured insights into intelligent, AI-supported safety workflows can reduce workload, improve response times, and minimize digital fatigue across airports of all sizes.
🛫 What you’ll learn:
Join us to discover how smarter workflows are transforming drone data into safer, more connected airport operations.
By Ali Taleb and Ibrahim Ali Fawaz, VIGELON
As drone and eVTOL operations scale, traditional maintenance models fall short. This presentation introduces Vigelon’s AI-powered predictive maintenance platform, designed to keep fleets mission-ready by forecasting failures before they happen and optimizing resource allocation.
🔧 What you’ll learn:
Join us to explore how AI is transforming maintenance from reactive to predictive—unlocking safer, more efficient aerial mobility at scale.
By Jacob Cole, University of Alberta
This presentation explores a low-cost RPAS system calibrated to measure wind speed in situ, using Ardupilot and validated against fixed anemometers. The project investigates how drone-based wind data can improve accuracy in projectile applications such as target shooting and golf.
🌬️ What you’ll learn:
Join us to discover how drones are redefining wind measurement for performance and precision.
Co-Founder
VIGELON
Co-Founder
Wavionix Technologies Inc.
Graduate Student
University of Alberta
Research Assistant
University of Alberta / Department of Electrical Engineering
VIGELON