Are Drones the answer to urban mass transit challenges?
One company thinks they could be. Mark Moore is Engineering Director for Vehicle Systems at Uber Elevate, Uber’s light-aircraft ridesharing project. There he is working the next generation of urban mobility solutions that involve air passenger drones. Prior to joining Uber, Mark worked for NASA for over 32 years, the entire time focusing on conceptual design studies of advanced aircraft concepts. His research focused on understanding how to best integrate the emerging technology area of electric propulsion and automation to achieve breakthrough on-demand aviation capabilities. He left NASA for Uber to make electric VTOL flight a reality. In this episode of the Drone Radio Show, Mark talks about Uber’s passenger drones, its planned future commuter service and its impact on cities and regions.
Ever Wonder How Europe is Coming Along with Its Unmanned Traffic Management System?
Well, today’s guest gives us some insight. Philip Butterworth-Hayes is a consultant and writer on global aerospace affairs. He is the editor of Unmanned Airspace, the first dedicated UTM/counter UAS new service, and editor of Skyway, the journal of EUROCONTROL. He is also a commentator on aviation safety issues for the global broadcast industry. In this edition of the Drone Radio Show. Philip shares his perspective on efforts to create an unmanned traffic management system in Europe and he compares those efforts with what he’s observed here in the United States.
Is there a simple way to reduce flight risks?
Today’s guests believe there is. Tomer Kashi, CEO and Ori Blumenthal, CTO are co-founders of Skywatch, a powerful data analytics platform that empowers drone operators and fleet managers to track their important safety metrics and reduce flight risks. Their platform leverages the power of machine learning to mitigate risk, which can lead to lower insurance rates for drone operators. In this edition of the Drone Radio Show, Tomer and Ori talk about the company, their new platform and app, and how machine learning can reduce the cost of insurance.