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2020 ACCELERATOR COHORT  |  View All »

MIRA: Autonomous Aircraft Inspection

A software + hardware package to help aviation professionals perform faster, better aircraft inspections

Danny Flynn, Co-Founder, College of Engineering ’22

Ivan Lewis, Co-Founder, College of Business, BIT ’22

Neel Kanjani, Co-Founder, College of Engineering, Aerospace, ’22

Aayush Salot, Co-Founder, College of Engineering, Aerospace, ’22

Neil Gutkin, Co-Founder, Computational Modeling & Data Analytics ’22

Nick Prete, Co-Founder, College of Architecture and Urban Studies, Industrial Design, ’22

MIRA is a platform for performing autonomous inspection of commercial aircraft. Images are captured from autonomous UAVs during routine aircraft inspections and are processed via a machine learning system to autonomously detect defects in the surface of the aircraft. Utilizing UAVs and machine learning to detect surface defects reduces the time and cost of performing aircraft inspections while at the same time enhancing the quality of the inspection, making for safer flights for passengers.

This idea/project spawned out of Studio+ during the Spring 2020 semester and was heavily influenced by our mentors from Boeing. We identified one competitor that appears to have developed a similar platform already (Donecle), indicating that there is indeed a market for this technology. However, they are France-based, which makes doing business in the United States difficult, especially with military clients.

We are currently somewhere in the “proof-of-concept” stage, with high-level design and software front-end somewhat done but no physical prototype yet.


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“Our new inspection methodology allows for more detailed inspections while also reducing the amount of time it takes to get an aircraft back into the sky.” – Neel Kanjani, Co-Founder, MIRA

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