The FAA is sponsoring the FAA Challenge: Smart Airport Student Competition (“Smart Airport Challenge”) to recognize students with the ability to demonstrate innovative thinking focused on improving the efficiency, effectiveness, and utilization of smart technology in and around the airport environment while enhancing the overall traveling experience.
The FAA is using this competition to:
- stimulate and advance innovation in aviation research;
- promote the development of a robust aviation workforce to support a growing and evolving aerospace system;
- develop a pipeline to fill current and projected shortages via partnerships with academia and industry;
- and drive a passion for aviation in today’s youth of all ages and backgrounds.
The FAA intends to incentivize university-level students at accredited United States-based colleges and universities to think creatively in developing solutions to transportation technology challenges while addressing the human factors aspects of the traveler’s experience, and to share those innovations with the broader community.
Universities should consider the cutting-edge needs of the FAA and smart airports of the future, focusing on key emerging technology areas of health-smart airports, Unmanned Aerial Systems (UAS), data analytics, and autonomous robotics systems. Teams should propose one (1) of the four (4) following themes:
Theme 1: Increased Sanitation and Hygiene Practices for Health-Smart Airports The COVID-19 pandemic has caused public concern regarding air travel due to potential spread of the virus through human contact, surfaces, and air particles. Smart airports of the future should be designed to reduce the spread of pathogens. Innovative solutions are sought for integrating health screening into the security process, reducing the need for physical contact or proximity with passengers through automation, increasing monitoring of social distancing and symptomatic individuals, improving air circulation and filtering, and improving sanitation practices, including the use of UV light.
Theme 2: Innovative Uses for Unmanned Aerial Systems (UAS) at Airports The use of Unmanned Aerial Systems (UAS) has increased exponentially over the past decade. Smart airports of the future could safely use UAS in a variety of functions. Innovative solutions are sought for the use of tethered or untethered Unmanned Aerial Vehicles (UAV), or “drones,” for UAV/wildlife detection and mitigation, detection of foreign objects or ice on runways/taxiways, aircraft and runway inspection, perimeter security, and increased connectivity.
Theme 3: Smart Airport Data Analytics Data analytics is an emerging field of analyzing raw data in order to make conclusions and is being used nationwide to discover and predict trends. Airports are complex systems rich in data that could be used to improve operations, passenger experience, and safety. Innovative solutions are sought for the use of big data analytic techniques to reduce security wait times, facilitate navigation, increase the probability of on-time departures, reduce energy consumption, automate interpretation of video data, and improve operational efficiency.
Theme 4: Innovative Uses for Autonomous Robotics Systems at Airports Autonomous and semi-autonomous robotics systems are being used throughout industry to improve productivity and perform potentially hazardous operations. High levels of reliability and trusted autonomy are required for such systems to be integrated into airport operations. Innovative reliable autonomous systems are sought for security screening, mobility of passengers and equipment, baggage handling and transport, baggage inspection and tracking, UAV/wildlife detection and mitigation, perimeter security, and runway incursion detection.
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Total Cash Prize Pool:
Travel Reimbursement up to $6,000 will be awarded to each of the three finalist teams to help offset the cost of traveling to the 2021 FAA Challenge Forum and Awards Ceremony to demonstrate their concepts. A $25,000 prize will be presented to the lead university of the winning team.