The 2024 Federal Aviation Administration (FAA) Data Challenge ushers in a groundbreaking opportunity for university students to identify challenges and present solutions toward the evolution of the National Airspace System (NAS) into a more information-centric entity. By harnessing the power of artificial intelligence and advanced analytics, participants are invited to tackle pressing challenges within aviation safety, operational efficiency, sustainable aviation, and the exploration of novel NAS applications. This challenge not only highlights the FAA's commitment to innovation and safety but also opens the door for the next generation of data scientists and engineers to contribute meaningful solutions that could shape the future of aviation.
Embarking on this challenge offers a unique opportunity to engage with real-world problems, leveraging vast datasets and cutting-edge technologies to make tangible impacts. Participants will have the chance to demonstrate their skills, creativity, and passion for aviation, all while being supported by academic mentors and the broader aviation community. This is more than a competition; it's a chance to be at the forefront of a major shift towards an info-centric NAS, driving advancements that promise to enhance efficiency, safety, and sustainability across the aviation industry.
The challenge is structured in two main phases: Phase 1 focuses on problem identification in an abstract submission, where solvers articulate aviation-related problems and their plan to address them using AI/ML and advanced analytics. Up to ten finalists are then selected to proceed to Phase 2, which involves developing and executing the proposed solutions, culminating in an in-person presentation to FAA officials in the Washington, D.C metropolitan area. This structure encourages a deep dive into the complexities of aviation challenges and showcases the innovative potential of participants' solutions.
The evolution of the National Airspace System (NAS) under the FAA's strategic direction is a testament to the agency's commitment to integrating advanced technologies to improve the efficiency, safety, and sustainability of air travel. The transition towards an Info-Centric NAS aims to accommodate the anticipated increase in diverse operations and vehicle types within the airspace. This future vision of the NAS is enhanced interoperability and agility in traffic management services, and the adoption of safety management practices that leverage big data for real-time safety assurance. Projects under the Info-Centric NAS initiative, such as Advanced Air Mobility and the Automation Evolution Strategy, signify the FAA's proactive stance in embracing innovative solutions that promise to redefine the future of aviation.
These strategic endeavors resonate with the goals of the 2024 FAA Data Challenge, which seeks to harness the innovative potential of university students in advancing AI/ML and analytics solutions across key areas of aviation. By aligning with the FAA's broader mission and strategic plans, the challenge acts as a catalyst for fostering novel solutions that contribute to the ongoing transformation of the NAS, setting a course towards a more efficient, safe, and sustainable aviation ecosystem.
The 2024 FAA Data Challenge invites university students back to the forefront of innovation in aviation analytics. This two-phase competition is designed not just to spark creativity but to fuel the journey towards an info-centric NAS through the adept use of AI/ML and advanced analytics. This challenge is open to U.S. university students. Please view the challenge rules for complete eligibility information.
Phase 1: Ideation and Abstract Submission In the initial phase, we seek your most forward-thinking ideas—abstracts outlining potential solutions to aviation-related challenges using enhanced data analytics methods. This is your opportunity to explore the vast skies of data analytics, where your vision could lead to significant advancements in how we understand and navigate the airspace. Problems identified will demonstrate potential for significant impact in improving aviation safety, improving operational efficiency of the NAS, contributing to the drive for sustainable aviation, and assisting with the rapidly evolving new and novel uses of the NAS.
The selection process is as rigorous as it is inspiring, with up to ten finalists being chosen based not only on the problem identified but also on the innovativeness and feasibility of the proposed analytical approach. This is your chance to think big, to question the status quo, and to propose solutions that could revolutionize the future of aviation.
Phase 2: Solution Development and Presentation Finalists will embark on a journey to turn their abstracts into tangible solutions. This phase is about bringing your ideas to life through data models, algorithms, and analytics that will be scrutinized by a panel of FAA officials. The culmination of this phase is an in-person event where you will showcase your work, offering a unique platform to present your findings and the potential impact on the aviation industry.
Your solution could not only earn you accolades but also contribute to a safer, more efficient, and innovative airspace. The best solutions will be recognized with awards and all qualified submissions will gain visibility among key stakeholders in the aviation sector.
Finalists will be invited to present their solutions at a live event with the FAA in March, 2025. Prize funds from Phase 1, as well as an additional stipend, can be used for travel to the event.
To secure victory in the 2024 FAA University Data Challenge, your submission must clearly identify a pressing aviation-related problem, the data and solution you propose to solve it, and a plan for how you will execute in Phase 2. Your Phase 1 submission should succinctly demonstrate your understanding of the chosen issue and its significance within the fields of aviation safety, operational efficiency, sustainable aviation, or novel NAS applications. Additionally, illustrate the solution, its potential impact, and how it stands out for its innovation. Winning entries will adeptly bridge the gap between problem identification and solution, backed by a solid plan for Phase 2 execution. This includes leveraging the right data, outlining a clear development strategy, and showing readiness to implement the solution with academic support, all within the challenge timeframe.
To be eligible for an award, your proposal must, at minimum:
The Problem You Can Solve
In your abstract submission for Phase 1 of the 2024 FAA Data Challenge, your primary task is to articulate a problem within at least one of the specified categories that you believe can be addressed through the application of AI/ML and advanced analytics. It's imperative that your abstract not only outlines the problem but also demonstrates a deep understanding of its complexities and significance. By providing evidence that underscores the magnitude of the issue and your understanding of it, you position yourself as a solver capable of unlocking potentially transformative solutions.
Improve Aviation Safety: Enhanced safety in aviation is an ongoing journey toward preemptive hazard identification and mitigation. By leveraging operational data, AI/ML technologies offer unprecedented opportunities to discern trends, correlate events, and forecast potential safety breaches with a precision that approaches real-time analysis.
Improve Operational Efficiency of the NAS: The NAS efficiency is inherently tied to the optimal flow of real-time data regarding weather conditions, aircraft locations, and airspace status. The strategic dissemination of this data empowers decision-makers, facilitating enhanced airspace and airport capacity utilization. Here, the potential for AI/ML to streamline operations and decision-making processes is vast, setting the stage for a more responsive and efficient NAS.
Contribute to Sustainable Aviation: The trajectory toward sustainable aviation is multifaceted, necessitating advancements across fuel sustainability, operational efficiencies, next-generation aircraft development, and the minimization of environmental footprints. The right analytics can offer insights that could lead to breakthroughs in how the aviation industry approaches sustainability. Your abstract could explore how data-driven strategies can accelerate progress in any of these areas, marking a significant step toward eco-friendly skies.
Assist with Rapidly Evolving New and Novel Uses of the NAS: The aviation sector is experiencing rapid expansion, driven by increasing demands for commercial and private services and the introduction of innovative aircraft types. This growth necessitates the adoption of advanced analytical methods, such as modeling and simulation, to swiftly assess operational scenarios, mitigate risks, and enhance overall efficiency. The opportunity here is to apply your analytical acumen to simulate future aviation landscapes, potentially reshaping how the NAS accommodates emerging aviation modalities.
In framing your problem statement, ensure it resonates with the urgency and relevance of the challenge at hand. Your submission should not only reflect a meticulous analysis of the problem but also your vision for a solution that can significantly impact the aviation industry. It's about convincing the evaluators that you grasp the issue deeply enough to propose a viable, impactful solution. Let your abstract set the stage for your innovative, data-driven advanced analytics solution.
The Data
As part of your submission, describe the data that can be used to solve the problem you have chosen. There are volumes of publicly available data, and below are several examples. Solvers are not limited to using only publicly available data. Solvers may even source or generate synthetic data. As part of your submission, you will provide detailed evidence into the reliability of the data and its ability to solve the problem.
The FAA Data Portal is a gateway into safety data, air traffic information, and environmental insights, all designed with user-friendly interfaces to democratize access to critical aviation data. This portal supports transparency and research with its comprehensive datasets. The FAA Data & Research Site focuses on the FAA's commitment to ensuring the safety of commercial and general aviation. It provides extensive information on the agency's research activities, including details on how research is conducted, the resulting data and statistics, and insights into funding and grant data. The Sherlock Data Warehouse, distinctively a NASA-affiliated site, is a comprehensive data repository tailored for air traffic management research and development. Encompassing flight information, weather data, and traffic flow-related products, the infrastructure supports big data analytics and machine learning, offering users the tools to search, view, and download diverse data sources tailored to their research needs. A newer feature of the Sherlock Data Warehouse is the TFM Flow, which captures nationwide traffic data from the FAA's Traffic Flow Management (TFM) system, and is a rich resource for understanding air traffic flow across the NAS.
Managed by the FAA's IT Shared Services and the Chief Data Office, the FAA Data Catalog is developed with open-source application CKAN, following the DCAT-US Schema v1.1 for metadata standards. Launched in 2020, it aims to comply with the OPEN Government Data Act by making government data available in open, machine-readable formats. The Bureau of Transportation Statistics (BTS) Site is part of the U.S. Department of Transportation and offers a broad array of transportation data, including comprehensive aviation statistics. The site facilitates access to data on airlines, airports, and air traffic, among other statistics, aiming to enhance the understanding, performance, and safety of the U.S. transportation system. The BTS also houses the Top 50 U.S. Airports Dataset, which contains historic volumes of passengers. Pursuant to Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government, the Department of Transportation released an Artificial Intelligence (AI) Use Case Inventory to the public on October 24, 2022. The inventory was submitted to the Federal Chief Information Officers Council and is updated on an annual basis (most recently, July 26, 2023). Within the use cases are examples of how the Federal Aviation Administration is leveraging AI/ML. The Airport Data and Information Portal (ADIP) is accessible through adip.faa.gov, offering public access to airport data, including historical aeronautical information and private airport reports. This portal provides a geospatial perspective on airport operations, layouts, and other critical data.
You, Your Solution, and Your Plan
In your Phase 1 submission, you are charged to describe your plan that bridges the gap between the problem you've identified and the solution you propose. This plan is your roadmap for Phase 2, detailing how you will leverage your skills, resources, and the mentorship of a committed professor to bring your vision to fruition within the allocated time frame.
Describe the solution you envision for the problem you've chosen to tackle. Clearly define the solution you propose, focusing on how it addresses the identified problem directly and effectively, and highlighting what makes your solution innovative. Detail the steps you will take to develop your solution in an execution plan, including your approach to data analysis, model development, and any AI/ML techniques you plan to employ. Describe resources at your disposal, including software tools, data sets, and any unique assets that give you a competitive edge. Equally important is the support from a professor who is committed to your project. Outline their role and how their expertise will guide and enhance your work. Provide a realistic timeline for your project, breaking down the phases of development, testing, and refinement, allowing you to deliver within the months allocated for Phase 2. Finally, convey your dedication to seeing the project through to completion. This is where you can speak to your passion for aviation, data analytics, and the potential to contribute to the FAA's mission. Highlight any previous projects or experiences that illustrate your ability to undertake ambitious projects and deliver results. This is your moment to inspire confidence in your abilities and your project, demonstrating that you and your team are the right ones to bring this solution to life.
| Section | Description | Overall Weight |
| Understanding of the Problem |
| 30% |
| The Data to Be Used |
| 20% |
| The Solution |
| 25% |
| The Team & Plan |
| 15% |
| Innovation/Novelty |
| 10%
|
Phase 1 Prizes
In Phase 1, a total prize purse of $10,000 will be distributed among ten finalists, to their university. Each finalist’s university will receive $1,000 to acknowledge their innovative ideas and contributions towards solving significant aviation-related problems using AI/ML and advanced analytics. Additionally, finalists will be reimbursed up to $8,000 for travel expenses to attend the Phase 2 live event, where they will have the opportunity to showcase their solutions to FAA officials and the broader aviation community.
Judges for this competition may award 'Best in Class' certificates for different categories.
Phase 2 Prizes
In Phase 2, the competition intensifies with a total prize purse of $90,000, distributed to the university of the finalists based on the tiered system below. This structure ensures that each of the ten finalists is rewarded for their innovative solutions and contributions toward enhancing the National Airspace System (NAS) through AI/ML and advanced analytics.
Place | Prize Amount |
| 1st Place | $25,000 |
| 2nd Place | $20,000 |
| 3rd Place | $15,000 |
| 4th Place | $10,000 |
| 5th Place | $5,000 |
| 6th place (5 winners) | $3,000 |
All ten finalists who submit a technical paper meeting the challenge's minimum requirements, attend the live event, and present their solution will be eligible for these prizes.
