Federal Aviation Administration, Civil Aeromedical Institute
University of North Florida
Embry-Riddle Aeronautical University
California State University, San Bernardino
Prototype Ai Assistant For Private And Student Pilots,
2026
Embry-Riddle Aeronautical University
Prototype Ai Assistant For Private And Student Pilots, Shawn De La Osa
Discovery Day - Daytona Beach
This research explores AI-based decision support in light general aviation (e.g., Cessna 172, Diamond), where onboard hardware is typically too limited for modern AI. In aviation, AI has the potential to act as a “copilot” supporting planning, execution, and assessment, particularly since single pilots must simultaneously aviate, navigate, and communicate under high workload. However, although AI adoption is rapidly expanding, many implementations are introduced without fully incorporating human-centered design processes that account for pilot workflow and workload. We leverage a human factors process in this research. First, we design and evaluate a cloud-based AI copilot . The system leverages Starlink …
Flight Testing And System Identification Of An Experimental Cessna 182,
2026
Embry-Riddle Aeronautical University
Flight Testing And System Identification Of An Experimental Cessna 182, Mariano Chavez Rangel
Discovery Day - Daytona Beach
Flight testing and system identification are essential for accurately characterizing aircraft dynamics and supporting the development of reliable flight control systems. This work presents the use of an experimental Cessna 182 as a full-scale platform for flight testing and system identification, conducted by the Eagle Flight Research Center. The objective is to generate high-fidelity flight data to estimate aerodynamic and dynamic coefficients and establish a baseline model for comparison with a sub-scale aircraft incorporating Integrated High-Lift Propulsor (IHLP) technology. The experimental aircraft is equipped with a comprehensive onboard instrumentation suite designed to capture synchronized measurements of air data, aircraft motion, …
Adaptive Health Monitoring For Runtime Safety Assurance Of Advanced Air Mobility Applications,
2026
Embry-Riddle Aeronautical University
Adaptive Health Monitoring For Runtime Safety Assurance Of Advanced Air Mobility Applications, Michael Budihartono, Francisco Bustamante, Gabriela Gavilanez
Discovery Day - Daytona Beach
This work proposes a comprehensive, adaptive framework for abnormal condition detection and flight envelope prediction in complex systems. The approach integrates data reduction techniques, including principal component analysis and lower-dimensional projections, to efficiently distinguish between nominal and abnormal operational states while maintaining computational efficiency through metacognitive interventions. A hybrid detection architecture combines bio-inspired real-value negative selection algorithms with support vector machines, augmented by generative machine learning models to synthesize failure data and support training through digital twin environments. Online fault trend analysis enables continuous monitoring of system degradation, while the system dynamically adapts to operational variations by minimizing offline training …
Crowd Monitoring And Firearm Detection Uas,
2026
Embry-Riddle Aeronautical University
Crowd Monitoring And Firearm Detection Uas, Arjun Nambiar, Sang-A Lee, Diego Espino, Will Obot Jr, Ethan Encarnacion, Jarrett Usui, Jacob D. Kline
Discovery Day - Daytona Beach
The increasing complexity of public safety operations in urban and high-density environments necessitates intelligent, mobile surveillance systems capable of real-time threat identification and situational awareness. Traditional monitoring approaches, such as fixed CCTV systems and manual observation, are often limited by coverage, scalability, and response latency in complex environments or large-scale events. This project addresses these challenges through the development of a computer vision-enabled Uncrewed Aerial System (UAS) designed for crowd monitoring and firearm detection. The primary objective is to design and validate a modular, Artificial Intelligence (AI)-Machine Learning (ML)-driven model capable of identifying firearms within dynamic environments while supporting real-time …
Characterizing Air Traffic Density Using Nationwide Ads-B Data,
2026
Embry-Riddle Aeronautical University
Characterizing Air Traffic Density Using Nationwide Ads-B Data, Taeyun Yoo, Arjun Nambiar, Sang-A Lee
Discovery Day - Daytona Beach
This study addresses the increasing need to understand aircraft activity in low-altitude airspace, where emerging operations such as Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) are expected to heighten traffic complexity and safety risks. This research develops a scalable framework for constructing a nationwide, high-resolution, altitude-stratified airspace density atlas using Automatic Dependent Surveillance–Broadcast (ADS-B) data. The methodology incorporates large-scale data acquisition, terrain-referenced altitude normalization, and spatial aggregation using a hexagonal grid system, followed by statistical modeling to estimate traffic density across spatial and temporal dimensions. Preliminary results indicate the capability to generate detailed geospatial representations of aircraft activity, …
Spatial Dynamics Of Lead Waste: An Esda Approach To U.S. Interstate Transfers,
2026
Embry-Riddle Aeronautical University
Spatial Dynamics Of Lead Waste: An Esda Approach To U.S. Interstate Transfers, Santiago Acuna Gonzalez
Discovery Day - Daytona Beach
Spatial Dynamics of Lead Waste: An ESDA Approach to U.S. Interstate Transfers This research applied a novel Exploratory Spatial Data Analysis (ESDA) methodology to analyze interstate movements (n= 446) of lead (Pb; CAS 7339-92-1) among facilities that transported more than 1,000 lbs offsite across the United States, using the Environmental Protection Agency’s (EPA) 2024 Toxic Release Inventory (TRI). Using QGIS, the analysis produced three geospatial products by integrating TRI Form R Schedule 3A with coordinates from the EPA Facility Registry Service (FRS) to populate offsite locations. First, a state-level net-flow choropleth distinguished exporting from importing states. Second, an export-focused map …
Environmental Ethics And Impact Of Artificial Intelligence Data Centers,
2026
Embry-Riddle Aeronautical University
Environmental Ethics And Impact Of Artificial Intelligence Data Centers, Jacky Yang
Discovery Day - Daytona Beach
Data centers, including artificial intelligence (AI) facilities, serve as the backbone for many modern digital services and products. With the rapid digitization of society, the expansion of these centers in the United States has accelerated significantly. From an anthropocentric and utilitarian perspective, they provide economic benefits, supporting employment and generating public revenue. However, they can also create a significant amount of environmental and societal challenges. From an ecocentric and environmental justice perspective, AI data centers has contributed to increased competition for the limited resources, such as water, electricity, and land and has been linked to rising utility costs, noise pollution, …
Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation,
2026
Embry-Riddle Aeronautical University
Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth
Discovery Day - Daytona Beach
Understanding the complex causal relationships underlying aviation accidents is critical for improving safety and preventing future incidents. However, much of this information exists in unstructured narrative reports, making large-scale analysis difficult. This project aims to automatically extract and model causal chains from National Transportation Safety Board (NTSB) accident narratives using a combination of traditional natural language processing (NLP) techniques, transformer-based architectures, and graph-based knowledge representation. Traditional NLP methods, including named entity recognition, dependency parsing, and rule-based pattern matching, will be used to identify structured cause–effect relationships. These approaches will be compared with transformer-based models, including a lightweight encoder for classification …
Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes,
2026
Embry Riddle Aeronautical University
Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon
Discovery Day - Daytona Beach
Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes examines how cybersecurity risks differ across major transportation sectors and addresses the lack of a structured, cross modal analysis in existing transportation cybersecurity research. As transportation systems increasingly rely on digital infrastructure, communication networks, operational technologies, and interconnected platforms, they become more exposed to cyber threats that can affect safety, mobility, operations, and public trust. Despite the growing importance of this issue, there is still limited research that quantitatively compares how cyber risks vary across transportation modes such as road and intelligent transportation systems, aviation, rail and transit, and maritime systems. …
Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning,
2026
Embry-Riddle Aeronautical University
Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang
Discovery Day - Daytona Beach
Runway incursions remain one of the most persistent safety challenges in modern aviation operations, often resulting from complex interactions among human, environmental, and operational factors. While existing Safety Management System (SMS) frameworks emphasize monitoring the frequency of incursions, they provide limited predictive capability regarding event severity. This ongoing study seeks to address that gap by applying a novel tabular-to-image deep-learning approach to improve the accuracy and interpretability of runway-incursion severity prediction models. Data for this study will be drawn from the Federal Aviation Administration (FAA) Runway Safety Statistics and National Transportation Safety Board (NTSB) accident databases. The methodology will involve …
Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions,
2026
Embry-Riddle Aeronautical University
Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan
Discovery Day - Daytona Beach
The effective implementation of Safety Management Systems (SMS) at airports depends not only on compliance with regulatory requirements but also on the presence of a strong and measurable safety culture. While the Federal Aviation Administration (FAA)’s increasing emphasis on SMS has accelerated adoption across certificated airports, many airport operators, often coming from operational, engineering, or business backgrounds, lack practical methods to assess safety culture in a structured and actionable manner. Existing guidance highlights the importance of safety culture and safety climate. However, limited research exists on how airport stakeholders perceive and experience safety culture within the airport operating environment. This …
Sequential Causal Architecture For Multimodal Aviation Accident Prediction,
2026
Embry-Riddle Aeronautical University
Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison
Discovery Day - Daytona Beach
Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …
Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac,
2026
Embry-Riddle Aeronautical University
Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana
Discovery Day - Daytona Beach
Air traffic congestion is an increasingly important factor in aviation safety as global flight activity continues to grow. This project investigates whether higher traffic density is associated with an increased risk of aviation incidents and identifies key contributing factors. Using publicly available flight (ADS-B) and incident (NTSB) data, we apply several machine learning models to analyze traffic patterns and predict risk. We begin with logistic regression to evaluate the relationship between density and incident probability, followed by decision trees to extract interpretable rules describing high-risk conditions. K-nearest neighbors (KNN) is used to examine similarity in traffic patterns among incident flights, …
Impact Of Stress & Fatigue On Cardiovascular Function In Young Pilots: A Thematic Review,
2026
Embry-Riddle Aeronautical University
Impact Of Stress & Fatigue On Cardiovascular Function In Young Pilots: A Thematic Review, Swarna Manoj
Discovery Day - Daytona Beach
Impact of Stress & Fatigue on Cardiovascular Function in Young Pilots: A Thematic Review Authors: Swarna Manoj, Scott Ferguson Keywords: pilot, stress, fatigue, heart rate variability (HRV), cardiovascular disease (CVD) Aviation is expanding globally and young pilots are the major workforce, yet FAA protocols require mandatory ECG only from age 35, with annual cardiac screening after age 40. Over the past five years, a pattern of sudden cardiac arrests in pilots particularly aged 30-40 has urged safety concerns. Despite the existing literature examining fatigue, burnout, stress, sleep hygiene and circadian disruption, only few studies systematically examine how these factors impact …
Human Factors Challenges In Automated Flight Operations,
2026
Embry-Riddle Aeronautical University
Human Factors Challenges In Automated Flight Operations, Jorge Ivan Gonzalez Rivera, Zoe Guyette, Emma Hatten, Katie Huynh, Benjamin Marsh
Discovery Day - Daytona Beach
Automation complacency, a critical aviation hazard, is commonly seen amongst flight crews in high-automation commercial flight decks. This issue occurs when over-reliance on automated systems leads to a decline in manual flying expertise and situational awareness, posing a severe risk of loss of control in-flight (LOC-I) and catastrophic accidents. To bridge the safety gap between current operational demands for efficiency and the regulatory requirement for pilot proficiency, this study proposes the Manual Flight Compliance and Monitoring System (MFCMS). This solution integrates engineering and administrative controls to reduce automation-related risks by mandating 15 minutes of manual flight per hour during cruise …
Multimodal Interpretation Of Pilot–Controller Communications For Runway Safety Assurance And Enhanced Atc Situational Awareness.,
2026
Embry-Riddle Aeronautical University
Multimodal Interpretation Of Pilot–Controller Communications For Runway Safety Assurance And Enhanced Atc Situational Awareness., Chaebin Song, Juin Park
Discovery Day - Daytona Beach
Recent runway safety events have highlighted the importance of accurate and timely interpretation of pilot–controller communications, especially in complex airport environments where aircraft and ground vehicles interact on or near active movement areas. In light of the recent LaGuardia Airport collision, which has drawn attention to communication, coordination, and surface safety challenges, this project investigates how multimodal data can support air traffic controllers’ situational awareness and safety assurance. This study develops an in-progress framework that combines Automatic Speech Recognition (ASR) of pilot–controller radio communications with ADS-B trajectory data to improve interpretation of operational intent and cross-check communications against observed aircraft …
Applying The Hfacs Framework: A Case Study Of Air Florida Flight 90,
2026
Embry-Riddle Aeronautical University
Applying The Hfacs Framework: A Case Study Of Air Florida Flight 90, Ashley Perez-Galvan, Cenk Altinkum, Ryan Hunt
Discovery Day - Daytona Beach
Applying the HFACS Framework: A Case Study of Air Florida Flight 90 Abstract This study applies the Human Factors Analysis and Classification System (HFACS), a widely used safety framework for identifying human and organizational contributors to accidents to examine the crash of Air Florida Flight 90 crash on January 13, 1982. The accident occurred shortly after takeoff from Washington National Airport during severe winter weather, when the aircraft failed to gain sufficient lift and impacted a bridge before entering the Potomac River. The goal this analysis is to understand how multiple layers of human and organizational factors contributed to this …
The Impact Of Environmental Contributing Factors In Spatial Disorientation And Non-Spatial Disorientation Related General Aviation Accidents,
2026
Embry-Riddle Aeronautical University
The Impact Of Environmental Contributing Factors In Spatial Disorientation And Non-Spatial Disorientation Related General Aviation Accidents, Victoria Cornaro, Molly Mersinger
Discovery Day - Daytona Beach
The Impact of Environmental Contributing Factors in Spatial Disorientation and Non-Spatial Disorientation Related General Aviation Accidents Spatial disorientation (SD) is an inherent risk of flying and with a high risk of resulting in a fatal accident (Gibbs et al, 2011). SD related accidents occur when a pilot’s perception of the aircraft altitude, position, or relative motion conflict with reality (Benson, 1999). SD accidents are significantly more likely to result in a fatality than non-SD cases. The purpose of this study was to investigate the role of different contributing factors on SD and non-SD general aviation accidents. We used the NTSB …
Remora Ads-B In Receiver,
2026
Embry-Riddle Aeronautical University
Remora Ads-B In Receiver, Noah Evans, Sara Patel, Nicholas Gatto, Daniel Ingleton
Discovery Day - Daytona Beach
The Remora is a compact Automatic Dependent Surveillance Broadcast (ADS-B) receiver, designed to enhance situational awareness for pilots operating experimental and homebuilt aircraft. Unlike conventional panel or windscreen-mounted systems, the Remora is installed externally, making it a low-profile solution to the ADS-B In challenge. The device integrates easily with the aircraft’s existing power supply. It transmits data wirelessly to electronic flight bags (EFBs) within the cockpit, using existing iOS and Android software for display and user interaction. The primary function of the Remora is to provide public-access, real-time traffic awareness and weather forecasting, enabling pilots to make informed mission decisions. …
Human Factors And Passenger Survival In Aircraft Emergency Evacuations,
2026
Embry-Riddle Aeronautical University
Human Factors And Passenger Survival In Aircraft Emergency Evacuations, Anjelysa Oleszewski, Adam Dvorak, Anthony Bulko, Christopher Lee, Nicholas Murphy
Discovery Day - Daytona Beach
In the event of an emergency where evacuation of the aircraft is necessary, passengers have 90 seconds to locate their nearest exit and egress as safely and quickly as possible. However, news outlets have reported multiple occurrences of passengers evacuating and taking their belongings with them during this decade. The root of this hazard occurs in multiple areas of flight, particularly during safety briefings and during emergency evacuations. The purpose of this project is to focus on improving passenger knowledge of safety features such as exit door locations through digital mediums and strengthen deliverance of life-saving information. The project shares …
