2026 ASEE Annual Conference & Exposition

This research explores various applications of Unmanned Aerial Systems (UASs) as a means to engage lower-level undergraduate students in hands-on projects within the Aerospace Education and Research (AERO) Lab. While many early-stage undergraduate students express interest in research, they often lack a clear understanding of what it entails. To bridge this gap, students participate in diverse projects that involve the integration of sensors—such as thermal imaging, RGB, and infrared cameras—mounted on UAS platforms for data collection and analysis.
In one project, students develop a real-time thermal imaging system to assess human conditions using live UAS footage. The system distinguishes between conscious (upright) and unconscious (fallen) individuals by analyzing thermal video streams transmitted directly from the UAS to a ground station. A deep learning model, based on YOLOv12, is trained on a custom thermal dataset featuring a variety of human postures and environmental conditions. This solution offers a reliable and privacy-conscious approach for applications in safety monitoring, search-and-rescue missions, and emergency response scenarios.
Another project focuses on real-time pedestrian detection using Artificial Intelligence (AI) models. Students collect original aerial footage using UASs to evaluate the accuracy and performance of these models in detecting and counting humans from different altitudes and under varying lighting conditions. Potential use cases include crowd monitoring at outdoor events, locating missing persons, and enhancing security in open public areas.
This paper will detail each project and highlight student learning outcomes, feedback, and opportunities for improvement.