Project Team
Students
Suryansh Sijwali
Computer Science
Harrisburg
Faculty Mentors
Seth Wolpert
Harrisburg
School of Science, Engineering, and Technology
Project
https://sites.psu.edu/mcreu/files/formidable/2/2024-07-25/REU_Poster_UAVforDM_SS.pdf
Project Video
Project Abstract
Disaster response requires rapid assessment and detailed data to guide critical decisions. While Unmanned Aerial Vehicles (UAVs) offer valuable data collection capabilities, current systems struggle with object detection accuracy in chaotic environments, lack real-time detailed terrain mapping, and have limitations in data transmission speed and reliability. This research addresses these challenges by proposing a groundbreaking UAV system. The system integrates cutting-edge technologies including advanced object detection with adaptive feature fusion for superior accuracy, LiDAR-based real-time terrain mapping for detailed 3D visualizations, and a high-speed optical communication system for reliable data transmission. This comprehensive approach empowers first responders with a clear picture of the disaster zone, facilitating faster and more targeted rescue efforts, ultimately saving lives and minimizing damage during critical events.
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