Human-Computer Interaction Commons^™

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Learning To Refine Gesture-Derived Voxel-To-Loop For Generative 3d Modeling In Vr, Kallen Lonbom, Trudi Di Qi

Engineering Faculty Articles and Research

We present a generative modeling pipeline for refining and denoising coarse 3D shapes created through freehand interaction in virtual reality (VR). While recent loop-based generative models focus on shape synthesis from clean inputs, our work addresses the challenge of reconstructing coherent geometry from noisy, coarse volumetric data. To this end, we introduce a hybrid voxel-to-loop representation that captures the topology of rough voxel shapes and converts them into sequential cross-sectional loops for generative refinement. We develop two transformer architectures and evaluate their efficacy primarily on synthetically perturbed datasets with additional examples from VR. Our results demonstrate that this representation is …