EasyVizAR: Supporting First Responders Through the Use of Collaborative Augmented Reality Tools
First responders operate in high-stakes environments, demanding rapid, accurate decision-making. Recent research has provided recommendations on how Augmented Reality (AR) could be utilized to support their efforts. Building off of these studies, this paper presents EasyVizAR, an AR system designed to enhance situational awareness and operational efficiency in challenging indoor scenarios. Leveraging edge computing and advanced computer vision techniques, EasyVizAR addresses critical challenges, such as object detection, localization, and information sharing. This research details the system’s architecture, including its use of ParaDrop-based edge computing, and explores its application in rescue and active-shooter scenarios. We present our work in developing key features, including real-time object saliency cues, improved object detection, person identification, multi-user 3D map generation and visualization, and multimodal AR navigation cues.
Authors
- Suman Banerjee (ORCID: https://orcid.org/0000-0002-5548-8862)
- Ross Tredinnick (ORCID: https://orcid.org/0000-0003-0540-9561)
- Kevin Ponto (ORCID: https://orcid.org/0000-0003-4156-9693)
- Lance Hartung (ORCID: https://orcid.org/0000-0001-5897-9205)
- Bryce Sprecher (ORCID: https://orcid.org/0009-0009-3146-3749)
- Yuhang Zhao (ORCID: https://orcid.org/0000-0003-3686-695X)
Institutions
- University of Wisconsin–Madison (US)
- Wisconsin Institutes for Discovery (US)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-10-28
- DOI
- https://doi.org/10.3390/app152111498
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Standards and Technology