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A Digital Twin Navigation System for Hospital Supply Rooms: 3D Spatial Guidance Tool
Rugved Parmar1, Nischal Sharma1, Adam Budzikowski2
1SUNY Downstate Health Sciences University, Department of Internal Medicine, New York, United States, New York.
Applied Clinical Informatics
|May 28, 2026
Summary
A new 3D digital twin system can help clinicians quickly find supplies in hospital storage rooms. This technology uses web-based tools to improve navigation and reduce time spent searching for items.
Area of Science:
- Health Informatics
- Computer Science
- Spatial Cognition
Background:
- Hospital supply rooms present challenges for clinicians due to their complex, dense, and vertically oriented nature.
- Current text-based inventory systems increase cognitive load by requiring mental translation of codes to physical locations.
- Digital twin technology, while growing in healthcare, remains underreported for supply room navigation applications.
Purpose of the Study:
- To design and assess the feasibility of a browser-based 3D digital twin system for spatial guidance in hospital supply rooms.
- To provide an efficient solution for locating medical supplies within complex storage environments.
Main Methods:
- Developed a 3D digital twin using React and Three.js to model a hospital clean supply room.
- Implemented instanced rendering for over 100 storage bins.
- Integrated a text-based search interface that highlights target bins and animates camera movement.
Main Results:
- The digital twin prototype demonstrated rapid search response times (sub-10 ms) and fast loading (under 1 second) on standard hardware.
- Informal user walkthroughs indicated positive initial reception, though formal usability studies are pending.
Conclusions:
- A 3D digital twin approach is technically feasible for improving hospital supply room navigation using cost-effective, open-source web technologies.
- This system addresses spatial cognition challenges inherent in dense healthcare storage environments.
- Further formal usability evaluations are necessary to quantify the clinical impact and benefits.
