Emergency Assistive Mobile Application with Digital Twin for Real-Time 3D Navigation in Indoor Environments
Navigation in indoor environments during emergencies can be challenging for individuals with visual impairments, mobility issues and cognitive disabilities. Traditional navigation methods fail to provide the necessary support in complex, dynamic indoor buildings such as office buildings, hospitals, or shopping malls. This paper seeks to introduce a novel assistive technology platform that leverages real-time 3D spatial awareness to promote safe and efficient navigation in an indoor building environment. By leveraging 3D spatial mapping technology, the mobile application creates a highly detailed and dynamic representation of the indoor building environment. The proposed mobile application offers precise real-time updates on the user, detecting obstacles, entrances, and the directions to the exit. The device camera determines the user’s location and maps it to a corresponding position within the building’s Digital Twin and continuously adjusts navigation path within the building. It utilizes a combination of sensors, cameras and artificial intelligence to process and interpret building layout in real-time. It provides personalized navigation cues, adjusting to the user’s pace and preferences, ensuring that the guidance remains both effective and non-intrusive. By providing timely, personalized, and adaptive navigation instructions, the mobile application ensures that users can make informed decisions about their route, avoid hazards, and locate exits or safe zones efficiently. A limited user study was conducted to test the effectiveness of the proposed mobile application using the mobile phone usability questionnaire (MPUQ). The results showed that the mobile application was relatively easy to use and the digital twin was an accurate representation of the surroundings.
Authors
- Sharad Sharma (ORCID: https://orcid.org/0000-0001-7528-4616)
- B. C. Bhatt (ORCID: https://orcid.org/0000-0002-4582-1879)
- Andrew Summitt
Institutions
- University of North Texas (US)
Publication Details
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1109/sera65747.2025.11154602
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00