Detecting environmental barriers affecting older adult pedestrians via Gramian angular field-based CNN of smartphone sensor data
These findings demonstrate that image-based deep learning provides a practical and interpretable solution for real-time, personalized detection of environmental barriers, offering a scalable tool for data-driven walkability enhancement in age-friendly urban design.
Authors
- Sungkook Hong (ORCID: https://orcid.org/0000-0001-8962-9283)
- Jaeyun Kim (ORCID: https://orcid.org/0000-0002-4687-6732)
Institutions
- Dankook University (KR)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-11-05
- DOI
- https://doi.org/10.3389/fpubh.2025.1697589
- Citations
- 1
- Primary Topic
- Urban Transport and Accessibility
- Type
- article
- Field-Weighted Citation Impact
- 2.18