SafetyBuilder: An AR-based Framework for In-situ AI-assisted Creation of Child Safety Protection
Children often encounter safety hazards, such as sharp table corners or exposed electrical outlets, which are out of their radar. Childcare providers may lack awareness of these hazards and the technical expertise required to design effective protective solutions. To address this, we propose SafetyBuilder, an AR-based framework that enables childcare providers to detect safety hazards in the environment and create customized protective devices for 3D printing. The framework comprises three core components: real-time environmental hazard detection, AI-assisted suggestions for protective measures, and in-situ customization of 3D printable protective devices. We then evaluated SafetyBuilder via design workshops involving 10 participants and user testing of a proof-of-concept prototype system with nine participants. The results showed that the framework effectively supports users in identifying potential hazards, creating customized protective devices, and improving their confidence in managing child safety risks.
Authors
- Tao Chen (ORCID: https://orcid.org/0000-0001-9704-9545)
- Ziyan Wang (ORCID: https://orcid.org/0000-0002-8941-8926)
- Zisu Li (ORCID: https://orcid.org/0000-0001-8825-0191)
- Liang He
- Jiawei Li
- Mingming Fan
- Yukai Zhang
Institutions
- Guangdong University of Technology (CN)
- The University of Texas at Dallas (US)
- Hong Kong University of Science and Technology (HK)
- University of Hong Kong (HK)
Publication Details
- Journal
- Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
- Published
- 2026-03-16
- DOI
- https://doi.org/10.1145/3789690
- Citations
- 1
- Primary Topic
- Innovative Human-Technology Interaction
- Type
- article
- Field-Weighted Citation Impact
- 36.85