Title: AI-based behaviour-aware path risk assessment for wheelchair-centric smart assistive devices

Authors: Chiao-Wen Kao; Shih-Tung Wang; Chi-Sheng Huang

Addresses: Department of Applied Artificial Intelligence, Ming Chuan University, Taiwan ' Department of Applied Artificial Intelligence, Ming Chuan University, Taiwan ' Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taiwan

Abstract: Mobility challenges in aging societies underscore the need for safer navigation solutions for wheelchair users, who often face hazards like uneven surfaces and indistinct curbs. Addressing these concerns, this study introduces an AI-based behaviour-aware path risk assessment system designed for wheelchair-centric assistive devices. The system combines object detection and semantic segmentation to identify critical road features, such as sidewalks, curbs, and lanes. A path risk assessment module evaluates path safety using a scoring algorithm incorporating regional weighting and adjusting to varying environmental conditions. Integrating internet of behaviour principles, the system adapts dynamically to user behaviours and conditions, offering personalised risk assessments. Tested on a custom dataset, the system demonstrated accurate real-time evaluations, with horizontal camera orientations excelling in dynamic scenarios and vertical setups suited for detailed analysis. These findings highlight its potential to enhance safety and mobility, with future work focusing on dynamic obstacles and multi-view integration for broader applications.

Keywords: behaviour-aware systems; smart assistive devices; path risk assessment; semantic segmentation; wheelchair-centric.

DOI: 10.1504/IJAHUC.2026.153817

International Journal of Ad Hoc and Ubiquitous Computing, 2026 Vol.52 No.1, pp.1 - 15

Received: 20 Dec 2024
Accepted: 20 Feb 2025
Published online: 27 May 2026 *

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