SISCMot: Situation Inference and Monitoring System for Intelligent Motorized Wheelchairs

Assistive technologies aim to enhance independence and social inclusion for individuals with motor disabilities. Leveraging the Internet of Things (IoT), this study introduces SISCMot, an innovative monitoring and inference system tailored for intelligent motorized wheelchairs. SISCMot incorporates real-time data acquisition from the wheelchair’s electromechanical components, enabling context-aware analysis through IoT-connected dashboards. This system benefits a comprehensive range of stakeholders—including users, caregivers, technical support, and manufacturers—by providing critical insights into component performance, user mobility, and potential maintenance needs. Additionally, SISCMot offers a unique edge in preventive maintenance by monitoring key mechanical and electrical metrics, thereby extending the wheelchair’s operational lifespan. Evaluation based on the Technology Acceptance Model (TAM) confirms high usability and perceived value among target users, underscoring the system’s practical contribution to the assistive technology landscape.