SmartCare Assist: An IoT-Based System for Eye-Guided Wheelchair Navigation, Fall Detection, and Hand Gesture Communication for Disabled Individuals
Anish Roy, Mufti Mahmud, Shah Muhammad Azmat Ullah · 2025
This is representative of the motivation to redevelop assistive technologies for persons with disabilities through innovative solutions that address independence, safety, and mobility. This paper introduces SmartCare Assist, an integrated IoT system to help overcome some of the most critical challenges faced by wheelchair users and people with limited mobility. In this work, SmartCare Assist allows three key functions: eye-gaze-controlled wheelchair navigation, fall detection alert mechanism, and wireless communication using hand gestures. The eye-gaze navigation module utilizes Dlib-68-point face landmark detection and OpenCV for real-time eye movement tracking. Furthermore, the system incorporates an MPU6050 gyroscope sensor and an ESP8266 Wi-Fi module fall detector, which trigger instant alerts on the IFTTT cloud platform, allowing caregivers to receive real-time emergency notifications on their smartphones. It also enables wireless command execution with hand-gesture communications based on gyroscope-based movement detection. Our results show that in various scenarios, the system has the potential to ensure feasibility, reliability, and responsiveness toward improving the life quality of individuals with physical impairments. Future iterations are set to enable obstacle avoidance while optimizing stability for increased functionality and a better user experience.