SWHEELS: THE SMART WHEELCHAIR

SWheels is a smart, voice-controlled wheelchair prototype designed to enhance mobility and independence for individuals with partial or complete paralysis. This project aims to bridge accessibility gaps by integrating advanced features such as voice command operation, joystick control, automatic speed adjustment on inclines, obstacle detection, fall detection, and real-time dash cam streaming. The system is powered by a Raspberry Pi 5 and dual ESP32 microcontrollers, enabling distributed processing for efficient control and safety management. Voice navigation interprets natural language instructions like “move forward for 10 meters” through a language model API, translating them into structured commands for motor control. The obstacle avoidance mechanism, implemented using six ultrasonic sensors (HC-SR04), ensures safe navigation in indoor environments such as hospitals and schools. Real-time video streaming is achieved via MJPG-Streamer, allowing live monitoring over a local network. SWheels follows a phased development approach, beginning with basic assistive mobility features, followed by autonomous navigation and path-learning capabilities. The successful implementation of this prototype demonstrates the viability of combining low-cost hardware with smart control logic to deliver a scalable, user-friendly mobility solution. The system’s modular design also supports future enhancements, such as gesture recognition and health monitoring, making it a promising candidate for further development in assistive technology.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-16
DOI
https://doi.org/10.5281/zenodo.15229054
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
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article

SWHEELS: THE SMART WHEELCHAIR

Zenodo (CERN European Organization for Nuclear Research)
Gaze Tracking and Assistive Technology
article

SWHEELS: THE SMART WHEELCHAIR

article en

Abstract

SWheels is a smart, voice-controlled wheelchair prototype designed to enhance mobility and independence for individuals with partial or complete paralysis. This project aims to bridge accessibility gaps by integrating advanced features such as voice command operation, joystick control, automatic speed adjustment on inclines, obstacle detection, fall detection, and real-time dash cam streaming. The system is powered by a Raspberry Pi 5 and dual ESP32 microcontrollers, enabling distributed processing for efficient control and safety management. Voice navigation interprets natural language instructions like “move forward for 10 meters” through a language model API, translating them into structured commands for motor control. The obstacle avoidance mechanism, implemented using six ultrasonic sensors (HC-SR04), ensures safe navigation in indoor environments such as hospitals and schools. Real-time video streaming is achieved via MJPG-Streamer, allowing live monitoring over a local network. SWheels follows a phased development approach, beginning with basic assistive mobility features, followed by autonomous navigation and path-learning capabilities. The successful implementation of this prototype demonstrates the viability of combining low-cost hardware with smart control logic to deliver a scalable, user-friendly mobility solution. The system’s modular design also supports future enhancements, such as gesture recognition and health monitoring, making it a promising candidate for further development in assistive technology.

Zenodo (CERN European Organization for Nuclear Research)
Institute of Engineering (NP)
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Gaze Tracking and Assistive Technology
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SWHEELS: THE SMART WHEELCHAIR · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS