Preface
The Smart Wheelchair project was conceived in the electrical and electronics department of BMS College of Engineering by the batch of 2009-2013 with an aim to provide convenient locomotion for paraplegics and quadriplegics. The wheelchair then, was an automated one which provided features like obstacle detection, accelerometer based motion and DTMF based mobile control. It was implemented on an Arduino board with an Atmel Atmega 8 microcontroller.
This project was then taken forward as an inter-disciplinary project by the batch of 2010-14 with the students of Electrical and Electronics Engineering being the flag bearers.
A ground survey was conducted to evaluate the need and present status of wheelchairs in the market. The usability and the shortcoming were also evaluated and that became the basis for this implementation of Smart Wheelchair.
After the batch of 2014 took over the project, the control system for the wheelchair was revamped and was replaced by a single powerful computing device called the Raspberry Pi. The Raspberry Pi acts as a central control unit which coordinates and communicates between various modules of the Wheelchair. The modular existence of the control entities is a unique feature of the smart wheelchair which allows the user to choose what best suits his needs.
Extensive work has been done on various techniques like image processing and speech processing which did not give satisfactory results and hence was scrapped as control option for the wheelchair.
The smart wheelchair project has been funded under the TEQIP-II initiative by the World Bank.
The project deals with the designing of the technology behind the control of these intelligent wheelchairs. The goal of this smart wheelchair project is to enhance an ordinary powered wheelchair with navigation keys for the self-mobility, authenticated access of one’s own medical records from the connected hospital’s database and to obtain help during emergencies. Strategies would be developed to accomplish newly-identified goals which may involve additional sensors, computing and interfaces.