Jain College of Engineering & Research Belagavi
(Approved by AICTE, New Delhi, affiliated to VTU Belagavi & Recognized by Govt. of Karnataka)
Department of Electronics & Communication Engineering
A Mini Project Synopsis on
“Voice Assistant Smart Wheel Chair”
Project Associates
Mr. Shridhar M Bhopale (2JR22EC053)
Ms. Anushka A Naik (2JR23EC400)
Mr. Shamshoddin A Shaikh (2JR23EC405)
Ms. Snehal S Punekar (2JR23EC406)
Under the guidance of
Prof. Chaitanya K. Jambotkar
Subject Code: BEC586
Abstract
Smart Wheelchair is known as a Power Wheelchair that is integrated into multiple
sensors, assistive technology, and computers that give the user with a disability such as
impairment, handicaps, and permanent injury, the required mobility to move freely and
safely. These types of wheelchairs are gradually replacing the traditional wheelchairs;
however, their expensive costs are preventing a large size of disabled people from
having one. According to the organization of World Health (WHO), only 5 to 15% out
of 70 million disabled people have access to wheelchairs. Therefore, we need to offer a
cost-effective Smart that not only minimized the cost but also provides plenty of
features that use the latest components and technologies. In the last years, there have
been many pleasant efforts that serve this purpose. They have adopted various
technologies such as artificial intelligence, where they have designed an autonomous
wheelchair that used machine learning concepts to navigate, and some also used
Internet of Thing technology to control the wheelchair-using voice recognition system.
This report will present a cost-effective Smart Wheelchair-based Arduino Uno
microcontroller and IoT technology that have several features to gain disabled people,
especially poor people who cannot afford expensive Smart Wheelchair, the required
help to finish daily life tasks without external help. To conclude this project will make
the Smart Wheelchair affordable to a wide range of disabled people and will be based
on Arduino Uno, ESP-12e module to give Wi-Fi access, MPU6050 to detect fall with
Voice message notification using IFTTT platform, obstacle detection with buzzer and
LED to work as hazards, voice recognition system, and joysticks to control the
wheelchair.
Keywords— Smart Wheelchair; IoT Technology; Arduino; obstacle detection; voice
recognition system; joystick; health monitoring system
Problem Statement
For many disabled or paralyzed individuals, moving around independently is a daily
challenge, as traditional mobility aids often require physical effort that they may not be
able to provide. This lack of accessible, hands-free control can limit their freedom and
make them dependent on others for basic mobility. There is a need for a solution that
allows them to move safely and easily through voice commands, empowering them to
navigate their environment independently and improving their quality of life.
Literature Survey
Ghorbelet.al [1] discussed the idea of shared control of the motorized wheelchair.
They used ATMega 328 microcontroller, 16 * 2 LCD and joystick to make the user-
friendliness of the system. Reddy and Kumar [2] gave a proposal for a smart
wheelchair that could be connected to the smartphones of the patients’ guardians.
They also found a method to include an IoT service to regularly monitor the patient's
condition. Bastos-Filho et al[3] created an brain waves might be detected through an
interface. Pu-et-al [4] worked on the wheelchairs with an obstruction detection
technique that used an RGB camera, an IR camera, a LIDAR, and ultrasonic sensors.
A smart wheelchair, also known as a power wheelchair, is outfitted with a variety of
sensors,cutting-edge technology, and monitors to help people with physical disabilities
travel freely and safely.
These wheelchairs are taking the place of conventional wheelchairs, however because
of its exorbitant price, the wheelchair is out of reach for many who are less fortunate
financially. WHO conducted a survey in 2016 and concluded that only6 to 16% of 75
million people have access to conventional wheelchair. Therefore, the high cost of
this wheelchair is the one of the main reasons which is preventing the majority of
disabled people to buy this wheelchair.
In this project we will try to focus on developing a wheelchair that is equipped with
plenty of features and use the latest technology in minimal cost. To conclude this
project, we will be giving the following features in our wheelchair – two modes of
control (autonomous and manual), fall detection with a voice notification, obstacle
detection with sound, etc. smart wheelchair technology has the potential to greatly
improve the mobility and independence of individuals with disabilities. It is an area of
active research and development, with numerous advancements being made in the
field. While there are some challenges that need to be addressed, the overall outlook
for smart wheelchair technology is promising, and it is likely to become an
increasingly important part of the healthcare and assistive technology landscape in
the coming years.
Objectives
To enhance the independence and mobility of patients by enabling hands-free
control of wheelchair movement.
To provide a simple and intuitive voice interface that allows patients to navigate
their environment safely and efficiently.
To improve patient comfort and convenience by offering features such as speed
control, direction control, and obstacle detection through voice commands.
To monitor patient health by integrating sensors and providing voice-activated
updates on parameters like heart rate, body temperature, or position.
Methodology
Fig 1. Block Diagram of the Proposed Concept
The proposed methodology mainly involves 3 steps:
1. Voice Command Setup: Create a list of simple voice commands (like "move
forward," "turn left," "stop") and program the wheelchair to recognize them.
2. Integration of Sensors: Add sensors to the wheelchair that detect obstacles, so
the wheelchair can automatically stop or avoid hazards when a command is
given.
3. Speech Processing Software: Use speech recognition software to understand
the user’s voice commands and convert them into actions for the wheelchair to
follow.
References
[1]. A. Jayakody, A. Nawarathna, I. Wijesinghe, S. Liyanage and J. Dissanayake, "Smart
Wheelchair to Facilitate Disabled Individuals", 2019 International Conference on Advancements
in Computing (ICAC), pp. 249-254, 2019.
[2]. C. Shahnaz, A. Maksud, S. A. Fattah and S. S. Chowdhury, "Low-cost smart electric
wheelchair with destination mapping and intelligent control features", 2017 IEEE International
Symposium on Technology and Society (ISTAS), pp. 1-6, 2017.
[3]. M. M. Rahman, S. Chakraborty, A. Paul, A. M. Jobayer and M. A. Hossain, "Wheel therapy
chair: A smart system for disabled person with therapy facility", 2017 International Conference on
Electrical Computer and Communication Engineering (ECCE), pp. 630-635, 2017.
[4]. R. Alkhatib, A. Swaidan, J. Marzouk, M. Sabbah, S. Berjaoui and M. O. Diab, "Smart
Autonomous Wheelchair", 2019 3rd International Conference on Bio-engineering for Smart
Technologies (BioSMART), pp. 1-5, 2019.
[5]. P. V. Baiju, K. Varghese, J. M. Alapatt, S. J. Joju and K. M. Sagayam, "Smart Wheelchair for
Physically Challenged People", 2020 6th International Conference on Advanced Computing and
Communication Systems (ICACCS), pp. 828-831, 2020.
