Voice Controlled Wheelchair

Main Article Content

Article Sidebar

Published Sep 28, 2021
Sivakumar Rajagopal Soorya Prakash K Dinesh V.P Nithiyaraj V

Abstract

The proposed system is a smart voice-controlled wheelchair with an integrating flame sensor. The wheelchair is the most ubiquitous equipment used by people with lower limb disabilities as well as aged people who are not able to move independently because of their weakness [1-4]. Though many people’s needs are satisfied with traditional, manual, or powered wheelchairs, there are some individuals with both upper and lower limb disabilities and hands and arms impairment who find traditionally existing wheelchairs difficult to operate and are pushed into a situation where they are in need of help from other people around to control the wheelchair. A voice-controlled wheelchair is operated by using the voice commands through the given input which makes access easy for those people and lets them travel independently. This system also offers automatic protection alerts [5-7].

The voice recognition API is the key feature of this project that is used to set up the desired voice command and output (Figure 1). Voice recognition API here means a system for computer analysis of human voice, especially for the purposes of interpreting words and phrases or identifying an individual voice and it converts the recognized voice command into text and sends the command text to the HC-05 Bluetooth module. The Bluetooth module transmits the converted text command to Arduino (Figure 2). When Arduino receives the command it acts as per corresponding coded data stored in the memory to Arduino Microcontroller. L298N motor driver controls the locomotion accordingly along with making the movement easier. The integrated flame sensor checks the surrounding environment to ensure the safety of the user and updates the caretaker by sending a message to their mobile (Figure 3). The main objective of this project is to provide an effortless movement and low-cost wheelchair that is available to everyone in need.

How to Cite

Rajagopal, S., Soorya Prakash K, Dinesh V.P, & Nithiyaraj V. (2021). Voice Controlled Wheelchair. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/1234
Abstract 87 |

Article Details

References
[1] Journal by Takashi Gomi and Ann Griffith, applied AI Systems, Inc. Developing In- telligent Wheelchairs for the Handicapped.

[2] Gakopoulos S, Nica IG, Bekteshi S, Aerts JM, Monbaliu E, Hallez H. Development of a Data Logger for Capturing Human- Machine Interaction in Wheelchair Head-Foot Steering Sensor System in Dyskinetic Cerebral Palsy. Sensors (Basel). 2019; 19(24) : 5404. Published 2019 Dec 7. doi:10.3390/s19245404

[3] https://www.researchgate.net/publi cation/319442825_Voice_Controll ed_Wheelchair

[4] https://www.mdpi.com/1424- 8220/20/19/5510

[5] S. Desai, S. S. Mantha and V. M. Phalle, "Advances in smart wheelchair technology," 2017 International Conference onNascent Technologies in Engineering (ICNTE), 2017, pp. 17, doi: 10.1109/ICNTE.2017.7947914.

[6] https://www.javatpoint.com/arduin o-serial-serial-
begin#:~:text=The%20baud%20rat e%20signifies%20the,%2C%20384 00%2C%2028800%2C%20etc

[7] https://roboindia.com/tutorials/send ing-receiving-with-hc05-mit-appinventor/
Section
SE1: Sensors

Most read articles by the same author(s)

1 2 > >>