Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3252
Title: Intelligent Wheelchair with Emotion Analysis and Voice Recognition
Authors: Perera, S
Gamage, S
Weerasinghe, C
Jayawardena, C
Pathinayake, K
Rajapaksha, S
Keywords: Intelligent Wheelchair
Emotion Analysis
Voice Recognition
Issue Date: 26-Dec-2022
Publisher: IEEE
Citation: S. Perera, S. Gamage, C. Weerasinghe, C. Jayawardena, K. Pathinayake and S. Rajapaksha, "Intelligent Wheelchair with Emotion Analysis and Voice Recognition," 2022 7th International Conference on Information Technology Research (ICITR), Moratuwa, Sri Lanka, 2022, pp. 1-6, doi: 10.1109/ICITR57877.2022.9992532.
Series/Report no.: 2022 7th International Conference on Information Technology Research (ICITR);
Abstract: Intelligent wheelchairs are becoming more and more prevalent in contemporary life, and the peaceful interaction of humans with wheelchairs is one of the most popular research topics. The development of a voice recognition and emotion recognition based intelligent wheelchair framework is being addressed here for truly impaired/disabled people who are unable to operate the wheelchair by hand. The patient can operate the wheelchair using voice commands, and the wheelchair’s Emotion Analysis module recognizes the patient’s face and records the patient’s emotions before sending the information to a cell phone application. A portion of the intelligent wheelchair is made to gather crucial information given by other units and send out emergency calls or notifications to the caregivers. Face recognition technology uses image processing to identify facial expressions by detecting the patient’s face and facial expressions. This helps the other components collect and send data via Internet of Things technologies. Speech – to –Text and Text – to-Speech Methodology is used in the voice recognition module and it captures the voice command data set and extracts the features of the commands.The model is already built and trained to recognize the commands and to send action request to the relevant unit.The Responsive AI auto starts the timer when the patient moves away from the wheelchair, recognizes time and responses back. This unit auto also sends the alert and calls to the guardian when the user has no response.
URI: https://rda.sliit.lk/handle/123456789/3252
ISSN: 2831-3399
Appears in Collections:Department of Information Technology

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