Intelligent wheelchair with emotion analysis and voice recognition

dc.contributor.authorPerera, S
dc.contributor.authorGamage, S
dc.contributor.authorWeerasinghe, C
dc.contributor.authorJayawardena, C
dc.contributor.authorPathinayake, K
dc.contributor.authorRajapaksha, S
dc.contributor.editorSumathipala, KASN
dc.contributor.editorGanegoda, GU
dc.contributor.editorPiyathilake, ITS
dc.contributor.editorManawadu, IN
dc.date.accessioned2023-09-05T08:17:06Z
dc.date.available2023-09-05T08:17:06Z
dc.date.issued2022-12
dc.description.abstractIntelligent 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.en_US
dc.identifier.citation*****en_US
dc.identifier.conference7th International Conference in Information Technology Research 2022en_US
dc.identifier.departmentInformation Technology Research Unit, Faculty of Information Technology, University of Moratuwa.en_US
dc.identifier.emailit19045504@my.sliit.lken_US
dc.identifier.emailit19120430@my.sliit.lken_US
dc.identifier.emailit19000572@my.sliit.lken_US
dc.identifier.emailchandimal.j@sliit.lken_US
dc.identifier.emailit19127460@my.sliit.lken_US
dc.identifier.emailsamantha.r@sliit.lken_US
dc.identifier.facultyITen_US
dc.identifier.pgnosp. 41en_US
dc.identifier.placeMoratuwa, Sri Lankaen_US
dc.identifier.proceedingProceedings of the 7th International Conference in Information Technology Research 2022en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/21378
dc.identifier.year2022en_US
dc.language.isoenen_US
dc.publisherInformation Technology Research Unit, Faculty of Information Technology, University of Moratuwa.en_US
dc.relation.urihttps://icitr.uom.lk/past-abstractsen_US
dc.subjectIntelligent wheelchairen_US
dc.subjectFace recognitionen_US
dc.subjectEmotion analysisen_US
dc.subjectVoice recognitionen_US
dc.subjectresponsive AIen_US
dc.subjectEmergency alertsen_US
dc.titleIntelligent wheelchair with emotion analysis and voice recognitionen_US
dc.typeConference-Abstracten_US

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