Please use this identifier to cite or link to this item: http://148.72.244.84:8080/xmlui/handle/xmlui/13646
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dc.contributor.authorMohannad Abid Shehab Ahmed-
dc.date.accessioned2024-04-01T15:25:08Z-
dc.date.available2024-04-01T15:25:08Z-
dc.date.issued2014-12-01-
dc.identifier.citationhttps://djes.info/index.php/djes/article/view/434en_US
dc.identifier.issn1999-8716-
dc.identifier.urihttp://148.72.244.84:8080/xmlui/handle/xmlui/13646-
dc.description.abstractNowadays, voice is one of the methods commonly used to control the electrical and electronic appliances because of easily being reproduced by human. Many people with disabilities do not have the dexterity necessary to control a joystick on an electrical wheelchair, so the aim of this study is to control access to voice services and to implement a wheelchair using small vocabulary word recognition system. The HM2007 IC serves as the ear that will listen and interpret the voice command, while the PIC18F458 serve as the brain of the system that will process and coordinate the correct output of the input command to control the wheelchair motors. The methodology adopted is speech recognition development for isolated word from independent speakers where any speaker has two different sentences first for training and the second for testing to release the operation. The input of the system is a set of pick up five words used to control the movements of two motors connected to PIC 18F458 which is used as a programmable and controllable device, the speed of the motors is adjusted using the PWM (Pulse Width Modulation) technique where the duty cycle is simultaneously varied according to input switching device. For more efficient design, the system can worked in worst condition that could be achieved in noisy environment with different signal to noise ratios, besides that the electric power supply can utilize the solar cells. Finally, the proposed system is implemented and tested upon a data base consists of ten speakers (6 males and 4 females) and its performance rises the algorithm efficiency and reduce the execution time with 97% noiseless overall accuracyen_US
dc.language.isoenen_US
dc.publisherUniversity of Diyala – College of Engineeringen_US
dc.subjectHM2007, Solar Cells, Darlington Pair, PIC 18F458, Wheelchair, Speech Recognition, Micro C Programming.en_US
dc.titleDesign, Modeling, And Implementation of PIC Based Electrical Wheelchairen_US
dc.typeArticleen_US
Appears in Collections:مجلة ديالى للعلوم الهندسية / Diyala Journal of Engineering Sciences (DJES)

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