Tracking system using neural network
Wheelchair users might face difficulty to carry their luggage when traveling. A proposed solution is introduced based on the problem stated. A visual-based sensor cart follower is proposed to ease the mobility of a wheelchair in carrying their luggage. The cart will track and follow the wheelchair i...
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| Format: | Monograph |
| Language: | en |
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Universiti Sains Malaysia
2019
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| Online Access: | http://eprints.usm.my/55343/1/Tracking%20system%20using%20neural%20network.pdf http://eprints.usm.my/55343/ |
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| _version_ | 1834505981852123136 |
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| author | Chong, Chee Moi |
| author_facet | Chong, Chee Moi |
| author_sort | Chong, Chee Moi |
| building | Hamzah Sendut Library |
| collection | Institutional Repository |
| content_provider | Universiti Sains Malaysia |
| content_source | USM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Wheelchair users might face difficulty to carry their luggage when traveling. A proposed solution is introduced based on the problem stated. A visual-based sensor cart follower is proposed to ease the mobility of a wheelchair in carrying their luggage. The cart will track and follow the wheelchair in a suitable distance. A Camera acts as input to let cart able to track and follow the wheelchair, Vision sensor (Pixy CMUcam5) is used to detect the predefined colour pattern in this project. The visually based sensor gathered the information of the colour pattern board which situated behind the wheelchair and translate the gathered information into relative position information, such as distance and skew angle which helps the cart in following the wheelchair. This translation can be done in the neural network. The Mean Squared Error (MSE) value obtained is 0.14007. The neural network can be implemented in the Field Gate Programmable Array (FPGA). The implementation of the neural network on the FPGA can be done through software and hardware configuration. The error value in predict the distance is less than 0.8000 while the error value in predict the skew angle is less than 0.3000. |
| format | Monograph |
| id | my.usm.eprints.55343 |
| institution | Universiti Sains Malaysia |
| language | en |
| publishDate | 2019 |
| publisher | Universiti Sains Malaysia |
| record_format | eprints |
| spelling | my.usm.eprints.55343 http://eprints.usm.my/55343/ Tracking system using neural network Chong, Chee Moi T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering Wheelchair users might face difficulty to carry their luggage when traveling. A proposed solution is introduced based on the problem stated. A visual-based sensor cart follower is proposed to ease the mobility of a wheelchair in carrying their luggage. The cart will track and follow the wheelchair in a suitable distance. A Camera acts as input to let cart able to track and follow the wheelchair, Vision sensor (Pixy CMUcam5) is used to detect the predefined colour pattern in this project. The visually based sensor gathered the information of the colour pattern board which situated behind the wheelchair and translate the gathered information into relative position information, such as distance and skew angle which helps the cart in following the wheelchair. This translation can be done in the neural network. The Mean Squared Error (MSE) value obtained is 0.14007. The neural network can be implemented in the Field Gate Programmable Array (FPGA). The implementation of the neural network on the FPGA can be done through software and hardware configuration. The error value in predict the distance is less than 0.8000 while the error value in predict the skew angle is less than 0.3000. Universiti Sains Malaysia 2019-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/55343/1/Tracking%20system%20using%20neural%20network.pdf Chong, Chee Moi (2019) Tracking system using neural network. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik & Elektronik. (Submitted) |
| spellingShingle | T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering Chong, Chee Moi Tracking system using neural network |
| title | Tracking system using neural network |
| title_full | Tracking system using neural network |
| title_fullStr | Tracking system using neural network |
| title_full_unstemmed | Tracking system using neural network |
| title_short | Tracking system using neural network |
| title_sort | tracking system using neural network |
| topic | T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/55343/1/Tracking%20system%20using%20neural%20network.pdf http://eprints.usm.my/55343/ |
| url_provider | http://eprints.usm.my/ |