| dc.contributor.advisor | Qudimat, Ahmad | |
| dc.contributor.author | Hassouneh, Rana | |
| dc.contributor.author | Naser AL-Deen, Ghadeer | |
| dc.contributor.author | Alazah, Sami | |
| dc.date.accessioned | 2019-02-18T09:03:37Z | |
| dc.date.accessioned | 2022-05-22T06:26:38Z | |
| dc.date.available | 2019-02-18T09:03:37Z | |
| dc.date.available | 2022-05-22T06:26:38Z | |
| dc.date.issued | 2018-08-01 | |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/6768 | |
| dc.description | no of pages 47, Cd , اتصالات 1/2018 , in the store | |
| dc.description.abstract | Drowsiness is one of the major risk factors causing accidents that result in a large number of damage. Drivers and industrial workers ,who do not take regular breaks when driving or work for long time probably have a large effect on several mishaps occurring from drowsiness. Therefore, advanced technology to reduce these accidental rates is a very challenging problem. The purpose of this project is to develop a portable wireless device that can automatically detect the drowsiness in real time by using the electrooculogram (EOG). These include the mechanism that take the dynamic signal of the eye and turn it into an electrical signal through electrodes placed around the eye to monitor the eye movement. The signal was sent via the wireless communication of zigbee to a standalone microcontroller to analyze drowsiness using Convolutional Neural Networks .The alarm will ring when the drowsiness occurs. Such application is helpful to reduce losses of casualty and property. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | جامعة بوليتكنك فلسطين - اتصالات | en_US |
| dc.subject | Wireless Based Portable EOG | en_US |
| dc.subject | Real Time Drowsiness Detection | en_US |
| dc.title | Wireless Based Portable EOG Monitoring For Real Time Drowsiness Detection | en_US |
| dc.type | Other | en_US |