| dc.contributor.author | Ainebyona, Donald | |
| dc.contributor.author | Kahigiriza, Peter Warren | |
| dc.contributor.author | Kyobweine, Prisca Bikangaga | |
| dc.date.accessioned | 2020-01-03T14:45:01Z | |
| dc.date.available | 2020-01-03T14:45:01Z | |
| dc.date.issued | 2019-07 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12281/8064 | |
| dc.description | A project report submitted in Partial fulfillment of the Requirements for the award of a degree of Bachelor of Science in Computer Science of Makerere University | en_US |
| dc.description.abstract | Drowsiness is one of the major causes of accidents. The most important aspect to consider when one is driving is the driver's condition, which involves staying focused on the road. A large number of research studies have been conducted to reduce the risk of accidents while driving, primarily focusing on the physical conditions of the driver e.g. movement of the head. On this basis, this research is focused on the driver's heart rate by using pulse sensors. This is measured with the variation of the heart rate (HRV - Heart Rate Variability) in order to analyze and detect drowsiness in drivers. Our main goal is to avoid accidents derived from fatigue byusing an alarm system to keep drivers focused on the road. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Makerere University | en_US |
| dc.subject | Drowsiness | en_US |
| dc.subject | Drowsiness detection system. | en_US |
| dc.subject | Wake me App | en_US |
| dc.title | Wake Me App | en_US |
| dc.type | Thesis | en_US |
