Smart vehicle detection traffic management system enhanced with IoT and machine learning
| dc.contributor.author | Klutse, Edinam Kofi | |
| dc.date.accessioned | 2023-05-09T14:04:53Z | |
| dc.date.available | 2023-05-09T14:04:53Z | |
| dc.date.issued | 2021-05 | |
| dc.description | Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, May 2021 | |
| dc.description.abstract | Traffic congestion is amjor thief of time of the citizens of Ghana especially in urban areas like Accra. Due to the high demand of transportation services in urban areas, which is continually increasing day in day out, the problem has become prevalent in the Ghanaian society. The problem of traffic congestion affects the productivity of the working population negatively because of the time lost in traffic jams. Automated traffic lights and traffic instructors are doing their best to try and combat the traffic congestion however these measure are not dynamic enough to solve the problem. Consequently, this problem serves as a motivation to find a better way to handle traffic congestion in urban areas; hence, this paper delves into the use of the internet of things approach coupled with computer vision and machine learning techniques to develop a smart traffic management system based on a vehicle detection algorithm. | |
| dc.description.sponsorship | Ashesi University | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11988/861 | |
| dc.language.iso | en | |
| dc.title | Smart vehicle detection traffic management system enhanced with IoT and machine learning | |
| dc.type | Other |
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