dc.contributor.advisor |
Tahboub, Radwan |
|
dc.contributor.author |
Dabbas, Ansar |
|
dc.contributor.author |
Froukh, Sahar |
|
dc.date.accessioned |
2019-02-05T07:04:33Z |
|
dc.date.accessioned |
2022-05-22T06:25:14Z |
|
dc.date.available |
2019-02-05T07:04:33Z |
|
dc.date.available |
2022-05-22T06:25:14Z |
|
dc.date.issued |
2015-05-01 |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/123456789/6684 |
|
dc.description |
CD , no of pages 42, هندسة حاسوب 2/2015 |
|
dc.description.abstract |
Road traffic congestion continues to remain a serious problem in most cities
around the world, especially in the developing countries. It usually occurs in
small critical areas that represent city centers and roads intersections. This
problem is a result of inappropriate planning for road networks, increasing
number of vehicles and poor traffic management. The congestion leads to
unnecessary delay, noise, fuel wastage and loss of money. In addition accidents
rate may increase. the aim of this project is to build an embedded
system based on image processing and machine learning techniques to develop
an algorithm that can detect the road traffic congestion levels in Ain
Sarah Street. This algorithm will receive live images from a camera placed
on the street and analyse it using a microcontroller. Congestion level and
guide sign will be displayed on an optimal traffic light sign. The system is
feasible since building the model is inexpensive and it can be easily installed. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
جامعة بوليتكنك فلسطين - هندسة حاسوب |
en_US |
dc.subject |
Intelligent Traffic |
en_US |
dc.subject |
Light Guidance System |
en_US |
dc.title |
Intelligent Traffic Light Guidance System (ITLGS) |
en_US |
dc.type |
Other |
en_US |