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dc.contributor.advisorDaba, Jihad S.en_US
dc.contributor.authorFadous, Cybeleen_US
dc.contributor.authorMakdessi, Fadien_US
dc.descriptionIncludes bibliographical references (p. 34-35).en_US
dc.descriptionSupervised by Dr. Jihad Daba.en_US
dc.description.abstractWith the growing number of vehicles; the traffic and congestion levels has been increasing significantly causing more time lost and an increased pollution. Many approaches were taken trying to reduce this jamming issue such as the promotion and organization of public transport, restricting laws, and the expansion of the infrastructure. This project returns to the base level of vehicular traffic network by transforming the traditional traffic light system into a smart adaptive traffic light. This system bases its distribution of green light time on calculated values brought by sensors spread across the roads, where all elements are interconnected through the emerging technology of the Internet of Things.en_US
dc.description.statementofresponsibilityby Cybele Fadous, Fadi Makdessien_US
dc.format.extentvii, 53 p. :ill., tables ;30 cmen_US
dc.rightsThis object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holderen_US
dc.subject.lcshAutomatic controlen_US
dc.titleInternet of things based : adaptive traffic light system based on real-time sensing and estimated traffic flowen_US
dc.contributor.departmentDepartment of Electrical Engineeringen_US
dc.contributor.facultyFaculty of Engineeringen_US
dc.contributor.institutionUniversity of Balamanden_US
dc.description.degreeMS in Electrical Engineeringen_US
Appears in Collections:UOB Theses and Projects
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