Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/3423
Title: Internet of things based : adaptive traffic light system based on real-time sensing and estimated traffic flow
Authors: Fadous, Cybele
Makdessi, Fadi
Advisors: Daba, Jihad S. 
Subjects: Automatic control
Issue Date: 2017
Abstract: 
With 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.
Description: 
Includes bibliographical references (p. 34-35).

Supervised by Dr. Jihad Daba.
URI: https://scholarhub.balamand.edu.lb/handle/uob/3423
Rights: This 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 holder
Ezproxy URL: Link to full text
Type: Project
Appears in Collections:UOB Theses and Projects

Show full item record

Record view(s)

67
checked on Dec 22, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.