Paper ID Title 27 loT Real-Time Car Traffic Flow Counter for Smart Traffic Light System Raspberry Pi, Logistic regression, TensorFlow, Firebase, IOT. Kaiser Roy S. Narandan, Roel B. Lauron, Chris Jordan G. Aliac Cebu Institute of Technology University kasierroy@gmail.com, roel.lauron@gmail.com, chris.aliac@edu Abstract This paper presents a simple solution to aid in the analysis of real time traffic congestion in Keywords Author/s Affiliation Email

Fundamentals of Information Systems
9th Edition
ISBN:9781337097536
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter7: Knowledge Management And Specialized Information Systems
Section: Chapter Questions
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 Describe and indicate how will you intend to utilize the proposed project in your community

Paper ID
Title
Keywords
Author/s
Affiliation
Email
27
IoT Real-Time Car Traffic Flow Counter for Smart Traffic Light System
Raspberry Pi, Logistic regression, TensorFlow, Firebase, IOT.
Kaiser Roy S. Narandan, Roel B. Lauron, Chris Jordan G. Aliac
Cebu Institute of Technology University
kasierroy@gmail.com, roel.lauron@gmail.com, chris.aliac@edu
Abstract
This paper presents a simple solution to aid in the analysis of real time traffic congestion in
different road conditions. The system uses an ARM based raspberry Pi unit, connected with a
camera system and fully connected 4G or WIFI internet data. The system is easily mounted
places with full view of traffic. Once properly placed and operational, the system then uses
OpenCV and TensorFlow Algorithms to automatically count the number of vehicles on the road
according to vehicle type, and relative speed. All these data are then sent to a cloud repository
system via the Google Firebase. The system shows front end data via a website that discloses
said information for further analysis or may even be a potential plug-in to automated traffic light
system.
Transcribed Image Text:Paper ID Title Keywords Author/s Affiliation Email 27 IoT Real-Time Car Traffic Flow Counter for Smart Traffic Light System Raspberry Pi, Logistic regression, TensorFlow, Firebase, IOT. Kaiser Roy S. Narandan, Roel B. Lauron, Chris Jordan G. Aliac Cebu Institute of Technology University kasierroy@gmail.com, roel.lauron@gmail.com, chris.aliac@edu Abstract This paper presents a simple solution to aid in the analysis of real time traffic congestion in different road conditions. The system uses an ARM based raspberry Pi unit, connected with a camera system and fully connected 4G or WIFI internet data. The system is easily mounted places with full view of traffic. Once properly placed and operational, the system then uses OpenCV and TensorFlow Algorithms to automatically count the number of vehicles on the road according to vehicle type, and relative speed. All these data are then sent to a cloud repository system via the Google Firebase. The system shows front end data via a website that discloses said information for further analysis or may even be a potential plug-in to automated traffic light system.
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