The document describes a student project to develop an IoT-based traffic signal monitoring and control system. A team of 5 students - A.Deepthi Reddy, A.Guru Sravya, B.Sreya, G.K.Vaishnavi, and K.Shirisha from Vardhaman College of Engineering are working on the project. The system will use sensors to monitor traffic densities at signals and transmit the data online to controllers. It will provide a GUI for controllers to remotely monitor traffic and override signals if needed. The goal is to automate traffic signaling while allowing for manual overrides over the internet.

1. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Engineering Design Thinking (A7023)
Course End Project (CEP)
Traffic signal monitoring
Roll No. Name of the Student
21881A0566 A.DEEPTHI REDDY
21881A0568 A.GURU SRAVYA
21881A0574 B.SREYA
21881A0585 G.K.VAISHNAVI
21881A0592 K.SHIRISHA
Team - 04

2. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Outline of the Presentation
 Introduction
 Literature Review
 Existing Methods/Systems
 Objectives of the Project
 Block Diagram / Circuit Diagram
 Project Description
 Software & Hardware Components
 Features, Advantages & Applications
 Conclusions and Future Extensions
 References

3. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Introduction
 Here we propose an IOT based automated traffic signal monitoring as well as controller
system that automates complete traffic signaling system automation and also allows for
manual override over internet.
 The system uses Arduino based circuit system to monitor traffic signal densities and
transmits this data online over internet to the controllers. We use IOT Gecko in order to
develop the online GUI based system to monitor the traffic densities.
 The system shows current densities to help monitor traffic conditions on roads. Also the
system provides an option to the controllers to override any signal and make it green in
case of any ambulance or important vehicles to pass through while keeping other signals
red.
 This puts forth a traffic signal monitoring and controller system that can be operated
remotely over the internet from anywhere with manual override ability.

4. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Literature Review
 TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis
447: Active Traffic Management for Arterials explores practices associated with
the design, implementation, and operation of active traffic management (ATM)
on arterial roadways .
 ATM includes a suite of strategies that are used to National Academies of
Sciences, Engineering, and Medicine. 2013. Active Traffic Management for
Arterials. Washington, DC: The National Academies Press.

5. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Existing Methods/Systems
 Traffic signal control (TSC) use GPS to track the traffic at intersections and it
will also synchronise the traffic lights.
 Predictive traffic light control system –
 Is a proposed systems for predicting the next intersection timing and generating
the required speed at current intersection to cross next intersection without
stopping at it.
 The system is speed module for next intersection prediction embedded in
intelligent traffic light control system at intersection. It can also be designed for
GPS based navigation system.

6. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Objectives of the Project
 The main objective of the project is to use time efficiently as
the people are getting busy day-to-day .
Because people need to travel more now-a-days as they have to
expand their business all over the world .
So to decrease traffic congestion we are going to implement
this traffic monitoring system .
Traffic management is aimed at attaining maximum efficiency
from the existing road network while minimising adverse
impacts of traffic.

7. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Block Diagram / Circuit Diagram

8. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Project Description
 Congestion in traffic is a serious issue. In existing system signal timings are fixed
and they are independent of traffic density.
 Large red light delays leads to traffic congestion . In this paper, IoT based traffic
control system is implemented in which signal timings are updated based on the
vehicle counting .
 This system consists of WI-FI transceiver module it transmits the vehicle count of
the current system to the next traffic signal . Based on traffic density of previous
signal it controls the signals of the next signal.
 The system is based on raspberry-pi and Arduino. Image processing of traffic video
is done in MATLAB with sim u link support. The whole vehicle counting is
performed by raspberry pi.

9. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Software Components & Implementation
Software Components:
1) Arduino compiler
2) MC Programming Language :c
Software Implementation:
• The software implementation provides the creation of API.
• User needs to sign-in into the application by providing the specified details.
• For accessing, user must login into the application by providing the
credential.
• When the user feeds the source and destination details and clicks “NEXT”
the application displays the level of pollutants he is exposed to.

10. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Hardware Components & Implementation
Hardware components:
• Rectifier
• Regulator
• Power Supply
• LCD Display
• Wifi Module
• Led’s
• At mega 328 Microcontroller
• IR Sensors
• Resistors
• Capacitors
• Diodes
Hardware Implementation:
 STEP 1: Install Raspbian OS in Windows operating system.
 STEP 2: Open IDLE and create a new sketch by clicking programming.
Programming > Python 3(IDLE).
 STEP 3: Write a program. File > New File.

11. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Features, Advantages and Applications
 When properly timed, traffic signals increase the traffic handling
capacity of an intersection, and when installed under conditions
that justify its use, it is a valuable device for improving the safety
and efficiency of both pedestrian and vehicular traffic .
Traffic control system provide for an orderly movement of traffic.
 They help in reducing the frequency of an accident of some
special nature i.e. of right angles accidents.
They intercept heavy traffic to allow other traffic to cross the
road intersection safety.

12. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
Conclusions and Future Extensions
 This project still has space for improvement and can be extended by displaying
traffic data in an application that can be accessed by the public. In addition the
system can be made more efficient by using a camera with higher resolution or by
replacing the HC-SR04 ultrasonic sensors with industrial grade sensors that
serve the same purpose.
 Further changes can also be made to the system that permits emergency
vehicles to be given the highest priority in any situation .
 This system configuration reduces huge traffic queues caused by the conventionally
implemented system used in many places. The system also additionally reduces
the workload of officers who would have to direct traffic in unexpected situations,
using the traffic lights time management technique.
 It also enables traffic lights to work continuously with less chances of malfunctioning.
The system in simple words provides a simple yet effective solution to improper
traffic management systems.

13. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
References
 J. J. Caubel, T.E. Cados, T.W. Krichstetter, (2018) ‘A New Black Crabon
Sensor for Dense Air Quality Monitoring Networks’, IEEE.
 Harsh Gupta, Dhananjay Bhardwaj, Himanshu Agrawal, Vinay Anand
Tikkiwal, Arun Kumar, (2019) ‘An IoT Based Air Pollution Monitoring System
for Smart Cities’, ICSETS.
 G. Lo Re, D. Peri, S. D. Vassallo, (2013) ‘A mobile application for
assessment of air pollution exposure’, IEEE.
L

14. VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
THANK YOU