Smart Traffic Light System

Smart Traffic Light System 2015

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Al Balqa’ Applied University

Faculty of Engineering Technology

Graduation Project

Smart Traffic light System Presented to the Department of Mechatronics Engineering

In Partial Fulfillment Of the Requirements

For the Degree of

Bachelor of Science in Engineering Technology

Mohammad El-Badawi Mohammad Awawdeh Abdullah Ashour Abdullah Abd Alkareem Ahmad Al-Badawi Supervisor: Dr. Lina Momani

January, 2015


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Dedication

This project is sincerely dedicated to:

Our prophet

MOHAMMED [PBUH]

Mercy of all humankind

Our parents:

Who have supported and encouraged us through the past years.

Our instructors:

Who have accompanied us through the undergraduate period.

Our beloved homeland.


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Acknowledgment

After Thanks Our God We would like to express our deep appreciation to

Dr.Lina Momani for all her suspension encouragement with support and guidance

in supervising throughout the course of this project.

Finally, we must thank all our closest friends and family members who support us

throughout the way and gave us all the chances to get where we are right now.

Thank you all...


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ABSTRACT

raffic jams which caused by unutilized time of traffic light to pass as much as

possible number of vehicles on traffic light intersections, and the timing delay

method that applied on the current traffic light system is not feasible to organize the traffic

process for vehicles, also emergency vehicles obstruction, missing guidelines, and

electrical power cut-off that happens to the traffic light intersections are growing problems

that needs to be solved. The aim of this project is developing a traffic light that can solve

these problems, that can be done by making a smart system that counts the cars on each

side of traffic light and estimates time for every traffic light, and measures a real time

frequencies from microphone and compare them to siren frequencies to let emergency

vehicles passes, also the system has a display boards for displaying temperature degree and

guidelines, and a solar tracking energy system that can solve the electrical power cut-of

problems.

T


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TABLE OF CONTENTS

ACKNOWLEDGEMENTS ........................................................................... 3

ABSTRACT ............................................................................................... 4

TABLE OF CONTENTS .............................................................................. 5

1 INTRODUCTION ............................................................................. 7

1.1 LITERATURE SURVAYES ............................................................ 9

1.1.1 CAR DENSITY USING IMAGE PROCESSING ...................................... 9

1.1.2 EMERGENCY SIGNAL DETECTING .................................................... 10

1.1.3 ALTERNATIVE ENERGY ................................................................... 11

2 THEORY ............................................................................................ 12

2.1 CAR DETECTING AND TIME CALCULATION .......................... 12

2.2 EMERGENCY DETECTING AND SIREN FREQUANCIES ........ 14

2.3 SOLAR TRACKING SYSTEM ....................................................... 18

3 PROPOSED SYSTEM ...................................................................... 21

3.1 DESCRIPTION ................................................................................ 21

3.2 OBJECTIVES ................................................................................... 22

3.3 DESIGN ............................................................................................ 22

3.3.1 CAR DETECTION BASED ON IMAGE PROCESSING ............................. 23

3.3.2 EMERGENCY DETECTING AND SIREN FREQUENCIES ......................... 25

3.3.3 SOLAR TRACKING SYSTEM .............................................................. 27

3.3.4 DISPLAY BOARDS ............................................................................ 29

4 SELECTION OF COMPONENTS .................................................. 31

4.1 CAR DETECTING BASED ON IMAGE PROCESSING ............................... 31

4.2 EMERGENCY DETECTING AND SIREN FREQUENCIES .......................... 34

4.3 SOLAR TRACKING SYSTEM ................................................................ 34

4.4 DISPLAY BOARDS .............................................................................. 38

5 SIMULATION ................................................................................... 39

5.1 TRAFFIC LIGHTS SIMULATION ........................................................... 39

5.2 DISPLAY BOARDS SIMULATION ......................................................... 40

5.3 EMERGENCY DETECTING SIMULATION .............................................. 41


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5.4 SOLAR TRACKING SYSTEM SIMULATION ........................................... 42

5.5 SIMULATION OF PROPOSED SYSTEM .................................................. 43

6 IMPLEMENTATION ....................................................................... 44

6.1 HARDWARE ....................................................................................... 44

6.1.1 PROTOTYPE COMPONENTS .............................................................. 46

6.2 SOFTWARE ......................................................................................... 47

6.2.1 CAR DETECTION BASED ON IMAGE PROCESSING ............................ 47

6.2.2 EMERGENCY DETECTING ................................................................ 50

6.3 SOLAR TRACKING SYSTEM ................................................................ 52

6.4 DISPLAY BOARDS .............................................................................. 52

7 TESTING AND PERFORMANCE MEASURE ............................. 53

8 CONCLUSIONS ................................................................................ 56

APPENDICES....................................................................................... 57

APPENDIX 1.......................................................................................... 58

APPENDIX 2.......................................................................................... 60

APPENDIX 3.......................................................................................... 63

APPENDIX 4.......................................................................................... 67

APPENDIX 5.......................................................................................... 68

APPENDIX 6.......................................................................................... 70

REFERENCES ....................................................................................... 72


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CHAPTER 1

INTRODUCTION

owadays traffic system faces different problems; many of these problems

obstruct traffic process, which are usually related to the traffic light, where

the control system of traffic light became necessary need and not just a secondary system,

however the increase of population growth followed by increased number of cars, caused

traffic jam and obstruction of the emergency vehicles. Other problems such as electrical

power cut-off, technical faults and missing way guidelines are existed.

Through observation the traffic in Jordan, it's become clear that most of the

problems that has been mentioned previously exist in traffic lights, where the traffic light

can be considered as gathering point for vehicles, this point need a system to monitor and

control the traffic, in terms of the traffic light sequence, speed control, investigation of car

accidents and link them to the traffic department. It also needs to contain many features

like path guidelines, weather, speed limits, and clock ... etc.

After searching and studying of all possible solutions for these problems in the

traffic system, the result of this search was that there are some countries that have solved

some of them, but not all of these problems in one system. They have developed some

partial systems to solve specific issues. However, the purpose of this project is to develop

a smart universal system, which includes all features and solutions for the problems faced

in current traffic systems. The integration of all these different techniques that accomplish

higher efficiency and more intelligence. This system will perform some missions of

controlling the traffic process automatically.

N


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However, the problems that occur in traffic light and their causes should be

discussed with more details, these problems are:

1- Traffic jam :

Current traffic light don’t care about cars distribution in quad intersection, so it

can do a traffic jam in different sides, and this problem related to non-direct

feedback system.

2- Obstruction of emergency vehicles :

Sometimes emergency vehicles are stuck on one side of the intersection with

red light, that make the drivers take an action and pass the red light to let the

emergency vehicles pass on, that’s why a confusion happens at the intersection,

which leads to delay the emergency vehicle.

3- Electrical power cut-off :

The traffic light system in Jordan suffers from frequent power outages where

there is no alternative power source to compensate the main source of street energy,

and that leads to state of confusion in traffic, which calls for The presence of a

policeman to regulate the functioning of the movement, but this solution consumes

time, effort and cost.

4- Guidelines:

The driver in Jordan faces in most intersections a problem in determining the

direction to his/her destination that he/she wants to go, that’s because of the lack of

signboards, which may sometimes cause accidents.


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1.1 LITERATURE SURVAYES

There are many Literature surveys that addressed Smart traffic light systems, a

summary of these surveys discussed below:

1.1.1 Car Density Using Image Processing:

Chandrasekhar, et al, addressed: “a system that implement image processing

algorithm in real time traffic light control which will control the traffic light efficiently.

A web camera is placed in each stage of traffic light that will capture the still images

of the road where we want to control the traffic. Then those captured images are

successively matched using image matching with a reference image which is an empty

road image. The traffic is governed according to percentage of matching” [1].

Nagaraj, et al, addressed: “Existing commercial image processing systems work

well in free-flowing traffic, but the systems have difficulties with traffic congestion,

shadows and various lighting conditions. The suggested feature-based tracking system

will detect vehicles under these challenging conditions. Using image processing

operations to calculate traffic density is cost effective as cameras are cheaper and

affordable devices compared to any other devices such as sensors” [2].

Dangi, et al, addressed: “The image sequences from a camera are analyzed using

various edge detection and object counting methods to obtain the most efficient

technique”. Subsequently, the number of vehicles at the intersection is evaluated and

traffic is efficiently managed. The paper also proposes to implement a real-time

emergency vehicle detection system. In case an emergency vehicle is detected, the lane is

given priority over all the others” [3].


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1.1.2 Emergency signal detecting:

Fazend addressed: “A system has been investigated for the detection of incoming

direction of an emergency vehicle. Acoustic detection methods based on a cross

microphone array have been implemented. It is shown that source detection based on time

delay estimation outperforms sound intensity techniques, although both techniques

perform well for the application. The relaying of information to the driver as a warning

signal has been investigated through the use of ambisonic technology and a 4 speaker array

which is ubiquitous in most modern vehicles. Simulations show that accurate warning

information may be relayed to the driver and afford correct action” [4].

Hashem addressed: “This system was designed to be operated when it received

signal from emergency vehicles based on radio frequency (RF) transmission and used the

Programmable Integrated Circuit (PIC) 16F877A microcontroller to change the sequence

back to the normal sequence before the emergency mode was triggered. This system will

reduce accidents which often happen at the traffic light intersections because of other

vehicle had to huddle for given a special route to emergency vehicle. As the result, this

project successful analyzing and implementing the wireless communication; the radio

frequency (RF) transmission in the traffic light control system for emergency vehicles. The

prototype of this project is using the frequency of 434 MHz and function with the sequence

mode of traffic light when emergency vehicles passing by an intersection and changing the

sequence back to the normal sequence before the emergency mode was triggered. In future,

this prototype system can be improved by controlling the real traffic situation, in fact

improving present traffic light system technology” [5].


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1.1.3 Alternative energy:

Hassan and others addressed: “A photovoltaic system is needed in order to use this

energy continuously. The results of the investigation of components, design, and market

availability are shown in the paper. Solar cells, which are used for absorbing sunlight and

generating electric current, are the main source for the system’s operation. A charge

controller is used to control the flow of charge through the battery and to protect the battery

from overcharging and deep discharging. A dc-dc converter is used to regulate the output

voltage which depends on the type of dc to dc converter. Lead acid batteries are used as

the electric energy storage for the PV system to use electrical energy in the absence of

sunlight. The principle operation of the system and the feasibility of using it for rural area

with no power grid have been studied. For this project, a mount tracker was constructed

that enabled the solar panel to be placed at 0, 15, 30, 45, 60, 75 and 90 degree angles in

order to determine which angle and what time provides the optimum voltage. Experimental

results for different angles of radiation at different times of the day and different days of

the year are shown in the paper” [6].


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CHAPTER 2

THEORY

s the problem of urban traffic congestion spreads, there is a pressing need

for the introduction of advanced technology and equipment to improve the

state of traffic control. Traffic problems nowadays are increasing because of the growing

number of vehicles and the limited resources provided by current infrastructures. The

simplest way for controlling a traffic light uses timer for each phase. Another way is to use

electronic sensors in order to detect vehicles, and produce signal that cycles. Project

propose a system for controlling the traffic light by image processing. The system will

detect vehicles through images instead of using electronic sensors embedded in the

pavement.

2.1 CAR DETECTING AND TIME CALCULATION

The system will estimate the number of cars at each side of traffic light based on

image processing, then the system will estimate the turn on time for each traffic light

according to equation (2.1.1).

tY = K × XY……………..(2.1.1)

Where,

ty: turn on time.

XY: number of cars.

K: is the time average constant that every car can take to pass the traffic light. It

can be changed due to type of intersection.

The system also checks if the turn on time smaller than the maximum time and

greater than zero, then system turn on the traffic light for one side with time delay equal

the turn on time (ty). After finish, the system turn off the traffic light and continue the

sequence.

A


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If ty is greater than tmax the system will determine that ty=tmax, where tmax is a specific

value of time that prevent the time delay estimated exceed over an acceptable value.

To give more clearance assume there are four sides and the number of cars in each

side are 4,1,3,0, respectively. The tmax=18 sec. The time constant K=6 sec. Then the turn

on time for each side:

ty1= 6 × 4 = 24 sec. but ty1 is greater than tmax, so ty1 = tmax = 18 sec.

ty2= 6 × 1 = 6 sec.

ty3= 6 × 3 = 18 sec.

ty4= 6 × 0 = 0 sec.

Table (2.1) shows the time diagram of the turn on time for each side.

Table (2.2) shows the time according to cars number.

Table (2.3) shows the traffic light sequence.

Table (2.1): Time diagram.

Table (2.2): Time according to cars number. Table (2.3): Traffic light sequence.

TIME 6 12 18 24 30 36 42

A

B

C

D

Traffic

Light Count Time (sec) Time / Count

A 4 18 6/1

B 1 6 6/1

C 3 18 6/1

D 0 0 6/1

Traffic

Light Turn

A 1

B 2

C 3

D 4


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2.2 EMERGENCY DETECTING AND SIREN FREQUANCIES

The system detect emergency vehicles by measuring frequencies of the sounds that

enter the mic, and compare it to the siren frequencies, if the frequencies are in the range of

the siren sound, the system will interrupted, then all the traffic lights on the intersection

will turns to red, and the traffic light on the side of the emergency vehicle will be turned to

green.

Sirens are devices that produce warning sounds. Siren sounds are intended to help

alert the public that an emergency vehicle (e.g., police car, ambulance, fire truck) is nearby

and responding to an emergency. These sounds should be recognized as the call for the

right-of-way of the vehicle.

Two widely used and recognized sounds are available with electronic siren system.

A wail is designed to mimic the intrinsic sound of a mechanical siren. This sound is

produced by slow increases and decreases in frequency. A yelp cycles through a range of

frequencies in a manner similar to a wail, but at a faster cycle rate. Other sounds, less

commonly used, are available with many siren systems. Most siren systems also have a so-

called manual control on the amplifier, which is a momentary contact switch that permits

intermittent, rather than continuous, operation [7].


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In the United States, the most widely recognized and cited documents that specify

test methods, performance requirements, and installation practices for emergency vehicle

sirens are those listed in Table (2.4) [7].

Table (2.4): Documents that specify test methods, performance requirements.

As the siren sound consists of wail, yelp, and Hi-Low frequencies, the Wail and

yelp sounds are produced by increases and decreases in the frequency of a square wave.

Any particular wail or yelp sound is characterized by its cycle rate and fundamental

frequency range. For a square wave, harmonics are present at frequencies higher than the

frequency of the square wave itself, which is the fundamental frequency of the square wave.

Examples of how the square wave frequency varies with time for wail and yelp are shown

in Figure (2.1) [7].

Description Abbreviated description used in this

guide

Section 3.14.6 of the Federal specification

KKK–A–1822 for ambulances, produced

by the U.S. General Services

Administration (GSA).

GSA K-Specification

Title 13, Article 8 of the California Code

of Regulations (CCR), produced by the

California Highway Patrol.

CCR Title 13

Emergency Vehicle Sirens -SAE J1849

August 1995 Recommended Practice,

produced by the Society of Automotive

Engineers (SAE).

SAE J1849


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Figure (2.1): Examples of wail and yelp with cycle rates of 20 cycles per minute (cpm) and 240

cpm, respectively.

Tables (2.5) and (2.6) summarize the frequency and cycle rate requirements of the

GSA K-Specification, CCR Title 13, and SAE J1849 for the wail and yelp sounds, [7].

See the Appendix (1).


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There are some considerations that must be taken for sound frequencies

measurements, as follows:

Echoes

Echoes are just time-shifted, attenuated versions of the original signal the frequency

content of the echo does not change, thus any echoes will actually help in the detection of

a siren.

Doppler Effect

Where

Vr is the velocity of the receiver relative to the medium; positive if the receiver is

moving towards the source (and negative in the other direction), in the project the receiver

is constant, so = 0.

VS is the velocity of the source relative to the medium; positive if the source is

moving away from the receiver (and negative in the other direction).

V is the velocity of waves in the medium (sound travels at 345 m/s in air) The car

ambulance moving at 90 Km/Hour = 25 m/s, relative to speed of sound in air, there will

not be a huge shift in frequency.


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2.3 SOLAR TRACKING SYSTEM

Solar Tracking System is a device for orienting a solar panel or concentrating a

solar reflector or lens towards the sun. Concentrators, especially in solar cell applications,

require a high degree of accuracy to ensure that the concentrated sunlight is directed

precisely to the powered device. There are two types of tracking system can be driven by

linear actuators.

Types of solar tracking system:

Single Axis Tracking System.

Dual Axis Tracking System.

A single axis system, Figure (2.2), is most commonly used for most standard PV cell

arrays. The cells are mounted on a moving axis which is oriented to rotate along the earth’s

axis. These types of trackers usually have simple levers which can be used to tilt the cells

depending on the season to still maximum the exposure to the sunlight.

This is the type of tracking system most commonly used for residential solar arrays, as

well as many smaller commercial arrays. While single axis trackers don’t allow for as much

exposure to the sun’s rays as dual axis systems, their main advantage lies in the price.

Single axis systems cost only a small fraction of what their dual axis counterparts do, which

makes them ideal for all but the biggest solar arrays.

Figure (2.2): Single Axis Tracking System.


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Dual axis systems, Figure (2.3), are typically used in concentrated solar power

systems, where it becomes necessary to completely orient the mirrors or reflectors so that

the sun’s rays are redirected onto their intended focal point. This type of solar tracker is

usually referred to as a heliostat, and consists of mirrors which rotate and tilt to focus their

energy on a fixed collector.

Figure (2.3): Tracking Dual axis systems.

Dual axis systems - as their name suggests - are capable of moving in two

directions, on both the horizontal and the vertical axis so they can make complete use of

the sun’s rays for the entire day. Another type of dual axis system is the moving collector,

which is the exact same concept as the single axis tracker, except these systems are still

capable of moving on the horizontal and vertical axes, thus increasing the amount of time

they are directly exposed to the sunlight.

The major advantage of dual tracking systems is that they allow the solar cells to

be placed much closer together, thus reducing the total amount of space necessary for a

large solar array.


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This means that much more power can be produced in a small area, and because of

the dual axis system, this power can also be produced in a much more efficient manner as

well. Almost all large scale commercial solar applications utilize dual axis systems for their

reliability and efficiency, and they allow for much less need for conventional types of

power which often burn fossil fuels and release pollution into the atmosphere

How the solar sensor works

The system contains 4 LDRs sensors with sheets between them, Figure (2.4), the

withe stips are the LDRs.

When the stick on top is righted to the sun or the brightest point the four LDRs get

the same amount of light on them. When right-top, right-down, and left-down LDRs are

in the shadow, and the left-top get the most light, then the controller send commands to

motors to make the same amount of light in each (LDRs). And the same thing on other

sensor.

Figure (2.4): sensor of 4 LDRs with sheets between them


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CHAPTER 3

PROPOSED SYSTEM

3.1 DESCRIPTION

urrent traffic lights do not have feedback, they only change signal based on

time principle, and such a system causes many problems that was previously

mentioned. In this project the feedback signal is entered to traffic light system by adding

camera on the intersection, and use this camera to count the number of vehicles for each

path by using image processing technique.

This technique analyze the images from camera at the same time, and import to the

controller the number of vehicles for each direction, then the controller estimates a period

of time needed by each path to open each traffic light based on the number of vehicles in a

fixed sequence, it is also used to monitor the traffic.

The system consists additional features such as opening one traffic light and closing

the others when it detects emergency vehicle siren, and the second feature is adding

alternative power source that depends on the solar energy, and it is used when the electrical

power source is cut-off.

Also, accessories are added to the system such as clock and temperature sensor that

allows the drivers to know the time and air temperature, and direction guidelines to guide

the drivers to the destination that they want.

C


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3.2 OBJECTIVES

After studying the principle of work of the traffic light and identify the problems

that related to it, it had to determine the desired objectives of this project to find appropriate

solutions to solve these problems, the most important objectives to be achieved are:

1. Reduce the traffic jam.

2. To give more flexibility to the traffic light system.

3. Use solar energy as a source of power under power cut-off cases.

4. Identify directions of local places using digital guidelines.

5. Develop control system can handle with emergency cases.

3.3 DESIGN

The system relies on the principle of priority of traffic, the priority always for

emergency vehicles, the system checks the signal coming from the Emergency vehicle, if

there is a logic signal (1) the system turn off all the traffic lights and determine the direction

of the emergency vehicle and then turn on the traffic light that the emergency vehicle is

coming from, and wait until the emergency vehicle passed the traffic light, and then return

to check the signal coming from the emergency vehicle. If there is a logic signal (0) the

system will determine the next traffic light turn depending on the traffic lights sequence.


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3.3.1 Car detection based on Image Processing

Image processing is a form of signal processing for which the input is an image,

such as a photograph or video frame; the output of image processing may be either an

image or a set of characteristics or parameters related to the image. Most image-processing

techniques involve treating the image as a two-dimensional signal and applying standard

signal-processing techniques to it.

Car detection process is performed by Image processing on the images which

picked from video frame that came from camera. Computer is used to perform image

processing by Matlab™ software.

3.3.1.1 System Requirements

System Require these hardware to be implemented, a Personal Computer (Main

Controller), Webcam Camera, Arduino (Mega), Electric wires, and power supply.

3.3.1.2 Bock Diagram

Figure (3.1) show the hardware of the process.

Figure (3.1): Car Detection Block Diagram.

Camera Computer Arduino Traffic

Lights

http://en.wikipedia.org/wiki/Signal_processing

http://en.wikipedia.org/wiki/Photograph

http://en.wikipedia.org/wiki/Video_frame

http://en.wikipedia.org/wiki/Parameter

http://en.wikipedia.org/wiki/Two-dimensional

http://en.wikipedia.org/wiki/Signal_(electrical_engineering)


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Check turn [Y]

Check number

of cars at X[Y]

Estimate turn

on time tY

If

0<tY<tmax

If tY=0

If ti>tY

No Yes

tY = tmax

Turn on traffic

side (Y) for tY

Yes No

Yes No

3.3.1.3 Flow chart

Figure (3.2) show the sequence of operations of the process.

Y: Side turn.

XY: Number of cars at Y side.

ty: Turn on time.

ti: instantaneous time.

tmax: Maximum time.

Figure (3.2): Car detecting flow chart.


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3.3.2 Emergency detecting and siren frequencies

The system consists of a microphone with built in amplifier and filter, Figure (3.3),

and an Arduino. The system will detect the emergency vehicles by its siren frequencies,

where the siren audio will be the input and the mice is the sensor that will receive the siren

sound, and the Arduino is the main controller that will open the way for the emergency

vehicles by measuring the input frequencies and compare them to the standard siren

frequency, where the output is a signal that will interrupt the traffic light sequence and open

the traffic light on the side of the emergency vehicle.

Figure (3.3): Microphone with built in amplifier and filter.


System Require these hardware to be implemented, Arduino UNO, Microphone with

built in amplifier and filter, Electric wires, and Power supply.


Figure (3.4) show the hardware the process.

Figure (3.4): Emergency Detecting Block Diagram.

Microphone

Arduino

Traffic

light

Controller

Traffic

Lights


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3.3.2.3 Flow chart

Figure (3.5) show the emergency signal detecting process.

Measure

frequencies of

audio signals

Calculate

average of

measured

frequencies

If

fmin<frq<fmax

No Yes

Interrupt traffic

light sequence

Turn all traffic

lights to Red

Turn the traffic

light on the

side of the

emergency

vehicle to

green for tmax

Return to main

sequence

Receive audio

signals

Figure (3.5): Emergency signal detecting flow chart.


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3.3.3 Solar tracking system

This model of the system, contains a panel which is sensing the sun light,

until the controller receives analog data from the solar sensor, and convert it to

digital data by internal ADC on it. Then this convert data processing by program

install in control unit, then sending it to interfacing output unit which sending

signals to two servo motor to change the position of the PV panel.


System Require these hardware to be implemented, Arduino UNO, Servo motors,

solar sensor, Electric wires, Power supply, Battery, and Solar cell.



Figure (3.6): Solar tracking Block Diagram.

Solar Sensor

Arduino

Servo

Motors


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Calculate

voltage average

for every side

(VL, VR, VU, VD)

Read solar

sensor voltage

for each side

Yes

No

Estimate difference

between LEFT side

and RIGHT side

MOVE TO

REQUIRED

POSITION

Estimate difference

between UP side

and DOWN side

If VU>VD || VD>VU If VR>VL || VL>VR

Yes

No

3.3.3.3 Flow chart

Figure (3.7) show the Solar tracking process.

Figure (3.7): Solar tracking Flow chart.

VL: Left side average voltage.

VR: Right side average voltage.

VU: Upside average voltage.

VD: Down side average voltage.

Required position: the position where the four solar sensors give same voltage.


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3.3.4 Display boards

Liquid Crystal Display (LCD), Figure (3.8), are added to display the guidelines of

the surrounding area of traffic light, and also display the temperature and the speed limit.

For temperature measuring a temperature transducer (LM35), Figure (3.9), is used to sense

the temperature and convert it to a voltage that represent the actual temperature, based on

Equation (3.3.1). Then the controller (Arduino) display the temperature on the LCD in

Celsius.

Temp = (5 × Vin × 100) / 1024………. (3.3.1)

Where,

Temp: actual temperature.

Vin: analog voltage from LM35 transducer.

Figure (3.8): Blue 16×2 LCD.

Figure (3.9): LM35 Transducer.


System Require these hardware to be implemented, Arduino UNO, LM35

Transducer, Four LCD's, Electric wires, and Power supply.


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Figure (3.10): Display Boards Block Diagram.

3.3.4.3 Flow chart

Figure (3.11) show temperature measuring process.

Convert

temperature to

voltage

Estimate actual

temperature

Display

Temperature,

guidelines, and

speed limit.

Sense

temperature

Figure (3.11): Display Boards flow chart.

LM35

Transducer

Arduino

LCD’s


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CHAPTER 4

SELECTION OF COMPONENTS

4.1 Car Detecting based on Image Processing

This sub system need to be implemented a Personal Computer, Arduino (Mega),

WebCam (Microsoft HD 3000).

4.1.1 Comparison between PC and Raspberry Pi.

Car detection process is performed by Image processing on the images which

picked from video frame that came from camera. At first Open Computer Vision (OpenCV)

Library is used to implement image processing. Raspberry Pi® microprocessor was chosen

to accomplish the process.

The Raspberry Pi is a credit card-sized single-board computer developed in

the UK by the Raspberry Pi Foundation with the intention of promoting the teaching of

basic computer science in schools. Shown in Figure (4.1).

Figure (4.1): Raspberry Pi computer Model B+.

http://en.wikipedia.org/wiki/Credit_card

http://en.wikipedia.org/wiki/Single-board_computer

http://en.wikipedia.org/wiki/United_Kingdom

http://en.wikipedia.org/wiki/Raspberry_Pi_Foundation

http://en.wikipedia.org/wiki/Computer_science


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Raspberry Pi is a good option for several applications of image processing because

it has many features such as Compatible with many camera devices, it Control any

hardware devices using (GIOP), it can Connect to the internet by Wi-Fi or LAN cable, It

can controlled remotely by a PC also it work with Linux operating system.

In other hand it has some disadvantages like the Processor speed is slow comparing

with PC microprocessor, it’s only 800MHz. This slowing in speed is not suitable for this

project because there is a lack in processing and sending the desired data to the

microcontroller.

So that Computer is used to perform image processing by Matlab™ software

because computer speed is high enough to implement image processing.

4.1.2 Comparison between Arduino (Mega) and PIC Microcontroller.

Arduino Mega, Figure (4.2), is an open-source physical computing platform based on

a simple I/O board and a development environment that implements the Processing/Wiring

language.

Figure (4.2): Arduino Mega.


Page | 33

Microchip's 16F877A 8-Bit Processor PIC Microcontroller has 8K of program space

and 33 I/O lines, 8 of which are 10bit Analog to Digital converter capable. Runs up to

20MHz with external crystal.

Arduino mega is chosen because it’s easier in use, more simple in programing, don’t

need a power circuit, it also more reliable.

4.1.3 Comparison between Microsoft HD 3000 Camera and Normal camera

Microsoft HD 3000 camera, Figure (4.3), has many features such as HD-quality

image, 16:9 format offers cinematic video recording, and TrueColor technology

automatically delivers bright and colorful video, in virtually all lighting conditions.

Microsoft HD 3000 camera is chosen because it give a high quality image which is

necessary for image processing, also it has a built in processor which is good for processing

speed, where computer will not waste time for image processing.

Figure (4.3): Microsoft HD 3000 camera.


Page | 34

4.2 Emergency Detecting and Siren Frequencies

This sub system need to be implemented an Electret Microphone Breakout and

Arduino.

4.2.1 Comparison between Electret Microphone Breakout with normal microphone

Microphone Breakout has these features, it couples a small electret microphone with

a 100x op-amp to amplify the sounds of voice, door knocks, etc. Loud enough to be

picked up by a microcontroller’s Analog to Digital converter, it also unit comes fully

assembled. Works from 2.7V up to 5.5V.

Electric microphone breakout is chosen because that normal microphone needs an

amplifier circuit and a filter circuit, where electric microphone breakout comes with

built in amplifier and built in filter.

4.3 Solar Tracking System

This sub system need to be implemented 2 servo's motors (995, metal gear), 4 light

depending resistors (LDR) (sensing element), 4 resistors (10K), Arduino (controller),

and 2 potentiometers (value doesn't matter).

4.3.1 Comparison between Servo Motor and Stepper Motor

A servomotor, Figure (4.4), is a rotary actuator that allows for precise control of angular

position, velocity and acceleration. It consists of a suitable motor coupled to a sensor for

position feedback. It also requires a relatively sophisticated controller, often a dedicated

module designed specifically for use with servomotors.

http://en.wikipedia.org/wiki/Rotary_actuator


Page | 35

Figure (4.4): Servo motor.

Servo Motors are fast, high torque, accurate rotation within a limited angle – Generally

a high performance alternative to stepper motors, but more complicated setup with PWM

tuning. Suited for robotic arms/legs or rudder control etc.

Stepper Motors are Slow, precise rotation, easy set up & control – Advantage over

servo motors in positional control. Where servos require a feedback mechanism and

support circuitry to drive positioning, a stepper motor has positional control via its nature

of rotation by fractional increments. Suited for 3D printers and similar devices where

position is fundamental.

Servo motors has been chosen because it operate at a range of speeds without

overheating, operate at zero speed while retaining enough torque to hold a load in position,

and operate a very low speeds for long periods without overheating.

4.3.2 Light depending resistors (LDR)

A photoresistor or light-dependent resistor (LDR), Figure (4.3.2), or photocell is

a light-controlled variable resistor. The resistance of a photoresistor decreases with

increasing incident light intensity; in other words, it exhibits photoconductivity. A

photoresistor can be applied in light-sensitive detector circuits, and light- and dark-

activated switching circuits.

http://en.wikipedia.org/wiki/Resistor

http://en.wikipedia.org/wiki/Electrical_resistance

http://en.wikipedia.org/wiki/Photoconductivity


Page | 36

Figure (4.5): Light depending resistors (LDR).

A photoresistor is made of a high resistance semiconductor. In the dark, a

photoresistor can have a resistance high, as shown in Figure (4.6), while in the light, a

photoresistor can have low resistance as shown in Figure (4.7). If incident light on a

photoresistor exceeds a certain frequency, photons absorbed by the semiconductor give

bound electrons enough energy to jump into the conduction band. The resulting free

electrons (and their hole partners) conduct electricity, thereby lowering resistance. The

resistance range and sensitivity of a photoresistor can substantially differ among dissimilar

devices. Moreover, unique photoresistors may react substantially differently to photons

within certain wavelength bands.

Figure (4.6): High resistance. Figure (4.7): Low resistance.

http://en.wikipedia.org/wiki/Semiconductor

http://en.wikipedia.org/wiki/Frequency

http://en.wikipedia.org/wiki/Photon

http://en.wikipedia.org/wiki/Electron

http://en.wikipedia.org/wiki/Conduction_band

http://en.wikipedia.org/wiki/Electron_hole

http://en.wikipedia.org/wiki/Electrical_resistance


Page | 37

4.3.3 Potentiometer

This potentiometer, Figure (4.8), is a two-in-one, good in a breadboard or with a

panel,. It’s a fairly standard linear taper 10K ohm potentiometer, with a grippy shaft. It’s

smooth and easy to turn, but not so loose that it will shift on its own. We like this one

because the legs are 0.2" apart with pin-points, so you can plug it into a breadboard or

perfboard. Once you're done prototyping, you can drill a hole into your project box and

mount the potentiometer that way. .

Figure (4.8): Potentiometer.


Page | 38

4.4 Display Boards

This sub system need to be implemented Four LCD’s, LM35 Temperature

Transducer, and Arduino.

4.4.1 LCD’s

LCD (Liquid Crystal Display) screen is an electronic display module and find a wide

range of applications. A 16x2 LCD display is very basic module and is very commonly

used in various devices and circuits. A 16x2 LCD means it can display 16 characters per

line and there are two lines in this LCD. This LCD has two registers, namely, Command

and Data.

4.4.2 Comparison between LM35 Transducer with Thermistor

Thermistor need an electric circuit to work, however LM35 don’t need, it easy to

use, and it can sense a wide range of temperature bigger than thermistors.


Page | 39

CHAPTER 5

SIMULATION

efore buying the project hardware pieces, all systems has been

simulated in PROTEUS™ program. Simulation is good for

testing the project in both side hardware connection and software. It gives an

indication if the system can be applied or not.

5.1 Traffic Lights Simulation

The Figure (5.1) illustrates the schematic diagram of traffic lights

connections with Arduino mega, where it can be simulated by PROTEUS as

it’s a real.

Figure (5.1): Traffic lights simulation.

B


Page | 40

5.2 Display Boards Simulation

The Figure (5.2) illustrates the schematic diagram of Display Boards

and LM35 transducer connections with Arduino UNO. Where it can be

simulated by PROTEUS as it’s a real.

Figure (5.2): LCD's simulation.


Page | 41

5.3 Emergency Detecting Simulation

The Figure (5.3) illustrates the schematic diagram of Microphone and

filter circuit connections with Arduino UNO. Where it can be simulated by

PROTEUS as it’s a real.

Figure (5.3): Emergency Detecting Simulation.

C1(1)

DIGITAL (~PWM)

ANALOG IN

ATMEGA328P-PU1121

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RX

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ARD2

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C1

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R1560

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C20.47uF

A

B

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FILTER CIRCUITMIC

OSCILLOSCOPE

ARDUINO UNO (FREQUENCY MEASSURING CONTROLLER)

ARDUINO MEGA ( MAIN SEQUENCE3 CONTROLLER)


Page | 42

5.4 Solar Tracking System Simulation

The Figure (5.4) illustrates the schematic diagram of LDR’s and servo

motors connections with Arduino UNO. Where it can be simulated by

PROTEUS as it’s a real.

Figure (5.4): Solar Tracing System simulation.


Page | 43

5.5 Simulation of Proposed System

The Figure (5.4) illustrates the schematic diagram of all systems connected

with each other. Where it can be simulated by PROTEUS as it’s a real.

Figure (5.5): Proposed System Simulation.


Page | 44

CHAPTER 6

IMPLEMENTATION

6.1 Hardware

he model has been designed based on the dimension which camera were able

to detect. The current location of the camera is just for simulation however,

in real design there is a camera for each side. After known the maximum range which

camera can detect clearly the dimension of the model has been determined. It was designed

from wood with Box shape to allow save all of control devices and wires inside it, on the

surface there is the intersection. However, the traffic light's columns was made from iron

which vacuumed inside. You can see the model as in Figure (6.1).

Figure (6.1): The model with camera.

T


Page | 45

According to the range that camera can detected, the design has been made using

AutoCAD™, so the final design was defined as shown in Figure (6.2). However, in this

design the car’s size and street medians were considered.

Figure (6.2): AutoCAD design for traffic light intersection.


Page | 46

6.1.1 Prototype Components

1. Cars

Due to the width of the street the dimensions of cars have been determined as

follow:

Width = 2cm, Length = 6cm as shown in Figure (6.3).

2. Traffic columns

The material that used is Iron, however it’s the only material that found in

suitable size and easy to form. The dimension of tube is (1×1) cm, the height is =

15 cm and the horizontal tube length = 10 cm. as shown in Figure (6.3).

Figure (6.3): Traffic column and cars.

3. Camera Holder

For simulation the camera is installed in the middle of intersection, however in

practical it’s better to have a camera for each traffic light.

4. Accessories

To add more beauty on the prototype, some accessories have been added to the

model such as: grass turf surfaces, chairs, trees and lamps columns.


Page | 47

6.2 Software

6.2.1 Car Detection based on Image Processing

6.2.1.1 Process Methodology

The process begin with recording a real-time video by camera and send it to the

computer, then computer start the image processing using Matlab™ in several steps to

estimate the time delay desired for each traffic light and send them to the Arduino™ to

control the traffic light.

6.2.1.2 Function of Matlab:

Determine the suitable resolution for video frames which is 640x480 Pixels.

Determine the type of image as RGB (Red, Green, and Blue).

Snapshot image from video. Figure (6.4).

Figure (6.4): Snapshot image

Convert the image to the grayscale mode. Figure (6.5).

Figure (6.5): Grayscale image.


Page | 48

Convert the image to binary mode, only two colors Wight (1) and Black (0).

Figure (6.6).

Figure (6.6): Binary mode image.

Filtering the image by discard any noise less than 400 pixel. Figure (6.7).

Figure (6.7): Binary mode image with filtration.

Dividing the image to four sections, each section represent a side of the intersection

(Right, Left, Up, Down), depending on specific pixels that determine boundaries of

each section. Figure (6.8).

Figure (6.8): Divided four sections.


Page | 49

Counting objects that has (1) state in each section separately and store it in matrices.

Estimating time delay needed for each section and store them in variables

(w, x, y, z).

Send the variables values serially to the Arduino by USB port.

The previous steps are done by instruction written on Matlab. The code shown in the

Appendix (2).

6.2.1.3 Function of Arduino:

Receive the time delay values which has been estimated by Matlab and use them

to control the traffic light system.

Control the sequence of the traffic light system.

The previous steps are done by instruction written on Arduino. The code shown in the

Appendix (3).


Page | 50

6.2.2 Emergency Detecting

6.2.2.1 Process Methodology

The process was running Arduino program live time frequency measuring for the

emergency signal detecting. At first a frequency measuring program has been built, the

program measures the frequencies that come to the mic and output the measured

frequencies using the serial port. In Figure (6.9) you can see how the first frequency

measuring program was running.

Figure (6.9): Frequency measuring program.


Page | 51

After that a four siren samples were selected for testing. The samples consists of 3

wail samples and one yelp sample, all samples have been tested on the frequency measuring

program. And values of (sum, average, maximum, minimum) has been calculated as shown

in Table (6.1).

Table (6.1): Measured frequencies (sum, average, maximum, minimum)

After measuring the final average value for the samples, an If statement instruction

was added to the program to make it ready for detecting, you can see the program code in

Appendix (4).

sample 1 sample 2 sample 3 sample 4 Total

Sum 25732 409875.4 1377418 416231.6 2229257

average 1531.679 1433.131 1698.419 1313.423 1494.163

Max 2873.05 2193.28 2887.04 2984.35 2984.35

Min 853.61 826.87 877.96 716.81 716.81

final average value 1731.774


Page | 52

6.3 Solar Tracking System

6.3.1 Process Methodology

The process begin with sensing the sun light, then check if all LDR’s have the same

voltage, then the solar cell still in the same position. If not, estimate the average difference

voltage for (up, down/left, right) side, and decide the precise required position by the

microcontroller and send commands to servo motors to move to the required position. You

can see the program code in Appendix (5).

6.4 Display Boards

6.4.1 Process Methodology

The process begin with sensing a temperature from LM35 transducer as a voltage

value, and send it to the Arduino, then the Arduino covert the voltage value to temperature

value in Celsius, then the Arduino will send the temperature, guidelines and speed limit to

display them on LCD's. You can see the program code in Appendix (6).


Page | 53

CHAPTER 7

TESTING AND PERFORMANCE MEASURE

urrent traffic light systems depends on fixed time, as explained previously.

On the other hand, the system of this project estimate the desired time of the

green light based on the number of cars. These two systems can be compared through the

following example from actual life, as shown in Figure (7.1):

Figure (7.1): Traffic light example

The following example shows traffic light intersection, there are four traffic lights

on the intersection (A, B, C, D), according to the tables below that shown comparison

between the current system and project system:

Comparison between the two systems:

In the current system fixed time will be given for every traffic light, usually

traffic light (A) and (C) are given the biggest time, (B) and (D) are given the lowest time,

the time will be constant and for a traffic with 3 car capacity, usually (A) and (C) will be

given as like (18) sec. and (B) and (D) will be given as like (12) sec. as shown in Table

(7.1).

C


Page | 54

Table (7.1): Current system, Timing sequence of traffic light.

In the proposed system of the traffic light (A) will be allocated (18) s, (C) will be

given (18) s, (B) will be given (12) s, (D) will be given (0) s, and in each side the times

will be dynamic time where the time based on the number of cars. Also the proposed system

is able to detect the emergency vehicle and interrupt the sequence, as shown in Table (7.2).

Table (7.2): The proposed system time diagram

TIME 6 12 18 24 30 36 42 48

A

B

C

D

Table (7.3) shows the comparison between the two systems.

Factors Current system Proposed system

Cycle time (sec) 60 48

Number of passing cars 8 8

Emergency detecting No Yes

Solar tracking No Yes

Guidelines No Yes

And it can be concluded from Table (7.3) that the current system does not contain

the emergency detecting system, neither solar tracking system nor the road guidelines, but

the proposed system provides all these features on the traffic lights, making the traffic

process more orderly and reduce the time delay.

TIME 6 12 18 24 30 36 42 48 54 60

A

B

C

D


Page | 55

Figure (7.2): Comparison between current and proposed system based on cycle time and number of passing cars.

Can also be mentioned that in the second cycle time the current system is not taking

into consideration the cars that lined up on the previous traffic light, and traffic light time

is constant even with the number of cars that lined up, but in the proposed system the

camera will count the number of cars in each side and calculate the new time for each

traffic light, which means increased time in the current system, and shortening it in the

proposed system.

60

48

8 8

CURRENT SYSTEM PROPOSED SYSTEM

Comparison between the two systems

Cycle time (sec) Number of passing cars


Page | 56

CHAPTER 8

CONCLUSIONS

After testing and validation of the proposed system, the advantages were found that the

cycle time of the traffic lights intersection has been reduced, number of passing cars

through traffic lights has been increased, emergency detecting has solved the obstruction

of emergency vehicles, solar tracking energy system has solved the electrical cut-off

problems, and also display boards system has solved the missing guidelines.

Practical results of the proposed system were that the system has minimized the traffic

jams, provides an alternative energy source in case of electrical power cut-off, revving the

process of passing emergency vehicles, reduce disorientation of drivers that happened

because of missing guidelines.

Proposals and improvements to develop the system in the future are using the camera

as a tool to monitor the movement of vehicles in terms of the type and speed of the car,

develop a technical faults system that is linked with traffic administration to be able to

determine the type and location of the fault signal, and develop a mobile application that

can help traffic department to control traffic light through this application and dispensing

the traditional traffic control, so the control of the process will be remotely.


Page | 57

APPENDICES


Page | 58

APPENDIX 1

Tables

Table (2.5 :( Frequency and cycle rate requirements for wail.

Parameter CCR Title 13 SAE J1849 GSA K-Specification

Cycle rate lower limit in

cycles per minute (cpm).

10 10 10

Cycle rate upper limit

(cpm).

30 30 18

Minimum range of

Fundamental frequency

none 850 Hz one octave*

Minimum fundamental

frequency (Hz)

100 650 500

Maximum fundamental

frequency (Hz)

2500 2000 2000

Octave band in which

maximum sound pressure

level is measured (Hz)

1000 or 2000 none 1000 or 2000

Maximum fundamental frequency is equal to twice the minimum fundamental frequency.


Page | 59

Table (2.6): Frequency and cycle rate requirements for yelp.

Maximum fundamental frequency is equal to twice the minimum fundamental frequency.

Parameter CCR Title 13 SAE J1849 GSA K-Specification

Cycle rate lower limit in

cycles per minute

(cpm).

150 150 150

Cycle rate upper limit

(cpm).

250 250 250

Minimum range of

Fundamental frequency

none 850 Hz one octave*

Minimum fundamental

frequency (Hz)

100 650 500

Maximum fundamental

frequency (Hz)

2500 2000 2000

Octave band in which

maximum sound

pressure

level is measured (Hz)

1000 or 2000 none 1000 or 2000


Page | 60

APPENDIX 2

Code of Car Detecting System Using Matlab

s1=serial('COM3','Baudrate',9600) % Setup serial communication with speed 9600 bit/sec

with Arduino COM

fopen(s1) % Start Serial Communication

pause(2) % Delay 2 sec

vid = videoinput('winvideo',2,'YUY2_640x480'); % Input video from camera and store it in vraible to

use it again

set(vid, 'ReturnedColorSpace', 'RGB'); % Set type of return image RGB mode

preview(vid); % Preview Video

pause(2)

while(1)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Right_Traffic_Light %%%%%%%%%%%%%%%%%%%%%%%%%%%%%

img = getsnapshot(vid); % Snapshoot image from Video

imwrite(img,'test6.png'); % Store image in image file 'test6.png'

I=imread('test6.png'); % Store image in variable to use it again

figure(2)

imshow(I) % Preview Image

I=rgb2gray(I); % Convert image to gray mode

figure(3)


I=im2bw(I,graythresh(I)); % Convert image to binary mode

figure(4)


I2=bwareaopen(I,400); % Filter Image ignore object less than 400 Pixel

figure(5)

imshow(I2) % Preview Image

right= I2(176:234, 440:585); % Crop Image for Right Side

right2=bwareaopen(right,800); % Filter Image ignore object less than 800 Pixel

rn=bwboundaries(right2); % Determine Objects (Cars)

length(rn) % Count Number of Cars

x=length(rn)*6+6; % Estimate Turn On Time for Green Light

figure(6)

subplot(2,2,1)

imshow(right2) % Preview Image

if length(rn)==0

fprintf(s1,'%s','10')

pause(2)

end

if length(rn)==1


pause(x)

end

if length(rn)==2


pause(x)

end

if length(rn)==3


pause(x)

end

if length(rn)>3


pause(24)

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Left_Traffic_Light %%%%%%%%%%%%%%%%%%%%%%%%%%%%%




Page | 61


figure(2)



figure(3)



figure(4)



figure(5)


left= I2(244:305, 92:224); % Crop Image for Left Side

left2=bwareaopen(left,800);

ln=bwboundaries(left2);

length(ln)

y=length(ln)*6+6;

figure(6)

subplot(2,2,2)

imshow(left2)

if length(ln)==0


pause(2)

end

if length(ln)==1


pause(y)

end

if length(ln)==2


pause(y)

end

if length(ln)==3


pause(y)

end

if length(ln)>3


pause(24)

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% UP_Traffic_Light %%%%%%%%%%%%%%%%%%%%%%%%%%%%%




figure(2)



figure(3)



figure(4)



figure(5)


up=I2(4:129, 268:330); % Crop Image for UP Side

up2=bwareaopen(up,800);

upn=bwboundaries(up2);

length(upn)

z=length(upn)*6+6;

figure(6)

subplot(2,2,3)

imshow(up2)

if length(upn)==0


pause(2)


Page | 62

end

if length(upn)==1


pause(z)

end

if length(upn)==2


pause(z)

end

if length(upn)==3


pause(z)

end

if length(upn)>3


pause(24)

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Down_Traffic_Light %%%%%%%%%%%%%%%%%%%%%%%%%%%%%




figure(2)



figure(3)



figure(4)



figure(5)


down=I2(354:473 , 337:402); % Crop Image for Down Side

down2=bwareaopen(down,800);

dn=bwboundaries(down2);

length(dn)

b=length(dn)*6+6;

figure(6)

subplot(2,2,4)

imshow(down2);

if length(dn)==0


pause(2)

end

if length(dn)==1


pause(b)

end

if length(dn)==2


pause(b)

end

if length(dn)==3


pause(b)

end

if length(dn)>3


pause(24)

end

end


Page | 63

APPENDIX 3

Code of Traffic Light Sequence System Using Arduino

int incomingByte = 0; // for incoming serial data

char x[70];

int red_I =3;

int yellow_I = 4;

int green_I = 5;

int red_II = 6;

int yellow_II = 7;

int green_II = 8;

int red_III = 9;

int yellow_III = 10;

int green_III = 11;

int red_IV = 12;

int yellow_IV = 13;

int green_IV = 14;

int Emergency_I = 2;

int d;

void setup (){

Serial.begin(9600); // opens serial port, sets data rate to 9600 bps

pinMode(red_I, OUTPUT);

pinMode (yellow_I, OUTPUT);

pinMode (green_I, OUTPUT);

pinMode(red_II, OUTPUT);

pinMode (yellow_II, OUTPUT);

pinMode (green_II, OUTPUT);

pinMode(red_III, OUTPUT);

pinMode (yellow_III, OUTPUT);

pinMode (green_III, OUTPUT);

pinMode(red_IV, OUTPUT);

pinMode (yellow_IV, OUTPUT);

pinMode (green_IV, OUTPUT);

pinMode (Emergency_I, INPUT);

attachInterrupt(0,Emergency,RISING);

}

void loop (){

Serial.readBytesUntil(7, x, 70);

Serial.print("I received: ");

Serial.println(x);

////////////////////////////////////////////////////////////////////Traffic_I_Conditions//////////////

////////////////////////

if (x[0] == '1'){

if ( x[1] == '0')

{

digitalWrite(red_I,1);

digitalWrite(red_II,1);

digitalWrite(red_III,1);

digitalWrite(red_IV,1);

}

if (x[1] == '1')

{d=6000;

Traffic_I(d);

}

if (x[1] == '2')

{d=12000;

Traffic_I(d);

}

if (x[1] == '3')

{d=18000;


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Traffic_I(d);

}

}

////////////////////////////////////////////////////////////////////Traffic_II_Conditions/////////////

/////////////////////////

if (x[0] == '2'){

if ( x[1] == '0')

{





}

if (x[1] == '1')

{d=6000;

Traffic_II(d);

}

if (x[1] == '2')

{d=12000;

Traffic_II(d);

}

if (x[1] == '3')

{d=18000;

Traffic_II(d);

}

}

////////////////////////////////////////////////////////////////////Traffic_III_Conditions////////////

//////////////////////////

if (x[0] == '3'){

if (x[1] == '0')

{





}

if (x[1] == '1')

{d=6000;

Traffic_III(d);

}

if (x[1] == '2')

{d=12000;

Traffic_III(d);

}

if (x[1] == '3')

{d=18000;

Traffic_III(d);

}

}

////////////////////////////////////////////////////////////////////Traffic_IV_Conditions/////////////

/////////////////////////

if (x[0] == '4'){

if (x[1] == '0')

{





}

if (x[1] == '1')

{d=6000;

Traffic_IV(d);

}

if (x[1] == '2')

{d=12000;

Traffic_IV(d);


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}

if (x[1] == '3')

{d=18000;

Traffic_IV(d);

}

}

///////////////////////////////////////////////////////////////End_Conditions/////////////////////////

////////////////////////////

}

///////////////////////////////////////////////////////////////Traffic_I_loop/////////////////////////

////////////////////////////

void Traffic_I(int d){





delay(2000);


digitalWrite(yellow_I,1);

delay(2000);


digitalWrite(green_I,1);

delay(d);

digitalWrite(green_I,0);


delay(2000);



delay(1000);

return ;

}

///////////////////////////////////////////////////////////////Traffic_II_loop////////////////////////

/////////////////////////////

void Traffic_II(int d){





delay(2000);


digitalWrite(yellow_II,1);

delay(2000);


digitalWrite(green_II,1);

delay(d);

digitalWrite(green_II,0);


delay(2000);



delay(1000);

return ;

}

///////////////////////////////////////////////////////////////Traffic_III_loop///////////////////////

//////////////////////////////

void Traffic_III(int d){





delay(2000);


digitalWrite(yellow_III,1);

delay(2000);


digitalWrite(green_III,1);

delay(d);


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digitalWrite(green_III,0);


delay(2000);



delay(1000);

return ;

}

///////////////////////////////////////////////////////////////Traffic_IV_loop////////////////////////

/////////////////////////////

void Traffic_IV(int d){





delay(2000);


digitalWrite(yellow_IV,1);

delay(2000);


digitalWrite(green_IV,1);

delay(d);

digitalWrite(green_IV,0);


delay(2000);



delay(1000);

return ;

}

//////////////////////////////////////////////////////////////////Emergrncy_Interrupt_Function////////

///////////////////////////////

void Emergency()

{

digitalWrite(green_IV,LOW);

digitalWrite(yellow_IV,LOW);

digitalWrite(red_IV,HIGH);

digitalWrite(green_III,LOW);

digitalWrite(yellow_III,LOW);

digitalWrite(red_III,HIGH);

digitalWrite(green_II,LOW);

digitalWrite(yellow_II,LOW);

digitalWrite(red_II,HIGH);

digitalWrite(yellow_I,HIGH);

for (i=0; i<=1000; i++)

{ {delayMicroseconds(2000);}

}

digitalWrite(yellow_I,LOW);

digitalWrite(green_I,HIGH);

for (i=0; i<=1000; i++)

{ {delayMicroseconds(18000);}

}


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APPENDIX 4

Code of Emergency Detection System Using Arduino

#include <FreqMeasure.h> //frequency measure library in ardiuno

double sum=0; //variable for the sum of the live time frequency reading

int count=0; //variable for counting specific number of live time frequencies depending on the live

time of the instantaneous measuring you want

unsigned long finalsum=0; //variable for summing the measured frequencies

unsigned int finalnum=0; // variable for counting of measured frequencies

void setup()

{

pinMode(13,OUTPUT); //make led pin no.13 in output mode

Serial.begin(57600); //make serial communication avilable

FreqMeasure.begin(); //start the frequency measuring

}

void loop() {

if (FreqMeasure.available()) {

//if requency measuring is runing, average several reading together

sum = sum + FreqMeasure.read();

count = count + 1;

if (count > 30) {

float frequency = FreqMeasure.countToFrequency(sum / count);

sum = 0;

count = 0;

finalsum = finalsum + frequency; //start summing the meassured values

++finalnum;

if (finalnum >= 50){

//average serval measures together

float average = (finalsum / finalnum);

finalsum =0;

finalnum=0;

if ((average > 1700 && average <2100) || (average > 1100 && average <1300))

{

//check if the frequency is between the range of wail or yelp

digitalWrite(13,HIGH); // make led pin 13 on

Serial.println(average);// print the frequency to make sure of that it's in the range

}

else

digitalWrite(13,LOW); // if not make led pin 13 off

}

}

}

}


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APPENDIX 5

Code of Solar Tracking System Using Arduino

#include <Servo.h> // include Servo library

Servo horizontal; // horizontal servo

int servoh = 90; // stand horizontal servo

Servo vertical; // vertical servo

int servov = 90; // stand vertical servo

// LDR pin connections

// name = analogpin;

int ldrlt = 0; //LDR top left

int ldrrt = 1; //LDR top rigt

int ldrld = 2; //LDR down left

int ldrrd = 3; //ldr down rigt

void setup()

{

// servo connections

// name.attacht(pin);

horizontal.attach(9); //pwm pin

vertical.attach(10);

horizontal.write(servoh);

vertical.write(servov);

}

void loop()

{

int lt = analogRead(ldrlt); // top left 10bit 1024 values

int rt = analogRead(ldrrt); // top right

int ld = analogRead(ldrld); // down left

int rd = analogRead(ldrrd); // down rigt

int dtime = analogRead(4)/20; // read potentiometers

int tol = analogRead(5)/2; //256 value

int avt = (lt + rt) / 2; // average value top

int avd = (ld + rd) / 2; // average value down

int avl = (lt + ld) / 2; // average value left

int avr = (rt + rd) / 2; // average value right

int dvert = avt - avd; // check the diffirence of up and down

int dhoriz = avl - avr;// check the diffirence og left and rigt

if (-1*tol > dvert || dvert > tol) // check if the diffirence is in the tolerance else change vertical

angle

{

if (avt > avd)

{

--servov;

if (servov < 0)

{

servov = 0;

}

}

else if (avt < avd)

{

++servov;

if (servov > 170)

{

servov = 170;

}

}

vertical.write(servov);

}

if (-1*tol > dhoriz || dhoriz > tol) // check if the diffirence is in the tolerance else change

horizontal angle

{

if (avl > avr)

{

--servoh;

if (servoh < 0)

{

servoh = 0;

}

}

else if (avl < avr)

{


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++servoh;

if (servoh > 170)

{

servoh = 170;

}

}

horizontal.write(servoh);

}

delay(20);

delay(dtime);

}


Page | 70

APPENDIX 6

Code of Display Boards System Using Arduino

#include <LiquidCrystal.h> // include the library code

LiquidCrystal lcd1(12,11,5,4,3,2);

//initialize the library with the LCD1 at enable pin 11







int tempPin=0;

//data pin from temp sensor

int tempc;

// wether temp variable

void setup (){

// set up the LCD's number of columns and rows:

lcd1.begin(16,2);

lcd2.begin(16,2);

lcd3.begin(16,2);

lcd4.begin(16,2);

// clear all LCD's from data

lcd1.clear();

lcd2.clear();

lcd3.clear();

lcd4.clear();

}

void loop (){

tempc=(5.0* analogRead(tempPin) *100)/1024;

// ADC temp. conversion equation

lcd1.print ("Tabarbour >>");

// Print a message to the LCD.

lcd1.setCursor (0,1);

// set the cursor column0, row1

lcd1.print("Temperature=");

lcd1.setCursor(12,1);

lcd1.print(tempc);


lcd1.print("oC");

lcd2.print ("AL-Hashmi >>");




lcd2.print(tempc);


lcd2.print("oC");

lcd3.print ("AL-Zarqa >>");




lcd3.print(tempc);


lcd3.print("oC");

lcd4.print ("Sport City >>");




lcd4.print(tempc);


lcd4.print("oC");

delay (2000);

lcd1.clear();

lcd2.clear();

lcd3.clear();


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lcd4.clear();

delay (200);





lcd1.print ("AL-Hashmi <<");


lcd1.print("Speed Limit = 60");

lcd2.print ("Tabarbour <<");



lcd3.print ("Sport City <<");



lcd4.print ("AL-Zarqa <<");



delay (2000);

lcd1.clear();

lcd2.clear();

lcd3.clear();

lcd4.clear();

delay (200);





}


Page | 72

REFERENCES

1- Chandrasekhar. M, et al, International Journal of Engineering Research and Applications (IJERA).

2- Nagaraj, et al, International Journal of Engineering Research and Applications (IJERA), Vol. 3,

Issue 2, March -April 2013, pp.1087-1091.

3- Dangi, et al, Sardar Patel Institute of Technology, Mumbai, India.

4- Fazenda, et al, ICCAS-SICE, International Joint Conference, 18-21 Aug. 2009.

5- Hashim, et al, Faculty of Electronics & Computer Engineering, Universiti Teknikal Malaysia

Melaka, Malaysia.

6- Moghbelli et al, Texas A&M University at Qatar, Doha, Qatar.

7- National Institute of Justice, Guide to Test Methods, Performance Requirements, and Installation

Practices for Electronic Sirens, Used on Law Enforcement Vehicles, NIJ Guide 500–00.


Page | 73

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