Anti-Smog Radar Application for Vehicles

International Journal of Modern Research in Engineering & Management (IJMREM)
||Volume|| 2||Issue|| 2 ||Pages|| 22-33 || February 2019 || ISSN: 2581-4540
www.ijmrem.com IJMREM Page 22
Anti-Smog Radar Application for Vehicles
1,
Ghulam Fiza Mirza, 2,
Abdul Razzaque Jawad, 1,
Hyder Bux Mangrio,
3,
Ghulam Rubab Mirza
1,
Department of Telecommunication Engineering, Mehran University of Engineering & Technology
Jamshoro Pakistan
2,
School of Electrical Engineering and Computer Science, National University of Science and Technology
Islamabad, Pakistan
3,
Department of Electrical Engineering, Mehran University of Engineering & Technology
Jamshoro, Pakistan
----------------------------------------------------ABSTRACT-----------------------------------------------------
Smog is regarded as a dangerous situation for vehicles as the visibility of human fails and a person cannot
drive smoothly and safely which can lead to severe accidents and routine disturbances. Hence, “Anti-Smog
Radar Application for Vehicles” is proposed using Internet of Things technology which ensures the smooth flow
of vehicles in smog and prevents accidents in time and cost-efficient manner by detecting and displaying the
front objects with their important information (distance, position, velocity and size) on smart phone used by
authenticated drivers. The radar application controls the hardware system to be deployed on vehicles through
which the user can start, stop and set the hardware in particular direction. The hardware contains NodeMcu
(Microcontroller with built-in Wi-Fi), Ultrasonic sensor and servo motor. The servo is used to detect the
position of front objects and ultrasonic sensor is clipped on servo to detect the objects. For alerts, the objects
are drawn with different colors on application i.e. the red colored objects will be near to the vehicle, the yellow
colored objects will be at some distance from the vehicle and the green colored objects will be far from the
vehicle. Kalman algorithm is used to filter the ultrasonic readings to eliminate the noise. The proposed system
can work in every condition i.e. in day and night.
KEYWORDS: Internet of Things (IoT), Kalman Filter, Radar Application, Smog, Vehicles.
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Date of Submission: Date, 15 February 2019 Date of Accepted: 24. February 2019
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I. INTRODUCTION
There are various situations where human visibility fails resulting into catastrophe and insecurity. Example of
such situations is darkness, smog, rain, etc. Due to low visibility in smog, severe road accidents have occurred in
Asian countries such as: The report issued in Nov, 2017 indicates that in different cities of Punjab, 18 people
were killed and several people injured due to road accidents in smog which also killed 3 children in Layyah [1].
Another accident happened due to smog on Yamuna Expressway, Delhi on Nov 8, 2017 in which 24
automobiles were destroyed and many drivers were injured [2]. Indian media reported in Nov 2017 that as
compared to previous years, 30% road accidents are raised due to visibility problem in smog. The report
mentions that 515 accidents happened in one week in Lucknow and Ghaziabad, India [3]. In China and many
other countries, the automobiles are banned in smog for security purpose which leads to routine disturbance. An
effective system must be developed so that the accidents can be prevented and drivers can get the knowledge of
front objects along the road in order to provide safe and smooth drive by saving time. The proposed system uses
IoT technology to ensure the smooth flow of vehicles in a smoggy atmosphere and prevent large scale
catastrophe by detecting, locating and displaying the front objects with their important information such as
objects’ distance, position, velocity and size to the driver via android application. The hardware part of system
consists of NodeMcu (Microcontroller), Ultrasonic sensor and Servo motor as shown in Fig.1 which could be
fixed on the front of vehicle. The ultrasonic sensor is mounted on servo motor to calculate the distance and
velocity of objects from 0° to 180° angular position. Using built-in Nodemcu’s ESP8266 Wi-Fi module, the
distance, angular position and velocity of objects are then sent to the Firebase database to be used by android
application.

Fig.1 Block Diagram of Proposed System
The android application is developed in Android Studio which will be used by authenticated users (drivers) to
control the hardware system. The authentication is provided by login page where the user will enter the
registered email and password. If the user is not registered, he needs to get registered first by clicking the register
button on application and he will be directed to the registration page. For security purposes, the user can enter
invalid data (i.e. email and password) on login page only up to five times and after that the login button will not
work. If the login is successful, he will be able to use the radar application. When a user presses the start button
of android application, he will be able to see the front objects, angular position of object, size of object and
distance of objects from 0° to 180°. The objects are drawn on the application with respect to their distance from
the system i.e. red colored objects will be near to the vehicle, yellow colored objects will be at some distance
from the vehicle and green colored objects will be far from the vehicle hence, providing alerts to the user. The
user can also set the system at particular angular position to detect the specific object and view its distance,
position and velocity. The ultrasonic sensor measurements are filtered using Kalman filter in order to remove the
background noise and reduce the variations in the measurements.
Literature Review: Related work is studied and compared with the proposed system. In [4], embedded system
approach is used to develop arduino based radar system using servo motor, arduino microcontroller, ultrasonic
sensor and Java application. The ultrasonic sensor is clipped on servo motor so that the objects can be detected
at different angles. The java application is designed in processing software which can provide the visualization
of distance and angle readings on computer screen. In [5], Researchers have developed a radar system based on
velocity of ultrasonic signals in air to obtain angle and distance for fixed targets found in front of device. For
transmitting and receiving ultrasonic signals at 40 KHz, arduino microcontroller is used. The delay between
transmitted and received signal is observed using oscilloscope to manually calculate the object distance and
compare it with radar detected distance. Two types of alarms are generated and tested, first alarm is the visual
alarm which can be seen on personal computer screen and considered as radar screen and secondly the audible
alarm via LCD digital screen. In [6], rescue workers are assisted by taking a look of room having limited
visibility and hazards via designed device. The device is developed using array of ultrasonic sensors which
measures distances in the room and transmits distance data to processing software so that the object’s
information can be displayed to user.
The 2D image of room is generated with MATLAB using the system. For starting operation, MATLAB provides
a signal to the device which will start collecting data from arduino and sends the data to MATLAB so that the
2D plot can be generated. In [7], researchers have implemented distance identifier and target direction using
zigbee module. Signal is detected for moving and stationary object. Radar operation is monitored by AT89s52
microcontroller which is attached with DC motor and is integrated with radar target identifier system which
possesses pair of ultrasonic for moving objects and pair of IR for stationary object. The sensors track objects at
all angles and in case if object is moving in any direction then microcontroller communicate with zigbee on the
reception of control signal from sensors. The buzzer will beep in case of target detection and object status is
shown on LCD for user.

In [8], radar system is developed by researchers to calculate the direction of moving object and its position is
estimated. The system is composed of ARM7LPC2148, ultrasonic sensors array, power supply, 16×2 LCD,
Reset and crystal oscillator. Threshold echo identification level is set using comparator in order to prevent false
reflections. Three transistor amplifiers are used followed by a peak detector and comparator. By providing
power supply, radar starts its operation and ultrasonic sensors that are attached on antenna starts transmitting
ultrasonic waves to detect the target. Hence, the portion is continuously controlled by radar and in case if object
is found in that portion, alarm will be produced to start base station. The target distance and direction will be
displayed on LCD screen. In [9], Ultrasonic sensor is connected with arduino UNO and its signal is visualized
on the screen of laptop to identify the target in front of sensor in the range of 3 cm. The sensor is clipped on
servo motor to provide rotation of sensor from 15° to 165°. In [10], smart driver alert system is proposed in
which video stream is first provided to the system consists of traffic signboards and voice message is provided to
the driver upon recognition of signboard. Template matching is used which implements correlation coefficient
algorithm for comparison of images and recognition of signboard. In [11], motorcycles are identified and other
drivers are alerted when they find motorcycles surround them by simulating the scenario on OMNET++ and
INET. For this, IoT is used to separate the network into small clusters. Android application used by drivers send
MAC addresses to probe nodes via Wi-Fi or Bluetooth so that the vehicles can be identified. The drivers are
differentiated, registered to the master node, alerted of nearby motorcycles and removed from database on
moving to different cluster via probe node. In [12], the collision of vehicles is sensed by sensors which then uses
operations and parameters (acceleration and temperature) related to vehicle and inform the nearby sensors to
provide help to the collided vehicles. If lighter collision occurs, only the nearby sensors and local people will be
informed whereas in case of higher collision, the car’s location and other related information (such as
acceleration and temperature) will be sent to cloud with which nearby hospitals and showrooms are informed.
Comparison of Existing Systems with Proposed System: The systems described above use processing
software for visualizing radar data on personal computers. They mostly provide limited features (such as angle
or distance estimation) and cannot be used in vehicles as they are not providing such features to be used by
vehicles such as the data is visualized on personal computers. They are not utilizing any filter algorithm to
reduce the noisy data from sensor measurements. The works are simulated and not implemented in real time.
Compared to existing systems, the proposed system provides maximum features to make it suitable for high
speed vehicles. The android application is built which does not only displays the objects on chart but also shows
object related information such as distance, position, velocity and size. The system does not only rotate from 0°
to 180° to detect and obtain the information of object but can also be set at particular direction to view the
specific object and its necessary information. For security reason, the application requires the user to register
first and only authenticated users can use the application. It also maintains records of data by storing it on
Firebase and can be accessed anytime from anywhere. Moreover, the noise is removed from ultrasonic readings
to produce more accurate results using Kalman Filter. Hence, the proposed system provides cost efficient
solution to drivers to drive smoothly and avoid accidents in smog, rain, fog or any situation where person is not
able to view the scenario.
II. METHODOLOGY
The hardware design of proposed system is shown in Fig.2 and flow diagrams are shown in Fig.3 and Fig.4. The
working of radar system is described under:
➢ User Authentication via Application: The android application designed in Android Studio will be used by
authenticated user. For authentication, the user will be firstly directed to the Login page where he will enter his
necessary credentials (i.e. Email & Password) to use the application. If user is registered, the login will be
successful and he will be able to use the radar application. If user is not registered, he will need to be registered
first by pressing the “REGISTER” button so he will be directed to the registration page in order to get registered.
After registration, he will be moved to the Login page where he will enter the credentials and press the “LOGIN”
button to use the application. For security purpose, if user enters wrong credentials more than 5 times, the login
button will not work.
➢ Objects’ Detection From 0° to 180°: After successful Login, user will be directed to another activity of
application where he can see the radar chart and can control the system via application. On radar screen, there
are START, STOP, LOGOUT and SEND buttons. When a user press “START” button, the “Servo Status” of
Firebase field is set to 1 and NodeMcu continuously checks the status of another Firebase field “Servo”. If the
status of “Servo” field is 0, the servo motor starts rotating from 0 to 180 degrees and ultrasonic sensor mounted

on servo motor continuously calculates the distance of object (if found) using (1) as servo moves. The distance
readings are filtered using kalman filter to observe the accuracy of ultrasonic sensor.
(1)
Fig.2 Hardware Design of Proposed System
➢ Kalman Filter: This Algorithm works on two major processing stages i.e. Stage prediction and Update phase.
The stage prediction involves (2) and (3) [13] where is a predicted state estimation to be used by updated
state estimation and is a predicted error covariance in which Q represents process noise covariance
which will be used by updated error covariance. The algorithm uses (4), (5) and (6) for update phase [13] where
represents Kalman gain which reduces the updated error covariance and R represents measurement
covariance noise. It considers the sensor system dynamic equations with order system one by keeping F=1, B=0,
H=1, Q= and R=0.58. The value of Q is chosen randomly at which the results become accurate whereas the
value of R is calculated on Microsoft Excel using the variance formula on measurement distance raw data.
➢
(2)
(3)
(4)
(5)
(6)
These equations after substituting their values are then inserted into Arduino IDE using programming language
to filter the distance measurements.
➢ Data of Objects’ Detection From 0° to 180° on Firebase: The distance and servo angle readings are
pushed to the Firebase and android application do parallel tasks such as fetches those readings from Firebase,
displays them on the layout along with object size readings and draws the objects (if found) on radar chart with
alerts. Objects are detected using distance readings, if distance reading found greater than 0, object is detected
and drawn on the chart. For alerts, if the distance readings are found less than 100 cm, objects are found near to
the vehicle and drawn with red color, if distance readings are found greater than 100 cm but less than 200 cm,
the objects will be at some distance from vehicle and drawn with yellow color, and if distance readings are
greater than 200 cm, the objects will be far from vehicle and drawn with green color on radar chart.
➢ Objects’ Size Calculation: The width size of object is calculated when the servo rotates continuously from 0
to 180 degrees whereas when the servo is set to particular direction, the size will be shown as 0 because the

edges of objects cannot be found with static servo motor. When the blue line (Animated one) will scan the object
drawn on chart, there will be an increment in the size variable from starting of object till end of object. The size
variable is based on intercept formula shown below [25]:
(7)
Where x is the distance between object and sensor and y is the servo position.
➢ Data of Objects’ Detection at Particular Position on Firebase: When “Servo Status” is set to 1 and user
wants to see the object and its related information at particular position, he can enter the position and press
“SEND” button on application to pass that value into the Firebase field of “Servo”. If NodeMcu detects that the
status of “Servo” field is other than 0, it will set the servo motor in the direction given by user. The distance of
object in that direction will be calculated and filtered using the same process described above. Using the distance
readings, velocity of object will be calculated using (8) in order to observe that the detected object is in motion
or rest condition. These readings (i.e. Servo position, Distance and Velocity) are then sent to the Firebase. The
android application fetches those readings from Firebase, draws the object on radar chart and displays the
information on its layout.
(8)
➢ STOP Button of Application: If user wants to stop the system, he can press the “STOP” button and Firebase
field “Servo Status” is set to 0. When NodeMcu finds the value of “Servo Status” as 0, it will set the servo at
center (90°) and stops sending the data to Firebase.
➢ Logout Button of Application: By pressing the “LOGOUT” button, user will be directed to the login page
and he will be no more using the application.
III. RESULTS
The results obtained for proposed system are discussed below:
User Authentication Results : In order to use the radar application, user will be first directed to the login page
as shown in Fig.5 where he will enter his registered email and password and press LOGIN button to use the
application and if user enters wrong credentials, he will be notified of unsuccessful login and the number of
attempts for every wrong sign-in is decremented for security purpose. If user is not registered (does not have
registered email and password), he will need to register first by clicking REGISTER button and new activity will
be opened where user will provide his email and password to register it as shown in Fig.6. When user registers,
the account upon his registration will be created with the unique id in Authentication section of Firebase and user
will be able to use the application as shown in Fig.7.
Radar Application Results: After the successful Login, user will be directed to the radar view of an application
as shown in Fig.8 which shows the radar chart along with START, STOP, SEND and LOGOUT buttons. By
touching START button, user will be able to see the detected objects on chart and readings of distance, angular
position, velocity and size of objects will also be displayed. User can view the object at particular angle by
giving angular position in EditText and touching SEND button. Using Logout button, user will exit from the
radar screen and move to the main page i.e. Login Page. When user press START button on application, the
Firebase field “Servo_Status” will be equal to 1 as shown in Fig.9 and the hardware system perform its function
by rotating servo motor from 0 to 180 degrees and detects the object distance at these angles using ultrasonic
sensor. The readings of detected objects and their corresponding angles are stored in “ObjectDetection” field as
shown in Fig.10 whereas the angles of servo are stored in “ServoAngle” field as shown in Fig.11.

Fig.3 Flowchart of Android Application and Fig.4 Flowchart of NodeMcu and
Firebase Communication Firebase Communication
Fig.5 Login Activity of Application Fig.6 Registration Activity of Application

Fig.7 User Authentication on Firebase
Fig.12 shows application layout which displays the current object’s distance 8 cm, angular position 99° and size
3.23 cm. As the servo motor rotates and object is detected then its distance, angle and size will be updated on the
layout and objects are drawn on the chart. The blue line is animated from 0° to 180° according to the current
angular value read from Firebase field “Servo Angle” which continuously checks that if object exists at it’s
position, size will be increased continuously till the object ends and if the object is not found, size will be 0 and
when the distance of object is found greater than 0, objects are drawn on chart with alerts (Red color for near
object, Yellow color for object found at some distance and green color for far object found) as shown.
Fig.8 Radar Application Fig.9 Servo_Status=1 and Servo=0

Fig.10 Detected Object Readings on Firebase Fig.11 Servo Rotation Angles on Firebase
Fig.12. Objects’ Detection from 0° to 180° Fig.13 Actual VS Radar Measured Object Size
Multiple objects found and are displayed on the radar chart and when the new sweep of servo begins, the objects
of previous cycle will be removed. Testing was conducted by placing different size of objects in front of radar
and actual measurement is compared with the radar measurement size. The results for tests are shown in Table1
and Fig.13 which indicates that the accuracy percent of radar size measurement is satisfactory. The velocity is
not calculated when the servo is in motion because if the static object is detected at particular distance but due to
servo rotation, the distances from that object varies and it will show the velocity reading other than 0 which is
not correct. Therefore, the feature of velocity calculation is done when the servo is positioned at particular angle.

Table 1 Readings of Actual and Radar Measured Object Size
Sno: Actual Object Sizes Radar Measured Sizes
1. 3cm 4.9cm
2. 4cm 6cm
3. 4.5cm 8.8cm
4. 4.7cm 9.3cm
5. 5cm 10.7cm
6. 5.6cm 7.5cm
7. 6cm 5.3cm
8. 7cm 10.5cm
9. 7.5cm 13.8cm
10. 8cm 10.44cm
11. 14.5cm 16.4cm
Fig.14 shows that when user provides particular angle from application, the Firebase field “Servo” will be set to
that angle and Nodemcu when finds the field “Servo” other than 0 it will set the servo at provided angle as
shown in Fig.15.
Fig.14 Servo_Status=1 and Servo=170 Fig.15 Hardware System Set to 170°
When a particular position is given by user, the system along with the calculation of distance also calculates the
velocity of object to detect that whether the object is moving or stationary and sends velocity readings
continuously to the firebase. The application fetches those velocity readings from Firebase and displays them on
the layout for user as shown in Fig.16. The hardware system is set to different angles for testing purpose where
Fig.17 shows that the system is set to angle 90. The size of object in stationary position of servo is always 0 as
servo will not recognize the start and end points of detected objects due to its rest position.
Kalman Filter Results : Ultrasonic sensor detects objects at distances but there occurs fluctuations in the
measurements hence, kalman algorithm is applied to smooth the values by calculating the previous values and
setting threshold. Blue signal in the Figures represent ultrasonic measured distance readings and red signal
shows the filtered readings. Results are obtained by rotating servo and object was placed at 3cm in Fig.18 and at
4cm in Fig.19. It is found from Figures 18 and 19 that the blue signal is fluctuating continuously whereas the red
one sets the threshold based on values of sensor and provides smooth signal.

Fig.16 Application Layout at 170° Fig.17 Application Layout at 90°
Fig. 18 Filter Performance at Object Distance 3cm Fig.19 Filter Performance at Object 4cm
The measurement noise R is calculated using variance formula on raw data of ultrasonic sensor in excel as
shown in Fig.20.
Fig.20 Variance Calculation in Excel

IV. CONCLUSION
In smog, the general problem which occurs is the low visibility or even a human cannot see the front view
resulting into accidents and disturbances in the routine of people. Keeping this problem in view, the radar system
for vehicles is proposed which detects the front objects from 0 degrees to 180 degrees which are shown on
developed application along with object related information such as distance, position and size. To provide alerts
to the user about objects’ distance, the objects are displayed on application with different colors such as red
colored objects indicates less distance between the vehicle and objects, yellow colored objects indicates that the
vehicle is at some distance from objects and green colored objects indicate that the vehicle is in safe mode as the
objects are far from it. The system can also be set in a particular direction via application to view specific object
and its information. By setting servo at particular direction, the velocity of object along with other information is
also calculated to know that the object is in motion or rest. The android application will be used by authenticated
drivers. The ultrasonic sensor readings are filtered to reduce the noise measurements. The proposed system is
tested and offers good results. The work can be extended by increasing the range of system replacing with the
efficient and large range ultrasonic sensor. The accuracy of system can be further improved as the results
obtained for size of object shows the differences with actual object size by applying efficient algorithms so that
the object’s size can be improved and approaches to the real size. Object type can also be detected via Machine
learning algorithms.
REFERENCES
[1] Sana Jamal, “Smog in Pakistan causing accidents, illness and flight disruption”, Gulf News Pakistan.
Published: 19:25 November 7, 2017. Last accessed on 22-12-2018.
[2] Anindita Sanyal, “Blinding Smog Causes 24-Vehicle Pile-Up on Expressway Near Delhi”, Delhi News
India. Updated: November 08, 2017 15:50 IST. Last accessed on 22-12-2018.
[3] Shalabh, “Smog triggers 30% rise in road accidents in 2 days”, Times of India, Nov 9, 2017, 11:51 IST.
Last accessed on 22-12-2018.
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System Based Radio Detection and Ranging (RADAR) System Using Arduino and Ultra-Sonic Sensor.
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BIOGRAPHIES
Engr. Ghulam Fiza Mirza received her Bachelor’s degree in Telecommunication Engineering in 2016 from
Mehran University of Engineering & Technology (MUET), Jamshoro. She is currently doing Joint Master from
University of Malaga, Spain and Mehran UET. Her research interests include Wireless Sensor Networks,
Internet of Things and Vehicle to Vehicle Communication.
Abdul Razzaque Jawad is currently pursuing bachelor’s degree in Computer Science from National
University of Sciences and Technology, Islamabad (NUST). His research interests include in the fields of
Artificial Intelligence, Algorithms Design, Internet of Things (IoT) and Programming.
Hyder Bux Mangrio is working as Assistant Professor in Department of Telecommunication at Institute of
Information & Communication Technologies (IICT), Mehran UET, Pakistan. He received his B.E in
Telecommunication and PGD from Faculty of Electrical, Electronics & Computer Engineering at Mehran UET,
Pakistan and his Master from Hamdard University, Karachi in 2017. His research interests include
Optoelectronics and Optical Communication, Visible Light Communication, Internet of Things and underwater
Optical Communication.
Engr. Ghulam Rubab Mirza received her Bachelor’s degree in Electrical Engineering in 2017 from Mehran
University of Engineering & Technology (MUET), Jamshoro. She is currently pursuing M.E in Power
Engineering from Mehran UET. Her previous published research paper is on Design and Fabrication of
Underground Fault Distance Locator Using Arduino and GSM in a 11th
International Conference on Open
Source Systems and Technologies (ICOSST-2017). Her research interest includes in the field of Automation &
Control and Internet of things (IoT).

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