E-Ticketing System for public transport

By-
Chirayu Deokar (B150408556)
Iliyas Khan (B150408559)
Shantanu Kulkarni (B150408563)
Utkarsh Patil (B150408566)
Guided by-
Prof. Suruchi Nannaware
Jayawantrao Sawant College of Engineering
Department of Information Technology

 Abstract
 Introduction
 Literature Survey
 Disadvantages of Existing System
 Proposed system
 Methodologies to implement the System modules
System Requirements
 Algorithms Used
 Goals and Objectives
 Project and System Requirements
 Conclusion
 References
Content
2

 Existing System Constraints
 Advantages of our System
 Ease of booking
 QR Code
 Wallet payment
 Security
 Data Analysis
Abstract
3

Introduction
• Users interact with the system from anywhere
• User can book bus seat in advance
• Payment can be done using E wallet
• User generates QR code
• Conductor scans QR code
• Data Analyst performs analysis on gathered data
4

Literature Survey
IEEE Papers Technology Used Description Drawbacks
GPS Supported City
Bus Tracking &
Smart
Ticketing System
(2015)
GPS & Smart
Card
Gives information
about vehicle position
and route travelled by
vehicle and includes
the integrated
use of smart cards
with GPS system.
Expensive to
introduce.
Risks of fake smart
cards-ticket still exist.
RFID and Android
Based Smart
Ticketing and
Destination
Announcement
System (2016)
RFID tag & GPS
Combines RFID and
GPS technology to
design an automatic
bus-ticketing system
Sometimes not as
accurate or reliable as
barcode scanners.
Implementation can be
difficult & time
consuming.
Electronic Ticket
Machine Data
Analytics for Public
Bus Transport
Planning
(2017)
ETM
Line-planning for bus
transport systems
based on data elicited
from Electronic Ticket
Machine (ETM).
Expensive to
Introduce.
Lots of specific
technical requirements
both passenger and
transport operators.
5

 Beneficial to employees and passengers
 Information available at fingertips
 Easy Booking and Execution of the system
 Security :
 Authentication
 AES
 Data analysis helps in monitoring overall function
Proposed system
6

Methodologies to implement the
System modules
1. User
2. Conductor
3. QR code
4. Admin
13

14
USER
 Register or login
 Select source and destination
 Check bus availability
 A unique QR code is generated
 User can travel in any bus on that route
 Other Features :
 Bus Tracking
 E -wallet Management

15
CONDUCTOR
 Scan Users QR code
 Validate Passenger details
 Automatically update database

16
QR code
 QR code is a 2 dimensional barcode
 Can b read horizontally as well as vertically
 A unique QR code for every booking
 QR code contains:
 user details
 Source
 Destination
 date and time of booking
 total fare.

17
Admin
 Admin plays an important role in smooth functioning of the
system
 Managing data stored in database
 Adding new busses to the system
 Allotting new TC to bus
 A well organized machine learning algorithm helps admin
analyse the data and take better decisions
 We have analyse the number of adults and children
travelling in a particular period

1] AES (Advanced Encryption Standard)
 AES is more secure algorithm. It is established
by U.S. National Institute of Standards and
Technology in 2001.
 AES is symmetric key algorithm.
 So we use the AES algorithm to secure the
information i.e. stored in QR code.
 This algorithm is generally divided in to two
steps. The following step is involved:-
Algorithms
18

Step1- Convert the data into QR
code
19

Step1- Convert QR code into data
20

2] Haversine
 The haversine formula determines the great-circle distance between
two points on a sphere given their longitudes and latitudes.
 The haversine formula is used in electronics and other applications
such as navigation. It helps in finding out the distance between two
points on a sphere.
Algorithms
21

22
Haversine Formulation
 Let the central angle Θ between any two points on a sphere be:
Θ = d/r
where:
- d is the distance between the two points (along a great
circle of the sphere; see spherical distance),
- r is the radius of the sphere.
 The haversine formula hav of Θ is given by
where r is the radius of earth(6371 km), d is the distance between
two points, φ1, φ2 latitude of the two points and λ1, λ2 is
longitude of the two points respectively.

23
Haversine Formulation
 Solving d by applying the inverse haversine or by using the
inverse sine function, we get:
OR

34
Data Analysis
 Analysis of Children and Adult tickets
 Histogram prepared gives a broader sense of travelers
 Other Analysis showing bus route traffic can also be
useful

• Consumers now gain time because they have the
possibility to buy and use their tickets whenever they
want and wherever they are thanks to their smartphones.
• The E-ticket is also eco-friendlier, compared to the paper
ticket it doesn't need to be printed, paper consumption
will thus decrease, making it even better for our planet
• It will be impossible to lose your ticket.
• To make the whole journey of a passenger enjoyable and
hassle-free.
• The location of the bus can be observed continuously
using GPS system.
Goals and objectives
35

 Android Studio :- To develop android
based app
 MySql , Xampp :- To Store Database
Information
 PHP :- To Create Web Services
Project Requirements
36

 Hardware Requirements:
 System : Intel I3 Processor.
 Hard Disk : 20 GB.
 Monitor : 15 VGA Colour.
 Mouse : Logitech.
 Ram : 4 GB
 Software Requirements:
 Operating system : Windows 7 and above.
 Coding Language : JAVA, ANDROID
 IDE : Android Studio
 Database : MYSQL
System Requirements
37

Problem Statement
“To design and Implement a secured E-
Ticketing system for public bus transport to
provide hassle free travel to daily users”
38

 This system provides online reservation of bus.
System is user friendly and accurate .It is available
for 24 hours. No need to go to the bus enquiry
office.
 The system is automatic and online which save
everyone’s valuable time.
 Bus Tracking will help users to get Real time
Location of buses.
 Data analysis provides smooth functioning of the
overall travel system.
Conclusion
39

 [1] Anila Cyril, Varghese George, Raviraj H. Mulangi "Electronic
Ticket Machine Data Analytics for Public Bus Transport
Planning", 2017 International Conference on Energy,
Communication, Data Analytics and Soft Computing (ICECDS),
21 June 2018.
 [2] Ajay Shingare, AnkitaPendole, Nikita Chaudhari and
Parikshit DeshpandeGPS Supported City Bus Tracking Smart
Ticketing System, 2015 International Conference on Green
Computing and Internet of Things (ICGCIoT), 14 January 2016
 [3] Prasun Chowdhury, Poulami Bala, Diptadeep Addy,Sumit
Giri, Aritra Ray Chaudhuri RFID and Android Based Smart
Ticketing and Destination Announcement System (ICACCI) 03
November 2016
 [4] Van Ly, M.; Martin, S.; Trivedi, M.M. Driver classification
and driving style recognition using inertial sensors. In
Proceedings of the 2013 IEEE Intelligent Vehicles Symposium,
References
40

 [5] Aljaafreh, A.; Alshabatat, N.; Najim Al-Din, M. Driving style
recognition using fuzzy logic. In Proceedings of the 2012 IEEE
International Conference on Vehicular Electronics and Safety
(ICVES), Istanbul, Turkey,24–27 July 2012; pp. 460–463.
 [6] Al-Sultan, S.; Al-Bayatti, A.; Zedan, H. Context-aware driver
behavior detectionPositioning System data. In Proceedings of the
2011 IEEE International Conference system in intelligent
transportation systems. IEEE Trans. Veh. Technol. 2013, 62, 4264–
4275.
 [7] Mohamad, I.; Ali, M.; Ismail, M. Abnormal driving detection
using real time Global on Space Science and Communication
(IconSpace), Penang, Malaysia, 12–13 July 2011; pp. 1–6.
 [8] Dorr, D.; Grabengiesser, D.; Gauterin, F. Online driving style
recognition using fuzzy logic. In Proceedings of the 2014 IEEE 17th
International Conference on Intelligent Transportation Systems
(ITSC), Qindao, China, 8–11 October 2014; pp. 1021–1026.
References
41

E-Ticketing System for public transport

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