DIGITAL TICKETING AND CROWD DETECTION SYSTEM FOR BUSES USING MOBILE APPS, IOT, AND ROUTE OPTIMIZATIO

Abstract

Abstract This idea introduces an innovative system designed to optimize both public and private bus transportation using. mobile applications, smart cnrd technology, loT, real-time data analytics, and route optimization. The system enhances routing efficiency, passenger safety, and user satisfaction by providing secure digital payments, real-time bus tracking, and passenger capacity monitoring. For. public transit, the system dynamically adjusts routes using real-time data, ensuring optimal travel times and reducing delays through its route optimization feature. Advanced crowd management is implemented using OpenCV technology to maintain safe occupancy levels, improving safety and comfort. The integration of mobile apps and smart cards enables seamless digital ticketing, with transactions securely stored on a decentralized ledger, eliminating fare evasion. For private institutions, such as schools and colleges, the system tracks bus movement, including live updates on locations, pickup and drop points, timings, and bus fee payment status, enhancing security. This comprehensive system not only improves operational efficiency and safety but also contributes to more sustainable and user-friendly transportation solutions for both public and private networks.

Specification

Field of Invention
This present invention relates to a method and system for digital ticketing, crowd detection,
and route optimization tor public and private buses using mobile apps, smart cards, loT,
and OpenCV technology.
Background of Invention
I) The Future of Travel in public Bus Service: How a Mobile Bus Ticketing System is
Revolutionizing the Public Travel
- T. Kavitha, G. Senbagavalli
The report on local bus ticketing identifies several significant flaws in the current manual
and semi-digital systems. One of the primary difficulties is the trouble that travellers suffer
when attempting to balance their bus tickets, which frequently results in delays or
incapacity to go. Furthermore, the validation process for these tickets can be timeconsuming,
particularly during peak hours, raising the potential of human error and
resulting in revenue loss owing to fare evasion. Another key disadvantage is the manual
gathering and reconciliation of balance amounts, which is time-consuming and prone to
.error. The lack of a completely automated system also renders the refund or cancellation
process inefficient, causing frustration among passengers who must cope with slow
payback processes. Additionally, without real-time updates or notifications, users are left
with little control or clarity over their bookings. The paper suggests that these limitations
create barriers to user convenience, and there is a need for more advanced, automated
solutions to streamline the ticketing and validation processes while ensuring greater
transparency and efficiency.
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2) Efficiency Analysis of Online Ticket Reservation System in Rajasthan State Road
Transport Corporations (RSRTC) Using ITS & ICT Enabled Services
- Mahendra Parihar, Varuni Sharma
The study focusses on the issues confronting the passenger road transport sector, notably
in the state of Rajasthan, with a special emphasis on the Rajasthan State Road Transport
Corporation (RSRTC). Despite increases in bus capacity and number ofbuses, the RSRTC
continues to -suffer from financial inefticiency, having been a loss-making company for
numerous years. According to the report, raising passenger numbers is critical to improve
the corporation's financial health, which may be accomplished by providing additional
conveniences such as a flawless online ticket reservation system. Despite efforts to improve
online ticketing services, the RSRTC continues to have challenges that cause passenger
annoyance and displeasure. These issues can sometimes evolve into clashes between
passengers and personnel. The paper's goal is to analyse the current online ticket
purchasing system, identifY the difficulties generating unhappiness, and propose ICTenabled
remedies that can improve the system without putting a large financial strain on
the already suffering RSRTC. The research highlights several problems, including
financial insecurity, poor amenities, and an ineffective online ticket reservation system that
need additional improvement to satisfy consumer expectations.
3) Cloud Based Town Bus Ticket Payment System Integrated with Mobile Application
- Sathish M
The paper identifies various flaws in the current bus transit system, including constant
overcrowding, which compromises passenger comfort and safety. While the planned smat1
application attempts to enhance seat distribution and enable cashless payments, it may
struggle to handle real-time passenger flow during busy hours. Furthermore, the issue of
assuring prompt refunds for unused ticket balances remains unsolved, which may
contribute to passenger unhappiness. Overall, while the digitalisation efforts are admirable,
their successful implementation may encounter substantial operational challenges.
4) Parallel Transpottation Management and Control System and Its Applications m
Building Smart Cities
- Fenghua Zhu; Zhenjiang Li; Songhang Chen; Gang Xiong
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The study addresses how smart city technology improvements can help ease traffic
congestion by developing parallel transp011 management and control systems (PTMS). It
focusses on the integration of artificial systems, computational experimentation, and
parallel execution (ACP) to produce more intelligent transportation systems. The suggested
architecture incorporates critical components such as social signals, intelligent
transportation system (ITS) clouds, agent-based traffic control, and transportation
knowledge automation. While the study covers the technological components and includes
a case study to evaluate performance, it may not fully address the practical issues of
deploying such sophisticated systems in various metropolitan areas. Furthermore, the
proposed systems' scalability and flexibility to changing traffic situations and city
intrastructures need additional investigation.
5) Crowd Detection Management System
- Wafaa Mohib Shalash
The research paper describes a mobile-based crowd anomalous behaviour detection and
management system designed to improve safety in crowded settings such as schools,
stadiums, and pilgrimage sites. While the suggested system employs advanced technology
to manage the substantial hazards associated with crowded environments, such as panic,
stampedes, and mob crushes, it does have some drawbacks that require additional
examination. One significant disadvantage is the dependency on IP surveillance cameras
for crowd behaviour identification. This dependency may present difficulties in terms of
camera location, coverage, and privacy considerations. In congested areas, blind spots or
insufficient camera angles might lead to missing incidents, jeopardising the system's
efficiency. Furthermore, the collecting and analysis of video data raises ethical concerns·
about public space surveillance, which may dissuade some users from using the system out
of concern for their privacy. Furthermore, while the framework intends to alert users about
irregular crowd behaviour, the mobile application's performance is dependent on rapid and
accurate data processing. If the server-side program experiences delays in detecting
anomalous behaviour or fails to analyse crowd data properly, it may result in false alarms
or missed warnings, weakening user trust. The study does not go into great detail about
these technical problems, nor does it provide a full review of the system's performance in
real-world circumstances. As a result, additional research is required to guarantee that the
suggested system not only works successfully, but also retains user confidence and
addresses ethical concerns during implementation.
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Summary
This transportation system transforms urban bus operations by integrating machine
learning, computer vision, and loT technologies. It dynamically optimizes routes, enhances
safety, and improves passenger experience by analyzing real-time traffic and passenger
data. The system prevents overcrowding, reducing travel times and congestion, while
promoting sustainability through reduced emissions and fuel consumption.
With a user-friendly mobile app and smart card-based digital ticketing, fare collection
becomes seamless, reducing delays and eliminating cash-based transactions. Passengers
.can access real-time updates on bus locations, arrival times, and seat availability, enhancing
their commute.
Unlike traditional static systems, this solution uses loT sensors and crowd detection to
ensure buses remain within safe capacity limits, improving safety and efficiency. Route
optimization algorithms adjust bus routes in real-time based on traffic patterns, road
conditions, and environmental factors, minimizing delays and fuel wastage.
Additionally, the system's data analytics provide insights for transport administrators,
enabling smarter decision-making and continuous improvement. This integrated approach
enhances urban transit, ensuring flexibility, safety, and sustainability for modern cities.
Objectives
• Implement a digital ticketing infrastructure that includes smart cards, mobile apps,
and the Internet of Things (loT) to transform public and private bus transit.
• Ensure that all payments are done electronically, preventing fare evasion and
corruption, while securely recording transactions on a decentralised ledger for
accountability.
• Provide private institutions with a tracking system that monitors real-time bus travel,
including live tracking, pickup and drop-off locations, and times.
• Monitor the status of bus fees for schools and colleges, thereby boosting the safety
and accountability of transportation services.
o Use real-time tracking to optimise bus routes and reduce delays through effective
route management, thereby improving public and institutional bus operations.
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• Eliminate cash transactions and manual procedures, enhancing transparency in
transportation systems.
• Use loT-based crowd monitoring to maintain safe passenger capacity, prevent
overcrowding, and raise safety standards.
• Support India's digital and smart city ambitions by improving serv1ce quality,
·operational efficiency, and reducing traffic congestion, thereby encouraging more
sustainable and dependable bus transportation systems.
Brief Description of the Drawing
Fig 1 : Block Diagram for Analysing Route Optimization using Route score
The flowchart Fig.J illustrates the bus route optimization process, integrating data
collection, route evaluation, and real-time communication using tht! Google Maps API and
Twilio API. The process begins with the start point, followed by data collection from the
Google Maps API, which includes map initialization and data loading. This data is then
processed to prepare for route analysis.
Next, the system checks for modifications in routes due to factors such as traffic or ongoing
construction. If modifications are needed, the process continues to label the optimized route
score. This score is calculated based on several parameters, including road construction
status, road closures, lteavy traffic conditions, road quality, accident rates, am/ otlter
relevant factors. The system utilizes these parameters to perform nested clustering,
allowing for a categorization of routes based on the calculated route scores.
If no modifications are required, the system permits the bus to continue traveling on the
same route. During the optimization process, the system calculates average scores of
clusters to finalize the optimized· route. Once the best route is determined, the new
·Optimized route is communicated to the drivers and checkers through the Twilio API. The
process concludes with the end point, ensuring an efficient and responsive bus routing
system that adapts to real-time conditions.
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Fig 2 : Usc case diagram of the proposed solution
The diagram in Fig.2 depicts a bus transportation system's workflow, featuring options for
both passenger and ad min roles. Passengers can log in to apply fore-tickets, check their ewallet
balance, track bus locations, view route scores, and monitor crowd counts. They can
also apply for an RFID pass and choose their route and ticket quantity. Admins can update
route scores, check GPS tracking and pass statuses, and manage ticket generation and ewallet
deductions. Both roles interact with a centralized database that siores and manages
all transactional and operational data.
Fig 3 : Circuit diagram for RFID connected with Arduino UNO
The image in Fig. 3 illustrates an Arduino Uno board connected to an RFID module. Colorcoded
wires indicate how each pin on the RFID module is connected to the corresponding
pins ·on the Arduino, facilitating corrimunication between the two devices for RFID data
reading and processing tasks. This setup is commonly used in projects for access control,
tracking, and security systems.
Connection of Arduino Uno to RFID-RC522:
• SDA (Pin 10 on Arduino) to SDA on RC522
• SCK (Pin 13 on Arduino) to SCK on RC522
• MOSI (Pin II on Arduino) to MOSI on RC522
• MISO (Pin 12 on Arduino) to MISO on RC522
• IRQ (not connected)
• GND (GND on Arduino) to GND on RC522
• RST (Pin 9 on Arduino) to RST on RC522
• VCC (5V on Arduino) to VCC on RC522
Output
When the RFID reader successfully scans an RFID tag (card or key fob), the output will
typically include:
• Card UID: The unique identifier of the RFID tag.
• Status Message: Indicating whether the scanning was successful or not
• Additional data, if the RFID tag has any stored data (e.g., balance or user
information) .
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Passive RFID technology is widely employed in private and public bus ticketing
systems to improve passenger safety and convenience. This system often uses
contactless RFID cards or key fobs, which passengers touch on RFID readers to
authenticate their tickets.
The RFID-RC522 module is a popular scanner in such applications because to its low
cost and high efficiency in scanning passive RFID tags. This module is linked into
ticketing systems for both private buses, such as those used in schools. and universities
to control student safety and attendance, and public bus systems that allow for cashless
transactions. Using this technology, both types of bus networks can assure safe
boarding, track ridership patterns, and improve overall safety while expediting fare
collection procedures.
Fig 4 : the Python code utilizing OpenCV for predicting the number of passengers in
the bus is implemented as part of the project focusing on counting people in buses.
The diagram illustrates a crowd detection system using OpenCV, specifically employing
the createBackgroundSubtractorMOG2 module to analyze live video feeds from inside a
bus. This setup processes video input to differentiate moving people from the background,
enabling accurate headcount monitoring. The processed video is shown in two formats:
I. Color Image with Bounding Boxes: This part of the interface shows the live feed
from the bus with detected individuals highlighted in green bounding boxes.
Movement tracking is visualized with lines (red for up and blue for down), helping
to understand the flow of movement inside the bus.
2. Binary Silhouette Image: On the right side, a binary view isolates moving figures
in white against a black background, a result of contour detection which simplifies
the scene to clearly identify and COI.)nt individuals.
This crowd detection data is crucial for maintaining optimal passenger levels. By counting
the number of people inside the bus and updating this information in real-time to a mobile
application, potential passengers can make informed decisions about whether to board the
bus based on current occupancy levels, improving passenger distribution and enhancing
overall travel comfort.
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Figure 5 : UI Interface of the Application
The images showcase a comprehensive mobile application interface developed usmg
Flutter, designed to enhance the user experience in bus transportation management. The
application features multiple screens that cater to various user needs, from login to ticket
booking and live tracking of buses.
Starting with a secure login screen, the app allows users to enter their credentials or sign
up for a new account, ensuring safe access to their personal and payment information. Once
logged in, users are greeted with a home screen that presents a suite of functionalities
including ticket generation, wallet management, ride history review, and access to help and
reporting features. This main menu is user-friendly and intuitively designed to facilitate
easy navigation.
For route selection and ticket booking, users can quickly view available bus routes, select
their desired timing, and view essential details such as the number of available seats and
the current crowd percentage inside the buses. This information helps in making an
informed decision about which bus to take, enhancing the commuting experience by
avoiding overcrowded buses.
The application also provides a real-time bus tracking feature, displayed on a map interface,
which allows users to track their ride lively, ensuring they can manage their time
efficiently. Additionally, for private bus services, particularly those used by schools, the
app includes safety location tracking for students and other essential information,
accessible through an admin page that helps inanage and monitor all the logistical aspects
of bus transportation.
Ticket booking is streamlined through an interface where users can confirm their ticket
with all pertinent details such as route, fare, and number of tickets displayed clearly. Upon
booking, an e-ticket is generated with a QR code, enhancing the ease of use at boarding
without the need for physical tickets. The app ensures that a copy of thee-ticket is securely
sent to the registered phone number, along with a pleasant message to enjoy the ride,
making the entire process seamless and user-friendly.
Overall, this mobile application acts as a robust tool for managing public and private bus
transportation, leveraging technology to improve safety, efficiency, and user satisfaction.
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Detailed Description of the Invention
The idea under consideration is a complete system that utilises technology to improve
public transportation. It encompasses both commercial institution-based transport services
and metropolitan bus networks. To enhance user experience, operational efficiency, and
passenger safety, it combines machine learning, real-time data analytics, loT sensors, and
mobile ·applications. With capabilities like crowd recognition and real-time .surveillance
for users of the transit system, the system, in its mature state, is also adaptable to individual
tracking for increased security within private institutions.
1. System Integration and Components:
a. Smartphone Apps and Smart Cards:
• Purpose: The goal is to expedite ticket sales, shorten boarding wait times, increase
transit effectiveness, and improve each user's ability to trace their journey .
. • Functionality: Via a mobile app, users may purchase tickets, view bus schedules,
follow the positions of buses in real time, and get. delays information. For
individuals who would rather use physical tokens, smart cards offer a convenient
substitute for fare collection and access.
• Integration: A central administration system that synchronises data, computes
fares, and guarantees transaction security is connected to both smart cards and
mobile apps. Parents can follow their children's arrival and departure from private
schools using real-time app notifications.
b. Algorithms for Machine Learning in Dynamic Route Optimisation:
• Algorithms Used: K-Means clustering and K-Nearest Neighbours (KNN)
regression are the algorithms that were used. The goal is to dynamically optimise
bus routes according to past trip data, roadworks, passenger demand, and traffic
conditions.
• Method: To recommend more effective routes, the system receives real-time data
from GPS and Internet of Things sensors. Delays are cut, fuel efficiency is
increased, and operating expenses are decreased.
e Private Institution Adaptation: Offers improved security measures, individualised
tracking, and bus routes that are optimised for private institutions.
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c. loT Deployment and Real-Time Data Analytics:
Sensors and devices include CCTV cameras for crowd surveillance, RFID scanners, GPS
trackers, traffic flow sensors, and environmental sensors for weather and air quality_
• Using Data: Long-term fleet and route management as well as on-the-spot service
operation adjustments are supported by real-time data gathered from loT devices.
This information guarantees a more effective and secure tracking system for
transportation users in private establishments.
2. Operational Modules:
a. Route Optimization Module:
• Functionality: This module optimises bus routes dynamically, cutting down on trip
times and fuel consumption by processing traffic updates, passenger data, and
sensor data. Benefits include higher passenger satisfaction, less delays, and more
operational efficiency_
• Private Use Case: This module allows real-time tracking of bus positions and
optimises bus routes for the safe and effective transportation of employees or pupils
in private institutions.
b. Module for Safety and Crowd Control:
• Technology: RFID tracking to track and analyse individual movements and crowd
density, and OpenCV for computer vision applications.
• Functionality: During peak hours, bus services are dynamically adjusted based on
the number of passengers to guarantee that buses don't go beyond safe capacity
restrictions.
• Private Use Case: With the system's specific tracking features, parents or
organisations may keep an eye on students' or workers' whereabouts and movements
in real time. In the event that crowd limitations are exceeded, alerts are generated,
and the system can reallocate resources to efficiently manage crowds.
c. Individual and Passenger Tracking Module:
• Components: Interactive features include feedback. and help choices within the
software, real-time notifications, and an easy-to-use UI.
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· • Improvements: offers a flawless travel experience, including real-time information
on crowd levels and bus timings. This module improves safety and accountability
for private. institutions by enabling parents or administrators to monitor individuals
entering and exiting transport services.
3. Scalability and Implementation:
a. Implementation in Phases:
• Pilot Testing: To test functionality and get user input, the system is first put into
use in a controlled setting.
• Rollout: Gradual extension to include private institutions and larger urban regions,
tailored to the needs of individual cities.
b. The ability to scale taking into account:
• Flexible Design: The modular architecture of the system guarantees adaptation in various
institutional and urban contexts, enabling the installation of new functions as required.
• Private Institutions: To provide improved tracking and safety, the system can be tailored
for use on corporate campuses, schools, or other private institutions.
4. Upcoming Improvements:
a. Enhanced Predictive Analysis
More sophisticated prediction models for route optimisation, crowd control, and transportation
demand forecasts will be incorporated into system updates.
b. Features for Enhanced Security:
There are plans to use more sophisticated Al-based tracking systems and biometric authentication
for bus boarding to further protect passenger security, particularly in private institutions.
Using real-time data, machine learning, and the Internet of things, this invention offers a
comprehensive, cutting-edge solution for the demands of both public and private transportation .
The result is optimised routes, improved safety, and a seamless user experience.

We Claim,
Claim [I]: A system and method for digital ticketing using mobile applications and smart
cards; integrated with loT technology, allowing passengers to purchase tickets for both
public and private buses via a platform developed using Flutter.
Claim [2]: As stated in Claim [I], the system incorporates real-time crowd detection within
buses through OpenCV technology, monitoring passenger density to ensure safety and
prevent buses from exceeding optimal capacity, especially during peak commuting hours.
Claim [3]: A hardware and software integration, as described in Claim [2], that enables bus·
location tracking, passenger load monitoring, and real-time updates on bus status,
accessible to both passengers and administrators using loT sensors and mobile interfaces.
Claim [4]: A method for route optimization that leverages real-time traffic data and
passenger load information to dynamically adjust bus routes, reducing delays and
enhancing operational efficiency for both public and private transportation networks.
Claim [5]: The system provides automated fare calculation based on the distance traveled,
using smart card data to minimize manual fare disputes and ensure transparent pricing
across both public and private bus networks.
Claim [6]: A method for providing real-time data analytics, as described in Claim [4], to
transport administrators, enabling them to analyze trends in passenger density, route
efficiency, and operational challenges, thereby supporting long-term improvements in bus
transportation systems.

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