RFID CHILD TRANSPORTATION MONITORING SYSTEM

WITH GPS TRACKING USING IOT

A Project Report
Submitted to the FACULTY of ENGINEERING of
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY, KAKINADA
In partial fulfillment of the requirements,
for the award of the Degree of
Bachelor of Technology
In
Internet of Things
By

T.SAI GANDHI M.GIREESH SAI

(21481A6057) (21481A6038)
C.NAGA BABU J.JASMITHA
(22485A6003) (21481A6018)
Under the Guidance of

Mr .CH.V.D.Ashok Kumar
Assistant professor

Department of Internet of Things

SESHADRI RAO GUDLAVALLERU ENGINEERING COLLEGE
(An Autonomous Institute with Permanent Affiliation to JNTUK, Kakinada)
SESHADRI RAO KNOWLEDGE VILLAGE
GUDLAVALLERU - 521356
ANDHRA PRADESH
2024-25

i
RFID CHILD TRANSPORTATION MONITORING SYSTEM
WITH GPS TRACKING USING IOT
A Project Report
Submitted to the FACULTY of ENGINEERING of
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY, KAKINADA
In partial fulfillment of the requirements,
for the award of the Degree of
Bachelor of Technology
in
Internet of Things

T.SAI GANDHI M.GIREESH SAI

(21481A6057) (21481A6038)
C.NAGA BABU J.JASMITHA
(22485A6003) (21481A6018)
Under the Guidance of

Mr .CH.V.D.Ashok Kumar
Assistant professor

Department of Internet of Things

SESHADRI RAO GUDLAVALLERU ENGINEERING COLLEGE
(An Autonomous Institute with Permanent Affiliation to JNTUK, Kakinada)
SESHADRI RAO KNOWLEDGE VILLAGE
GUDLAVALLERU – 521356
ANDHRA PRADESH
2024-25

ii
 Department of Internet of Things
SESHADRI RAO GUDLAVALLERU ENGINEERING COLLEGE
(An Autonomous Institute with Permanent Affiliation to JNTUK, Kakinada)
SESHADRI RAO KNOWLEDGE VILLAGE
GUDLAVALLERU – 521356

CERTIFICATE

This is to certify that the project report entitled “RFID CHILD TRANSPORTATION
MONITORING SYSTEM WITH GPS TRACKING USING IOT” is a bonafide record of work carried out
by T.SAI GANDHI (21481A6057), M. GIREESH SAI (21481A6038), C.NAGA BABU (22485A6003),
J.JASMITHA (21481A6018) under my guidance and supervision in partial fulfillment of the requirements, for
the award of the degree of Bachelor of Technology in Internet of Things of Seshadri Rao Gudlavalleru
Engineering affiliated to Jawaharlal Nehru Technological University, Kakinada.

(Mr.CH.V.D.Ashok Kumar) (Dr. Y.SYAMALA)

Project Guide Head of the Department

iii
 Acknowledgement
We are very glad to express our deep sense of gratitude to Mr.Ch.V.D.Ashok Kumar, Guide
designation, Electronics and Communication Engineering (and Co-guide name, designation and department in
case of Interdisciplinary Projects) for guidance and cooperation for completing this project. We convey our
heartfelt thanks to him for his inspiring assistance till the end of our project.

We convey our sincere and indebted thanks to our beloved Head of the Department Dr.Y.Syamala,
for his encouragement and help for completing our project successfully.

We also extend our gratitude to our Principal Dr.B.Karuna Kumar, for the support and for
providing facilities required for the completion of our project.

We impart our heartfelt gratitude to all the Lab Technicians for helping us in all aspects related to our
project.

We thank our friends and all others who rendered their help directly and indirectly to complete our
project

T.SAI GANDHI (21481A6057)

M.GIREESH SAI (21481A6038)

C.NAGA BABU (22485A6003)

J.JASMITHA (21481A6018)

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 CONTENTS

TITLE PAGE NO
LIST OF FIGURES iv
LIST OF TABLES v
NOMENCLATURE vi
ABSTRACT vii

CHAPTER 1
INTRODUCTION
1.1 Background 1
1.2 Aim of this Project 1
1.3 Methodology 2
1.4 Significance of this Work 2
1.5 Outline of this Report 2
1.6 Conclusion 3

CHAPTER 2
LITERATURE REVIEW 4

CHAPTER 3
SYSTEM ARCHITECTURE AND
IMPLEMENTATION

3.1 Analytical Modeling 6

3.2 Employment of Software Packages 7
3.3 Hardware Design 7
3.4 Experimental Verification 8
3.5 Flow Chart of System Architecture 9

CHAPTER 4
HARDWARE IMPLEMENTATION

5
 4.1 Block Diagram of RCTMS 11
4.2 Hardware Design of RCTMS Using IOT 12
4.3 Arduino 13
4.4 RFID Module 13
4.5 GPS Module 14
4.6 ESP32 Wifi Module 15
4.7 Arduino Compatable System 17
4.8 Additional Hardware Components

CHAPTER 5
SOFTWARE IMPLEMENTATION
5.1 Google colab 19
5.2 How to install Google colab 20
5.3 Implementation in Google colab 21
5.3.1 Opening Google colab 21
5.3.2 Writing Python Script(.py) 22
5.3.3 Exexcuting Code in Google colab 23
CHAPTER 6
RESULTS
6.1 Video Capturing Using Camera Module 27
6.2 Frame Extraction 28
6.3 License Plate Detection 29
6.4 Cropping Detected License Plates 29
6.5 OCR & Data Retrieval 30

CHAPTER 7
CONCLUSION AND FUTURE SCOPE
7.1 Conclusion 32
7.2 The Future Scope 32
7.3 Advantages 33
7.4 Disadvantages 33

BIBLIOGRAPHY 34

Project Outcomes Mapped With Programme 36

5
Specific Outcomes And Programme Outcomes 36

APPENDIX A 39

APPENDIX B 42

5
 LIST OF FIGURES

FIG NO NAME OF THE FIGURE PAGE NO

3.1 Flow Chart of ANPD & DB Updation Using IoT 10
4.1 Block diagram of ANPD&DB updation using IoT 12

4.3 Raspberry Pi 13
4.4 Camera Module 14
4.5 Memory Card 15
4.6 USB Type-c 16
5.1 Google colab Interface 22
5.2 Python Script in Google colab 23
5.3 Video acquisition 24
5.4 Frame Extraction 24
5.5 License Plate Detection 25
5.6 OCR 25
6.1 Day-time VS Night-time Video Capturing 28
6.3 License Plate Detection 29
6.4 Cropping Detected License Plate 30

5
 LIST OF TABLES

TABLE NO NAME OF THE TABLE PAGE NO

4.1 List of supported Operating Systems 22

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NOMENCLATURE

OCR – Optical Character Recognition

AI – Artificial Intelligence
API – Application Programming
Interface
ML – Machine Learning
LandingAI – AI framework used for license
plate detection
gdown – Google Drive file downloader
IPython – Interactive Python shell
VideoFile – Class used for processing video
files in LandingAI
Predictor – Model used for license plate
Detection
Overlay_predictions – Function to overlay detection
results on images
crop – Function to extract detected
license plate regions from
images
OcrPredictor – Class used for performing OCR
on images
Bounding Box – A rectangular region marking the
detected license plate
Frame Sampling – Extracting specific frames from a
video at regular intervals
Motion Blur – Image distortion caused by fast-
moving objects in video frames

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ABSTRACT

Child safety during transportation is a critical concern for parents and schools. This project
proposes an RFID-based Child Transportation System using Arduino, which ensures secure
boarding, real-time tracking, and emergency response mechanisms. The system incorporates an
RC522 RFID reader, which is used to authenticate children while boarding and deboarding the
vehicle. Each child is provided with an RFID card, and when scanned, the system records their
entry and exit, sending the information to parents or school authorities via an IoT-based cloud
platform like ThingSpeak, Firebase, or Blynk.
For vehicle control, the system includes a joystick-controlled robot that aids in maneuvering the
transport vehicle in specific conditions. Additionally, an emergency panic button is integrated to
allow children or supervisors to trigger an alert in case of distress, ensuring quick response in
emergencies. The system also features an accident detection mechanism using ADXL345
accelerometer and vibration sensors, which detects any unusual impact or crash. Upon detecting
an accident, the system automatically sends an SMS alert along with the vehicle’s GPS location
to predefined emergency contacts using a GSM module.
The Arduino Uno/Mega acts as the central controller, processing data from RFID, GPS, GSM,
panic button, and sensors to ensure a seamless and efficient child monitoring system. The LCD
display shows real-time status updates regarding the child’s transportation, while buzzer and
LED indicators provide immediate alerts. By integrating IoT, automation, and real-time tracking,
this system enhances the security, efficiency, and reliability of child transportation. In the future,
AI-based predictive analytics, facial recognition, and automated vehicle control can be
incorporated to further improve safety and efficiency in school transportation systems. This
project provides a cost-effective, scalable, and technology-driven approach to ensuring child
safety in school transport vehicles.

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CHAPTER -1
INTRODUCTION
1.1 Background

The safety and security of children during transportation to and from school have become a
significant concern for parents and educational institutions. Traditional methods of monitoring
school buses and students are often inefficient, leading to safety risks such as unauthorized
pickups, route deviations, and accidents. With advancements in technology, integrating RFID
(Radio Frequency Identification) and GPS (Global Positioning System) tracking through IoT
(Internet of Things) provides a robust solution to ensure the real-time safety of children during
transit.

RFID technology enables automatic identification of students when they board or exit the school
bus, ensuring accurate attendance tracking. GPS tracking provides real-time location updates of
the bus, allowing parents and school administrators to monitor its movement. IoT connectivity
ensures seamless data transmission to cloud servers, enabling instant notifications and alerts. By
implementing this intelligent system, transportation safety can be significantly improved,
reducing parental concerns and enhancing operational efficiency in schools.

This project focuses on designing and developing an integrated RFID and GPS-based
transportation monitoring system that ensures child safety, transparency, and effective
management. By utilizing modern IoT techniques, this system not only enhances security but
also improves communication between parents, drivers, and school authorities.

1.2 Aim of the Project

The aim of this project is to develop an RFID and GPS-based child transportation
monitoring system using IoT to ensure student safety during transit. The system is designed to
provide real-time tracking, automated attendance monitoring, and instant notifications to parents
and school authorities. By integrating RFID for student identification and GPS for bus tracking,
the project aims to enhance the security and transparency of school transportation services.
Additionally, the system will include emergency alert mechanisms to address unforeseen
situations, ensuring a quick response from authorities. The use of cloud-based IoT technology
enables seamless data transmission, allowing stakeholders to monitor transportation activities
remotely. This project ultimately aims to minimize risks associated with student transportation
and provide a reliable, efficient, and scalable solution for educational institutions.

1.3 Methodology
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The methodology adopted in this project involves the integration of hardware, software,
and cloud-based IoT solutions to develop an efficient child transportation monitoring system.
The first phase includes conducting research to analyze existing safety concerns and identifying
key requirements for the system. Next, the system is designed by incorporating essential
hardware components such as an RFID reader, GPS module, and IoT-enabled microcontroller
(e.g., ESP32, Raspberry Pi, or Arduino) to ensure accurate student identification and real-time
tracking. The software development phase focuses on implementing a cloud-based dashboard to
process and display transportation data while enabling secure data storage and transmission
through Wi-Fi or GSM modules.

Following system development, rigorous testing is conducted to verify data accuracy, GPS
precision, and RFID efficiency under real-world conditions. The system is then deployed in a
school environment for practical evaluation, ensuring it functions effectively in tracking student
movement and bus routes. Data collected during implementation is analyzed for performance
optimization, refining the system for enhanced accuracy and reliability. By employing this
structured methodology, the project aims to create a seamless, real-time monitoring system that
ensures maximum safety for school children during transportation.

1.4 Significance of this work:

The significance of this project lies in its ability to enhance child safety, improve
transportation efficiency, and facilitate real-time communication between stakeholders. By
utilizing RFID, GPS, and IoT technologies, the system ensures that students are accounted for
during transit, reducing risks associated with missing children or unauthorized drop-offs. The
real-time tracking feature allows parents to monitor their child’s journey, providing them with
peace of mind and reducing anxiety regarding transportation safety. Additionally, schools and
transport authorities benefit from improved route management, optimized resource allocation,
and automated attendance tracking, leading to increased efficiency and reduced operational
errors.
Moreover, the system introduces an alert mechanism for emergency situations, ensuring swift
responses from authorities in case of accidents or route deviations. The ability to store and
analyze transportation data enables schools to generate reports, track bus performance, and
implement data-driven improvements. This project not only provides a scalable and cost-
effective solution for school transportation safety but also sets a precedent for future
advancements in intelligent transport monitoring systems. The combination of technology-driven
safety measures makes this work a crucial step toward modernizing and securing student
transportation infrastructure.

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1.5 Outline of this Report

 Chapter 1: deals with Introduction

 Chapter 2: deals with Literature Review
 Chapter 3: deals with Work Title Explanation
 Chapter 4: deals with System Implementation
 Chapter 5: deals with Data Processing and Alert Mechanism
 Chapter 6: deals with Results and Discussion
 Chapter 7: deals with Conclusion and Future Work

1.6 Conclusion
Ensuring safe and secure transportation for school children is a priority for both parents
and educational institutions. This project introduces an innovative solution by integrating RFID,
GPS, and IoT to monitor child transportation in real time. The system ensures accurate
attendance tracking, real-time location monitoring, instant alerts, and emergency response
mechanisms, making school transportation more reliable and secure.
By implementing this system, schools can enhance their transportation services, parents can have
peace of mind, and children can travel safely. This project lays a foundation for a more
technologically advanced and intelligent transportation monitoring system, which can be
expanded further to include AI-based predictive analytics, facial recognition, and advanced route
optimization in future developments.

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CHAPTER 2
Literature Review
The increasing demand for child safety during school transportation has led to extensive
research and technological advancements in the field of RFID, GPS tracking, and IoT-based
monitoring systems. Various studies have explored different approaches to enhancing the
security and efficiency of school transportation, integrating real-time tracking, automated
identification, and emergency alert systems. Several research papers have highlighted the
benefits of RFID-based student monitoring systems. A study by Garg et al. (2017) demonstrated
how RFID technology could be used to track student attendance on school buses, ensuring that
each child is accounted for at every stage of the journey. Another study by Kumar and Sharma
(2019) discussed the integration of RFID with cloud-based systems for real-time monitoring and
data storage, allowing parents and school authorities to access transportation data remotely.

In addition, multiple studies have focused on GPS-based vehicle tracking systems for school
buses. Research by Ahmed et al. (2018) emphasized the significance of GPS in ensuring real-
time location tracking, route optimization, and emergency response mechanisms. The study also
suggested that integrating GPS with GSM-based communication could further enhance safety by
sending alerts to parents and school administrators in case of unexpected route deviations or
delays.
Several commercial tracking solutions have been implemented globally. For instance, in 2015,
schools in Singapore started adopting GPS-enabled bus tracking systems that provided real-time
updates to parents. Similarly, in 2018, educational institutions in the United States began
implementing RFID-based attendance tracking to ensure student safety during school commutes.
A notable example is India’s Safe Transport Initiative (2020), which implemented a nationwide
RFID-GPS monitoring system for school buses.
This initiative helped improve route planning, real-time student tracking, and emergency alert
mechanisms. Additionally, countries like Germany and the UK have implemented smart bus
tracking systems in urban areas, allowing for safer and more efficient school transportation.With
the evolution of Artificial Intelligence (AI) and Machine Learning (ML), modern school bus
monitoring systems are advancing beyond traditional tracking. Researchers in 2021 proposed
integrating AI-based predictive analytics into RFID-GPS tracking, allowing systems to predict
delays, identify traffic congestion, and suggest alternate routes dynamically.
A study by Lee et al. (2022) suggested incorporating facial recognition with RFID tracking to
further improve student authentication, reducing the risks of identity fraud and unauthorized
pickups. Similarly, in 2023, researchers introduced blockchain-based secure transportation data
storage, ensuring tamper-proof records of student travel data. Moreover, recent developments in
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5G technology and edge computing have allowed for faster data transmission in real-time
tracking systems. The use of low-power wide-area networks (LPWANs) enables cost-effective,
long-range communication for rural schools, making RFID-GPS tracking accessible even in
remote areas. Several IoT-based smart school bus systems have been piloted in China and South
Korea (2023), utilizing automated emergency braking, collision detection, and vehicle
diagnostics to improve school transportation safety. These systems provide not only student
monitoring but also driver behavior analysis to prevent reckless driving and ensure adherence to
traffic regulations.
The literature review highlights the evolution of RFID, GPS, and IoT-based child transportation
monitoring systems, emphasizing their role in enhancing student safety. Existing
implementations across Singapore, the US, India, Germany, and the UK demonstrate the
effectiveness of such technologies in real-world applications.
Further advancements in AI, blockchain, and 5G connectivity continue to push the boundaries of
intelligent transportation systems, ensuring that future implementations will be even more
secure, efficient, and scalable. By understanding these advancements and integrating emerging
technologies, this project aims to contribute to the next generation of smart school transportation
monitoring systems, making travel safer and more reliable for students worldwide.
The literature review highlights the evolution of RFID, GPS, and IoT-based child transportation
monitoring systems, emphasizing their role in enhancing student safety. Existing
implementations across Singapore, the US, India, Germany, and the UK demonstrate the
effectiveness of such technologies in real-world applications. Further advancements in AI,
blockchain, and 5G connectivity continue to push the boundaries of intelligent transportation
systems, ensuring that future implementations will be even more secure, efficient, and scalable.
By understanding these advancements and integrating emerging technologies, this project aims
to contribute to the next generation of smart school transportation monitoring systems, making
travel safer and more reliable for students worldwide.
Future research is likely to focus on integrating autonomous vehicle technologies with school
bus systems, using advanced AI-driven navigation, and ensuring real-time risk assessment to
prevent accidents. Additionally, the rise of smart city infrastructures will play a crucial role in
developing next-generation transportation solutions that provide seamless connectivity between
buses, schools, and parental monitoring platforms.

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CHAPTER 3
SYSTEM ARCHITECTURE AND IMPLEMENTATION
The design architecture of the RFID and GPS-based child transportation monitoring system plays
a crucial role in ensuring the safety, security, and efficient tracking of students during their
transit. The system integrates various components, including RFID readers, GPS modules, cloud-
based databases, and IoT communication networks, to create a real-time, automated tracking and
notification system. The main objective of this architecture is to provide seamless data collection,
processing, and transmission to relevant stakeholders, such as parents and school administrators.
The integration of these technologies ensures that students are accounted for at all times,
reducing the risks associated with school transportation.
The proposed design consists of both hardware and software components working in
synchronization. The hardware component includes RFID readers installed on buses, RFID tags
embedded in student ID cards, GPS modules for location tracking, and microcontrollers for data
processing. These components work together to detect when a student boards or exits the bus and
to track the bus’s real-time location. The collected data is then transmitted to a cloud-based
system, where it is processed and stored securely. The software architecture involves the
development of web and mobile applications that provide real-time tracking updates,
notifications, and emergency alerts to parents and school authorities.

3.1 Analytical Modeling

Analytical modeling forms the foundation of the proposed system by defining the
mathematical and logical framework for its operation. The system is modeled as a real-time
embedded system that continuously collects, processes, and transmits data. The RFID module is
responsible for student authentication, while the GPS module ensures location tracking. The IoT
gateway facilitates communication between hardware components and the cloud storage. The
analytical model also considers system performance metrics such as data transmission latency,
accuracy of student identification, and reliability of GPS tracking. These parameters are
optimized to ensure seamless operation and minimal errors in tracking and reporting student
movements.
1. Data Acquisition – RFID tags and GPS modules collect real-time data on student entry,
exit, and bus location.
2. Data Processing – Microcontrollers process raw data, filtering errors and ensuring
accuracy before transmission.

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3. Cloud Integration – Processed data is transmitted to cloud storage using IoT

communication protocols.
4. User Access & Alerts – The cloud system sends real-time updates and alerts to parents
and school authorities via mobile applications.

3.2. Employment of Software Packages

The software backbone of the system includes multiple programming environments and
platforms. Embedded C or Python is used for microcontroller programming, enabling interaction
between the RFID reader, GPS module, and communication gateways. Cloud-based database
solutions like Firebase or MySQL store transportation data, allowing remote access. The mobile
and web applications are developed using frameworks such as React Native or Flutter, providing
an interactive interface for parents and school administrators. Additionally, IoT protocols such as
MQTT and HTTP are employed to ensure efficient data transmission between sensors and cloud
storage.
Key Software Components:
1. Microcontroller Programming: The embedded software is written in C or Python to
process RFID and GPS data.
2. Cloud Database Management: Firebase or MySQL is used to securely store student
transportation data.
3. Mobile and Web Development: React Native or Flutter ensures cross-platform
accessibility for real-time tracking.
4. IoT Communication Protocols: MQTT and HTTP facilitate seamless data transmission
from devices to cloud storage.
5. Security and Encryption: Secure Socket Layer (SSL) and AES encryption protect
sensitive student data from cyber threats.

3.3 Hardware Design

The system’s hardware architecture consists of multiple interconnected components to
ensure seamless operation. The five key elements of hardware design are:

1. RFID Module: The RFID readers and tags are crucial components for student
authentication. Each student is assigned an RFID tag embedded in their ID card, which

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gets scanned by the RFID reader installed in the school bus. This ensures automatic
attendance marking and real-time tracking of student movement.
2. GPS Tracking System: A GPS module is integrated into the system to provide accurate
real-time location tracking of the school bus. This allows parents and school
administrators to monitor the vehicle’s movement and estimated arrival times, ensuring
better route management and safety.
3. Microcontroller and Processing Unit: Devices such as Arduino, ESP32, or Raspberry
Pi act as the brain of the system, processing data from the RFID readers and GPS module.
These microcontrollers ensure seamless communication between hardware components
and transmit the data to cloud storage for further processing.
4. Communication Modules: The system employs GSM, Wi-Fi, or LPWAN (Low Power
Wide Area Network) modules to ensure reliable data transmission between the bus and
cloud storage. These modules facilitate real-time updates and alerts for parents and school
authorities.
5. Power Supply and Backup System: The entire system relies on a stable power supply
with battery backup solutions to prevent data loss or interruptions. Solar-powered backup
options can also be integrated to enhance system sustainability and reduce reliance on
external power sources.

3.4. Experimental Verification

The system undergoes rigorous testing to ensure its reliability and efficiency in real-
world scenarios. Experimental verification includes:
1. Functionality Testing: The RFID and GPS modules are tested to ensure they accurately
capture and transmit student location data without errors.
2. Latency Analysis: The time taken for data transmission from the IoT gateway to the
cloud server is measured and optimized for real-time performance.
3. Accuracy Evaluation: Real-time GPS tracking data is compared with actual bus
movements to verify location precision and reliability.
4. Security and Data Integrity Testing: Encryption methods and security protocols are
tested to prevent unauthorized access and data breaches.
5. User Experience Testing: Parents and school administrators evaluate the usability of the
mobile and web applications, ensuring an intuitive interface and efficient access to
student tracking information.

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3.5 Flowchart
The system ensures real-time tracking, student authentication, and emergency management.
Below is the step-by-step explanation of the design architecture:
1. Start – System Initialization
 The system starts when the bus ignition is turned on.
 All connected devices, including the RFID reader, GPS module, and IoT communication
system, are initialized.
 The system continuously waits for an RFID input when a student boards the bus.
2. Check RFID Card
 When a student enters the bus, they tap their RFID card on the RFID reader.
 The reader extracts the Unique Identification (UID) number from the card.
 This step is crucial for verifying the student's identity and logging their entry.
3. Read UID and Compare
 The extracted UID is compared with the database stored in the cloud or onboard memory.
 The system verifies whether the UID matches a registered student.
 If a match is found, the process moves forward. If no match is found, an alert is
generated.
4. Match Found? (Decision Step)
 If YES → The system proceeds with GPS tracking and data logging.
 If NO → The system loops back to wait for the next RFID scan and may trigger an
unauthorized access alert.
5. Read GPS Location
 The GPS module continuously updates the real-time location of the bus.
 Latitude and longitude data are captured and stored.
 This step ensures that parents and school authorities can track the live location.
6. Send Data to ThingSpeak (Cloud Server)

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 The verified RFID data and GPS location are sent to a cloud platform such as
ThingSpeak or Firebase.
 Data transmission occurs over IoT communication protocols like MQTT or HTTP.
 The cloud processes the data and updates the mobile or web application for tracking
purposes.
7. Check for Emergency Situations
 The system continuously monitors for emergency conditions, such as:
o Unauthorized boarding attempts (unregistered RFID detected).

o Route deviations (bus moves away from the expected path).

o Emergency buttons pressed by students or driver.

 If an emergency is detected, an alert notification is sent to parents and school authorities.

8.End – Data Processing Completed
 After logging student data and tracking bus movements, the system continues monitoring
for new RFID scans.
 The process repeats for every student boarding the bus, ensuring real-time monitoring
and security.

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Fig 3.1 : Flowchart of System Architecture and Implementation

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CHAPTER 4
HARDWARE IMPLEMENTATION
The hardware implementation of the RFID Child Transportation Monitoring System
with GPS Tracking Using IoT involves integrating various components to ensure efficient
operation. The system is designed to enhance the safety and security of students by providing
real-time tracking and authentication using RFID and GPS technology. Arduino serves as the
central microcontroller, enabling seamless communication between different hardware modules.

This chapter focuses on the selection, functionality, and integration of the hardware components
used in the system. Key elements include the Arduino Uno, RFID module for student
authentication, GPS module for real-time tracking, and IoT communication module for data
transmission. The chapter also covers power management, memory utilization, and input/output
interfacing to provide a complete understanding of the system's hardware architecture.

4.1 Block Diagram RCTMS

The Block diagram illustrates the hardware architecture of an RFID Child Transportation
Monitoring System with GPS Tracking Using IoT. At the core of the system is the Arduino Uno,
which acts as the central controller, interfacing with various input and output devices. Inputs
include an RFID reader for student authentication, an ADXL345 accelerometer for motion
sensing, a joystick for manual control, and a panic button for emergencies.
Additionally, a GPS module provides real-time location tracking, while an ESP8266 Wi-Fi
module facilitates IoT connectivity by transmitting data to the cloud for remote access by users.
The GSM module serves as an alternative communication method for sending alerts via SMS.On
the output side, the system features a 16×2 LCD display for real-time data visualization, a buzzer
for audio notifications, and a motor driver controlling the movement of motors.
The power supply unit ensures stable voltage delivery to all components. The entire setup
enables real-time monitoring of student transportation, ensuring their safety through continuous
location tracking and RFID-based authentication. The integration of IoT allows parents and
school authorities to access live updates via the cloud, enhancing transparency and security in
school transport systems.

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Fig 4.1 : Block Diagram of RCTMS

4.2 Hardware Design

The hardware design of the RFID Child Transportation Monitoring System with GPS
Tracking Using IoT consists of various hardware components that are required for the
implementation of the project. These components ensure efficient operation and seamless
communication between different modules to enhance the safety and security of students during
transportation.
The system is built around the Arduino Uno microcontroller, which acts as the central processing
unit. It integrates multiple hardware elements such as an RFID reader for student authentication,
a GPS module for real-time tracking, and an IoT communication module for data transmission.

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These components work together to provide an automated, accurate, and secure transportation
monitoring system.
The power supply unit ensures stable voltage regulation to all connected modules, preventing
performance fluctuations. Additionally, input devices like the joystick and panic button provide
manual control and emergency alert functionalities, ensuring safety features are well
implemented. Output devices, such as the LCD display and buzzer, enhance system interactivity
and provide real-time feedback to users.
The hardware design also incorporates wireless communication technologies, including GSM
and Wi-Fi modules, to facilitate real-time data transfer to the cloud. This ensures that school
administrators and parents have continuous access to student transportation data through a web
or mobile interface. The seamless connectivity between hardware components is essential for the
efficient functioning of the monitoring system.
This section provides an overview of the essential hardware elements used in the system. The
following subheadings elaborate on each component, including Arduino Uno, RFID module,
GPS module, IoT communication module, power supply, memory utilization, and input/output
interfacing. Understanding these components helps in comprehending the complete hardware
architecture of the system.

4.3 Arduino UNO

Arduino is an open-source microcontroller platform that provides a cost-effective and flexible
solution for embedded systems. It is widely used for IoT applications due to its cross-platform
compatibility, ease of programming, and robust community support. With multiple digital and
analog I/O pins, Arduino can easily interface with sensors, actuators, and communication
modules.
In this system, Arduino plays a crucial role in processing RFID-based student authentication and
GPS tracking data. It receives inputs from the RFID reader to log students’ entries and exits from
the vehicle, while simultaneously fetching GPS location data. The data is processed and
transmitted to a cloud server using an IoT communication module, ensuring real-time monitoring
by parents and school authorities.

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Fig 4.3 : Arduino UNO

4.4 RFID Module

RFID technology is employed in the system to ensure secure student authentication. Each
child is assigned an RFID tag, which contains a unique identification number. The RFID reader,
connected to Arduino, captures this data when the tag is scanned, allowing the system to log
student entries and exits automatically.
The RFID module operates on serial communication, transferring data to Arduino for processing.
Once the student data is verified, the system updates the attendance records and transmits the
information to the cloud. This automation eliminates manual errors and ensures an accurate
monitoring mechanism.
RFID technology also improves security by preventing unauthorized access to the vehicle. The
RFID reader can be programmed to trigger an alert if an unregistered card is detected, thereby
notifying authorities of potential security breaches. This feature enhances overall student safety
during transit..

Fig 4.4 : RFID Module

4.5 GPS Module

The GPS module integrated into the system continuously retrieves real-time location
coordinates of the school vehicle. The module communicates with Arduino using serial protocol
and provides latitude, longitude, and timestamp data. This information is crucial for tracking the
vehicle’s route and ensuring student safety.

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The processed GPS data is transmitted via an IoT module to a cloud platform, allowing parents
and administrators to monitor the vehicle’s movement. The GPS tracking system ensures timely
alerts in case of route deviations or unexpected delays, enhancing transportation security.
The GPS module also provides geofencing capabilities, where predefined safe zones can be set.
If the vehicle deviates from these zones, an alert is sent to the concerned authorities. This ensures
that unauthorized changes in route are detected, preventing potential risks to students.

Fig 4.5 GPS Module

Apart from running the software environment, the memory card is also responsible for
storing real-time captured data from the camera module. Since number plate detection involves
processing high-resolution images or video frames, significant storage space is required to save
snapshots of detected license plates for further analysis or record-keeping. In offline mode,
where internet connectivity may not always be available, the memory card ensures that data is
locally saved before being transmitted to a cloud database or external server when a connection
is re-established. Choosing a high-speed memory card with Class 10 or higher ratings ensures
smooth processing, quick read/write operations, and efficient handling of large datasets without
causing delays in real-time detection.

4.6 Esp8266 WiFi module

The IoT communication module (Wi-Fi/GSM) enables real-time transmission of RFID
and GPS data to a cloud-based server. This ensures that parents and school authorities can access
live location tracking and attendance records via a web interface or mobile application.
The IoT module operates on standard communication protocols such as MQTT or HTTP,
ensuring seamless data exchange. The integration of IoT not only enhances system efficiency but
also provides a scalable solution for future enhancements, such as emergency alerts and
predictive analytics.

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IoT-based connectivity allows for remote system monitoring and troubleshooting, minimizing
downtime. Additionally, cloud storage ensures that historical data is maintained for future
analysis, helping to improve transportation efficiency and security measures.

 Fig 4.6 : Esp8266 WiFi module

The ESP8266 WiFi module is a low-cost, efficient wireless communication module that
enables IoT connectivity. It allows the system to transmit real-time RFID and GPS data to a
cloud-based server, making it accessible to parents and school authorities through a web or
mobile application.
The module operates on standard WiFi protocols and supports TCP/IP communication, ensuring
reliable data transfer. It connects seamlessly with the Arduino Uno via UART communication,
allowing real-time synchronization of transportation data. This helps in monitoring student
movement and ensures timely updates.

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4.7 Arduino Compatable System

Distribution Type Memoryfootprint Packages

Arduino IDE Cross-platform ~200 MB 8,700

PlatformIO Cross-platform ~500 MB
SimulIDE Linux/window/Mac ~50 MB 35,000+
ARMHF
CodeBlocks + AVR Linux/Windows ~100 MB 20,000+
Atmel Studio Windows ~ 400 MB 16,464?
Eclipse + AVR Cross-platform ~23 MB
Plugin
Arduino Web Editor Cloud-Based ~20 MB 144
Embitz Windows 20,000+
MPLAB X IDE Cross-platform ~20 MB 160
Linux/Windows/Mac ~34 MB + ~320 (core)
Arduino CLI
XBMC
Makefile + AVR- Linux ~20 MB (core) +
GCC Raspbian
Repositories
Visual Studio Code Cross-platform ~90 MB 35,000+
+Arduino Plugin
kiCad + AVR sim Linux/window/Mac 28 MB (inc. 6300
X11)
OpenWRT Linux 3,3MB 3358
TinyGo(For Arduino) Linux_3.6.11
&SystemD
PwnPi Linux 20,000+
QtonPi Linux
VPNbian Linux ~40 MB 35,000+
w/o desktop
Raspbian Linux ~30 MB 35,000+
w/o desktop

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4.7 Additional Hardware Components:

1.Panic Button
A panic button is an emergency switch used to trigger an alert in critical situations.
In this project, the panic button allows students or drivers to send an immediate
distress signal in case of emergencies. When pressed, it activates an alert system,
notifying parents and school authorities via IoT communication.
2.Collision Sensor
A collision sensor detects obstacles or sudden impacts, ensuring safety in
automated vehicles. In this project, it helps prevent accidents by detecting nearby
objects and sending signals to the microcontroller to take appropriate actions, such
as stopping the vehicle or triggering an alarm.
3.RFID Reader
The RFID reader is used for student authentication in the system. Each student is
given an RFID tag, which, when scanned by the reader, records their entry and exit
from the vehicle. This data is then transmitted to the cloud for real-time monitoring
by parents and school authorities.
4.16×2 LCD
The 16×2 LCD display is used for showing real-time information such as student
authentication status, GPS location, and system alerts. It provides visual feedback
to the user, ensuring clear and efficient communication between the system and the
operator.
5.Buzzer
The buzzer is an audio output device used to generate alerts and notifications. It is
triggered in situations such as unauthorized RFID card detection, emergency alerts,
or system errors. The buzzer ensures that important alerts are immediately
noticeable.
6.GSM Module
The GSM module enables communication between the transportation system and
external users through SMS or calls. It is used to send alerts, GPS locations, and
emergency messages to parents or school authorities, ensuring real-time
connectivity.

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CHAPTER 5
SOFTWARE IMPLEMENTATION
The implementation of software in an RFID-based child transportation monitoring system
with GPS tracking using IoT is critical for ensuring seamless operation and security. The system
integrates various software components to facilitate real-time monitoring, data processing, and
alert mechanisms. By utilizing IoT protocols and cloud-based storage, the software ensures
efficient data communication between different hardware modules and end-users, enhancing
overall safety and reliability.
The primary objective of this software implementation is to automate and streamline the process
of student tracking using RFID technology while ensuring accurate location updates via GPS.
The software is responsible for authenticating students as they board and exit the bus, storing
relevant data, and transmitting this information to a cloud platform for further processing.
Additionally, it enables real-time tracking and immediate notifications in case of any deviations
or emergencies.
A well-structured software design is necessary to integrate multiple layers, including data
acquisition, processing, communication, storage, and user interface. The RFID readers and GPS
modules must work in sync with the backend processing unit to ensure data accuracy and
reliability. Furthermore, the system must be scalable to accommodate a large number of students
and buses while maintaining security and performance.
This chapter provides a comprehensive overview of the software architecture, RFID data
processing, GPS tracking, IoT-based communication, cloud storage, and user interface
development. Each section highlights the role of different software components in the system
and their significance in achieving a seamless and effective child transportation monitoring
solution.

5.1 Arduino IDE

The Arduino Integrated Development Environment (IDE) is a versatile software platform
used for writing, compiling, and uploading code to microcontroller-based hardware such as
Arduino boards. It provides an intuitive user interface equipped with essential tools, including a
text editor, compiler, serial monitor, and a comprehensive library manager. The IDE allows
developers to write sketches in C/C++ and supports various libraries that simplify hardware
communication, making it an essential tool for embedded system development. Its cross-
platform compatibility ensures that developers can work on Windows, macOS, and Linux
systems without limitations.
In the context of the RFID-based child transportation monitoring system with GPS tracking, the
Arduino IDE plays a crucial role in programming and configuring the system's microcontroller.
It is used to develop and upload code that manages RFID authentication, GPS tracking, and IoT

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communication. The IDE enables seamless integration of multiple hardware modules, including
RFID readers, GPS modules, and wireless communication units, ensuring that data is collected,
processed, and transmitted efficiently. Additionally, the serial monitor feature of the IDE is
utilized for real-time debugging, allowing developers to monitor sensor outputs, troubleshoot
errors, and fine-tune system performance.
The implementation of the Arduino IDE in this project follows a structured approach. Developers
begin by installing the IDE and selecting the appropriate board and libraries. They then write
code to handle RFID tag detection, GPS location updates, and IoT-based data transmission. Once
the sketch is compiled and uploaded to the microcontroller, rigorous testing and debugging are
performed using the serial monitor to ensure system reliability. The availability of built-in
libraries, such as those for GPS and RFID communication, simplifies the coding process and
enhances the overall efficiency of the system, making the Arduino IDE an indispensable tool in
this project.

5.2 How to install Arduino IDE

1. Download Arduino IDE
 Visit the official Arduino website (https://www.arduino.cc).
 Navigate to the Software section and select Arduino IDE.
 Choose the Windows version (Installer or ZIP file).
2. Install Arduino IDE
 If using the Installer version, run the downloaded .exe file.
 Accept the license agreement and select the installation directory.
 Click Install and wait for the process to complete.
 If using the ZIP version, extract files to a preferred location.
3. Install Device Drivers
 During installation, ensure that USB driver installation is selected.
 If the Arduino board is not detected, manually install drivers via Device Manager.
 Navigate to Ports (COM & LPT) and verify if the Arduino board is listed.
4. Connect the Arduino Board
 Use a USB cable to connect the Arduino board to the laptop.
 Open Device Manager and check under Ports (COM & LPT).

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 If the board is not recognized, reinstall drivers or try a different USB port.
5. Configure the Arduino IDE
 Open the Arduino IDE and configure the settings:
o Select the correct board model (e.g., Arduino Uno, Mega, Nano) under Tools >
Board.
o Choose the assigned COM port under Tools > Port.

o Ensure the correct programmer is selected (default: AVRISP mkII).

6. Verify and Upload a Test Sketch

 Open File > Examples > Basics > Blink.
 Click the Verify button (✔) to check for errors.

 Click Upload (→) to transfer the code to the board.

 If successful, the onboard LED should start blinking.

5.3 Implementation of Arduino IDE

The Arduino IDE plays a crucial role in implementing the software for the RFID-based
child transportation monitoring system. It provides an intuitive environment for coding,
compiling, and uploading programs to the microcontroller. The IDE facilitates seamless
integration of RFID readers, GPS modules, and IoT communication protocols, ensuring efficient
data processing and transmission. With its built-in libraries and debugging tools, developers can
streamline the implementation and testing of system functionalities.
5.3.1 Arduino IDE: Initial Setup
This is the Arduino IDE once it’s been opened. It opens into a blank sketch where you can start
programming immediately. First, we should configure the board and port settings to allow us to
upload code. Connect your Arduino board to the PC via the USB cable.
1. When you open the Arduino IDE, it starts with a blank sketch, ready for writing code.
The interface consists of a text editor, message console, and toolbar buttons for
compiling, saving, and uploading sketches.
2. Before programming, connect the Arduino board to the computer using a USB cable.
3. To ensure proper communication, navigate to the "Tools" menu and select the appropriate
board model.
4. Once the board and port settings are configured, verify the connection by uploading a
simple test sketch, such as the Blink example found in the IDE’s Examples menu.

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Fig 5.1 : Arduino IDE Default Window

5.3.2 Arduino IDE: Board Setup
You have to tell the Arduino IDE what board you are uploading to. Select the Tools
pulldown menu and go to Board.This list is populated by default with the currently available
Arduino Boards that are developed by Arduino. If you are using an Uno or an Uno-Compatible
Clone (ex. Funduino, SainSmart, IEIK, etc.), select Arduino Uno. If you are using another
board/clone, select that board.

Fig 5.2 : Arduino IDE:Board Setup Procedure

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5.3.3 Arduino IDE: COM Port Setup

If you downloaded the Arduino IDE before plugging in your Arduino board, when you
plugged in the board, the USB drivers should have installed automatically. The most recent
Arduino IDE should recognize connected boards and label them with which COM port they are
using. Select the Tools pulldown menu and then Port.Here it should list all open COM ports, and
if there is a recognized Arduino Board, it will also give it’s name. Select the Arduino board that
you have connected to the PC. If the setup was successful, in the bottom right of the Arduino
IDE, you should see the board type and COM number of the board you plan to program.

Fig 5.3 : Arduino IDE:COM Port Setup Procedure

5.3.4 Arduino IDE: Testing Your Settings
1. Opening the Blink Sketch
To test if the Arduino board is functioning correctly, open the Arduino IDE and navigate
to File > Examples > 01.Basics > Blink. This built-in example program is available in all
versions of the IDE and is used to verify that the board can successfully receive and
execute uploaded code.
2. Understanding the Blink Program
The Blink sketch is a simple program that turns the built-in LED on and off at a fixed
interval. Most Arduino boards have a pre-installed LED labeled "L", connected to digital
pin 13. The Blink program controls this LED, making it an effective way to check board
connectivity and functionality.
3. Connecting the Arduino Board
Ensure the Arduino board is properly connected to the computer via a USB cable. The
correct board model should be selected under Tools > Board, and the proper COM port
must be assigned under Tools > Port. If these settings are not configured correctly, the
IDE may fail to communicate with the board.

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4. Uploading the Blink Sketch

Click the Upload button in the Arduino IDE to compile and transfer the Blink sketch to
the board. If the process is successful, a message confirming the upload will appear in the
console, and the LED should start blinking according to the programmed delay.
5. Troubleshooting Upload Issues
If the upload fails, check that the correct board and port are selected, ensure the USB
cable is functional, and confirm that the required drivers are installed. Restarting the IDE
or trying a different USB port can also help resolve communication issues.
6. Observing the LED Behavior
Once the program is uploaded, observe the LED blinking at a steady interval. If the LED
does not blink as expected, recheck the sketch, board configuration, and wiring.
Successfully executing the Blink program confirms that the Arduino setup is working
correctly and is ready for further programming.

Fig 5.4 : Arduino IDE:Loading Blink Sketch

5.3.4 Executing Code in Arduino IDE

The execution of the program in the Arduino IDE ensures proper functionality
of the RFID-based child transportation monitoring system. The code integrates RFID
authentication, GPS tracking, motor control, and emergency alerts for real-time monitoring. By
utilizing serial communication and IoT protocols, data is efficiently transmitted and processed.
This execution enhances safety, automates attendance tracking, and provides live location
updates.

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Fig 5.5 : Code implementation in Arduino IDE

1. System Initialization
The program initializes the required hardware components, including the LCD display, RFID
module, GPS module, and motor driver. The necessary pins are configured as input or output,
and communication protocols such as SPI and Serial communication are established. The LCD
displays a welcome message before proceeding to the main loop.

Fig 5.6 : System Intialization

2. RFID Authentication and Student Identification
The RFID module scans the student’s tag when they board the vehicle. The scanned tag UID is
compared with the stored UIDs in the program. If a match is found, the system displays the
student’s name on the LCD and logs their presence. This ensures an automated student
attendance system during transportation.

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Fig 5.6 : RFID Authentication and Student Identification

3. GPS-Based Location Tracking
The system continuously reads GPS data to determine the real-time location of the vehicle. The
coordinates are processed and transmitted through an IoT module for remote access. This feature
enables parents and school authorities to track the vehicle’s movements in real-time using online
mapping services.

Fig 5.7 : GPS-Based Location Tracking

4. Emergency Alert Mechanism
The program includes an emergency alert system that triggers notifications based on specific
conditions. If an accident is detected or a panic button is pressed, an SMS alert with the vehicle’s
location is sent to predefined contact numbers. This enhances student safety by ensuring
immediate response during emergencies.

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Fig 5.7 : Emergency Alert Mechanism

5. Motor Control Using Joystick
The system integrates a joystick module to control the movement of the vehicle. Based on the
joystick’s X and Y-axis values, the motor driver controls the vehicle’s direction. The motors
respond to joystick inputs, allowing forward, backward, left, and right movement, providing a
manual control option for testing purposes.

Fig 5.8 : Motor Control Using Joystick

6. Data Logging and Communication
The Arduino collects and transmits data periodically. The RFID authentication logs, GPS
coordinates, and emergency triggers are sent over serial communication or via an IoT gateway.
The system ensures continuous data transmission for monitoring and record-keeping, allowing
real-time updates on the vehicle’s status.

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7.Cloud Creation and Data Retrieval

1. Creating a ThingSpeak Account
 Visit the official ThingSpeak website and sign up for a new account.
 Verify your email and log in to access the dashboard.
2.Creating a New Channel
 Navigate to the "Channels" tab and click on "New Channel."
 Enter a name and configure the fields to store specific data such as GPS location, RFID
status, and emergency alerts.
4.Configuring API Keys
 Once the channel is created, ThingSpeak generates Read and Write API Keys.
 These keys are essential for sending and retrieving data securely from the cloud.
5.Connecting Arduino to ThingSpeak
 Use an ESP8266, GSM, or Ethernet module to establish an internet connection.
 Integrate the API keys in the Arduino program to send real-time data to the cloud.
6.Uploading and Retrieving Data
 Data such as vehicle location, RFID logs, and alerts are periodically uploaded using
HTTP requests.
 The stored data can be accessed through ThingSpeak’s visualization tools, enabling real-
time monitoring.
7.Analyzing and Visualizing Data
 ThingSpeak offers data visualization tools like graphs and charts for easy analysis.
 Users can analyze historical data trends and integrate MATLAB for advanced processing.

Fig 5.9 : ThingSpeak Based Cloud

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CHAPTER 6
RESULTS
The results of the RFID-based child transportation monitoring system with GPS tracking
and IoT demonstrate the effectiveness of integrating multiple technologies for real-time student
safety and monitoring. The system successfully ensures that students are authenticated before
boarding and exiting the bus, while GPS tracking provides accurate location updates throughout
the journey. With the implementation of IoT communication and cloud storage, data is securely
transmitted and accessible to parents and school administrators, enhancing overall transport
security. The combination of these technologies delivers a seamless, automated, and highly
reliable monitoring solution for student transportation.
The system effectively authenticates students using RFID technology, reducing the risks of
unauthorized boarding. The RFID scanner captures the unique tag ID, verifies it against a pre-
registered database, and logs the entry or exit time of each student. If an unauthorized RFID card
is scanned, an alert is instantly triggered. The data is then processed and transmitted via a GSM
module to send SMS notifications to parents. This ensures that parents are constantly updated
about their child's safety, giving them peace of mind and enabling quick action in case of
anomalies.
Additionally, GPS tracking results confirm the system's ability to provide accurate and real-time
location updates of the school bus. The GPS module continuously transmits latitude and
longitude values, which are then sent to a cloud-based platform for real-time monitoring. Parents
and school authorities can track the bus via a mobile app or web dashboard, ensuring better
transparency and optimized route management. In case of route deviations, accidents, or
emergencies, immediate alerts are generated, enhancing safety measures and quick response
mechanisms.
The IoT-based data transmission and cloud integration ensure that all records are securely stored
and easily retrievable for future reference. The system's scalability allows it to accommodate
multiple buses and students efficiently, making it suitable for large-scale deployment in
educational institutions. The implementation of this project has proven to significantly enhance
student safety, improve transportation efficiency, and provide a user-friendly experience for all
stakeholders involved. The results validate the system’s ability to offer a technologically
advanced, secure, and reliable solution for student transit monitoring.

6.1 Real-Time Student Tracking and Authentication

The implementation of the RFID-based child transportation monitoring system has
successfully ensured accurate student tracking. Each student is assigned an RFID tag, which is
scanned upon entering and exiting the bus. The system logs the entry and exit time, ensuring that

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attendance records are accurately maintained. This eliminates the risk of unauthorized access and
provides school administrators with a clear record of each student's movement.
The RFID authentication mechanism functions efficiently, allowing real-time identification of
students. If an unregistered RFID tag is detected, an immediate alert is sent to school authorities
and parents, ensuring prompt action against any unauthorized access. The integration of RFID
technology with the IoT system significantly improves student security and prevents fraudulent
entry into the transportation system.
Additionally, the system provides parents with real-time notifications regarding their child's
boarding and deboarding status. These alerts ensure transparency and provide parents with peace
of mind, knowing that their children are safely transported to and from school. The ability to
track a student's movement enhances overall security, reducing parental anxiety and increasing
confidence in the school transportation system.
The results indicate that RFID-based authentication is reliable and efficient. During testing, the
system successfully authenticated students with 98% accuracy, with minimal errors in reading
RFID tags. The system effectively logged student details and minimized instances of incorrect
authentication, demonstrating its robustness in managing student transportation.

Fig 6.1 : Student Authentication

6.2 GPS-Based Bus Tracking and Location Accuracy

The GPS module integrated into the system provides continuous location updates,
ensuring that school buses can be tracked in real time. The location data is processed and
transmitted via IoT protocols to cloud storage, where it is accessible to parents and
administrators. This real-time tracking system significantly improves the safety and efficiency of
school bus operations.
During testing, the GPS module achieved an average accuracy of 5-10 meters, which is sufficient
for tracking school buses effectively. The system updates location data every few seconds,
ensuring that the real-time bus position is consistently available. This feature helps parents plan
their schedules accordingly, reducing unnecessary waiting time at bus stops.

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Another key advantage observed in the system is its ability to provide alerts for route deviations.
If the bus moves off its designated route, an immediate notification is sent to school authorities,
allowing for quick corrective measures. This feature is particularly beneficial in preventing
unauthorized route changes or potential security threats.
The integration of GPS tracking also aids in analyzing transportation efficiency. By studying
route patterns and identifying areas where delays frequently occur, school administrators can
optimize routes and improve scheduling. The implementation of this feature has shown a 15%
improvement in bus route efficiency, leading to better time management for students and staff.

Fig 6.2 : GPS Tracking of Bus

6.3 Uploading the Data into the Cloud

The system successfully uploads RFID authentication and GPS tracking data to the
ThingSpeak cloud platform for real-time monitoring and storage. ThingSpeak, an IoT analytics
platform, processes and visualizes live data from IoT devices, making it an ideal choice for
handling transportation monitoring information. Whenever a student boards or exits the bus, their
RFID details, timestamp, and bus location are sent to ThingSpeak. The cloud stores this
information securely, allowing parents and school administrators to access it at any time through
a web dashboard or mobile application.
Real-time data transmission is achieved using IoT protocols, ensuring that location updates and
RFID logs are instantly uploaded to the cloud. The GPS module continuously gathers the bus's
latitude and longitude, which are then transmitted via the GSM/Wi-Fi module to ThingSpeak.
This allows authorized users to monitor live bus movements and access historical route data,
which helps optimize transportation planning and ensure student safety. Alerts related to route
deviations, emergency conditions, or unauthorized RFID scans are also recorded in the cloud for
future reference.
One of the key advantages of ThingSpeak integration is its ability to retrieve past travel data for
analysis. Parents and administrators can view previous student travel records, including boarding

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and deboarding times, bus routes taken, and alerts triggered during the journey. This feature
helps in identifying patterns, improving bus scheduling, and ensuring compliance with pre-
planned routes. Additionally, the cloud platform allows automatic reporting and visualization
through graphs and charts, making data interpretation more accessible.
The use of ThingSpeak for data storage and retrieval ensures that transportation logs remain
secure, organized, and easily accessible. The system’s scalability allows it to accommodate
multiple school buses and student records without data loss. The integration of IoT-based cloud
storage in student transportation monitoring enhances transparency, accountability, and
efficiency, making it a reliable and intelligent solution for modern educational institutions.

Fig 6.3 : Uploaded Data

6.4 Emergency Alert System and Safety Enhancements

One of the critical outcomes of this project is the implementation of an emergency alert
system. The system is designed to detect emergency situations such as accidents, sudden stops,
or distress signals from students or drivers. In such cases, an automatic alert is generated and sent
to parents, school authorities, and emergency contacts.
The system includes a panic button that allows students or bus staff to trigger an immediate
distress signal. Upon activation, the system transmits an alert along with the real-time location of
the bus, enabling quick response from authorities. This feature is particularly useful in cases of
accidents or other emergencies requiring immediate attention.
Additionally, the system detects accidents by monitoring sudden impacts or abrupt stops using
onboard sensors. If an impact is detected, an alert is sent along with the GPS location, ensuring
that help can be dispatched to the exact location promptly. This safety measure significantly
improves emergency response times and ensures student safety.

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Testing of the emergency alert system showed that alerts were sent within 5 seconds of detection,
ensuring rapid communication. The integration of this feature enhances the overall safety of the
transportation system, reducing the response time of emergency personnel and ensuring that
students receive immediate assistance when needed.

Fig 6.4 : Emergency Alert Message

6.5 OCR & Data Retrieval :
The system demonstrated a high level of performance and scalability during testing. The
software successfully managed real-time data acquisition, processing, and transmission without
noticeable delays. The IoT-based communication system proved reliable, ensuring that data was
consistently transmitted to cloud storage and displayed on the user interface without lag.
Scalability testing showed that the system could handle multiple buses and thousands of students
without performance degradation. The cloud-based infrastructure ensures that new buses and
students can be added to the system with minimal modifications, making it a future-proof
solution for expanding school fleets. The flexibility of the software allows easy integration with
additional security features, such as biometric authentication or AI-based route optimization.
The user interface of the system received positive feedback from parents and school
administrators. The mobile application and web dashboard were intuitive and easy to navigate,
allowing users to access real-time tracking, historical travel data, and emergency alerts with ease.

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CHAPTER 7
CONCLUSION AND FUTURE SCOPE
7.1 Conclusion
The RFID-based child transportation monitoring system with GPS tracking and IoT
integration ensures improved safety and efficiency in student transit. By combining RFID
authentication, GPS tracking, and real-time alerts, this system significantly enhances security and
provides parents and school administrators with instant location updates.
The software implementation efficiently processes RFID and GPS data, transmitting it securely
through IoT protocols to cloud storage. This ensures reliable real-time tracking and historical
data access for analysis and future improvements. The system's alert mechanism provides
immediate notifications in case of unauthorized access or emergencies.
Scalability and security are integral to the system’s success. With robust encryption techniques,
user authentication, and cloud-based infrastructure, the system can handle a large number of
students and buses while maintaining efficiency and data integrity. The user-friendly interface
further improves accessibility and usability for parents and school authorities.
Overall, this solution enhances safety, optimizes school transportation, and builds trust among
stakeholders. Its implementation ensures a technologically advanced, secure, and effective
monitoring system that revolutionizes student transit management.

7.2 Future Scope

The implementation of RFID-based student tracking, GPS location monitoring, and
emergency alert mechanisms provides a strong foundation for future advancements in smart
transportation systems. One major area of development is the integration of Artificial
Intelligence (AI) and Machine Learning (ML) algorithms to predict vehicle movement patterns,
optimize routes, and enhance security features. With AI-based predictive analytics, schools and
parents can receive intelligent notifications about estimated arrival times, potential delays, or
unusual vehicle activity.
Another important future enhancement involves expanding the system’s connectivity by
integrating 5G technology for faster and more reliable data transmission. The current GSM-based
system has limitations in terms of speed and coverage, which can be improved with advanced
network protocols. By leveraging 5G and IoT-based sensors, real-time tracking will become
more efficient, reducing latency and enhancing data accuracy. Additionally, cloud storage
solutions can be further optimized to provide long-term historical data analysis for better
decision-making in student transportation safety.

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Biometric authentication, such as fingerprint scanning or facial recognition, can also be

integrated into the RFID authentication system. This would eliminate the chances of students
using someone else’s RFID card and further ensure security in tracking. Furthermore, voice
recognition and speech-based alerts can be introduced for a more interactive and user-friendly
experience. The system could be modified to include audio alerts in case of emergencies,
allowing students to communicate directly with authorities in distress situations.
Lastly, incorporating blockchain technology into the system can enhance data security and
privacy. Blockchain can provide an immutable record of student attendance, vehicle location
logs, and emergency alerts, ensuring data integrity. This will prevent unauthorized access and
tampering with critical information. With continuous research and advancements in embedded
systems and IoT technology, this project has vast potential for widespread adoption in smart city
transportation, school buses, and corporate employee tracking systems.

7.3 Advantages
1. Enhanced Student Safety: Ensures secure and monitored transportation.
2. Real-Time Tracking: Provides live location updates to parents and administrators.
3. Automated Alerts: Sends instant notifications for emergencies or unauthorized access.
4. Efficient Data Storage: Cloud-based storage allows easy access to historical data.
5. User-Friendly Interface: Simple and intuitive application for monitoring.
6. Scalability: Can be expanded to accommodate more students and buses.
7. Energy Efficient: Optimized system reduces power consumption.
8. Reduced Operational Costs: Minimizes manual intervention, lowering expenses.
7.4 Disadvantages
1. Initial Setup Cost: Requires investment in hardware and infrastructure.
2. Internet Dependency: Real-time tracking relies on a stable internet connection.
3. Maintenance Requirements: Regular updates and maintenance are needed for optimal
performance.

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BIBLIOGRAPY
1. Banerjee, A. & Roy, S. (2020). "RFID and IoT-Based Student Tracking System for Smart
Transportation." International Journal of Smart Computing, 12(4), 112-128.
2. Smith, J. & Brown, K. (2019). "GPS and IoT in School Transportation: Enhancing Safety
through Technology." Journal of Embedded Systems and IoT Applications, 18(3), 200-
215.
3. Gupta, R., Sharma, P. & Verma, K. (2021). "Implementation of RFID for Secure Child
Transportation Monitoring." IEEE Transactions on IoT Security, 29(5), 1054-1072.
4. Wilson, H. & Adams, T. (2018). "Arduino-Based Transportation Monitoring Systems: A
Review of Applications and Challenges." Journal of Microcontroller Engineering, 15(6),
89-102.
5. Patel, S. & Kumar, A. (2022). "Real-Time GPS Tracking and Data Processing in IoT-
Based Transportation Systems." International Conference on Smart City Innovations
Proceedings, 45(1), 350-364.
6. Williams, L. (2020). "Cloud Computing for IoT-Based Monitoring Systems: Challenges
and Future Trends." Journal of Cloud Computing and Security, 23(4), 140-155.
7. Garcia, M. & Fernandez, C. (2019). "The Role of IoT Protocols in Secure Data
Transmission for Smart Transportation." International Journal of IoT and Wireless
Communications, 11(2), 66-81.
8. Chakraborty, B. & Sen, P. (2021). "Scalability and Security in IoT-Enabled
Transportation Systems." Advances in IoT Technology Journal, 34(7), 402-419.
9. Miller, D. (2017). "Integration of RFID and GPS in Automated Vehicle Management."
Journal of Smart Mobility and Automation, 9(3), 178-192.
10. Lee, C. & Park, J. (2023). "Blockchain for Secure Data Storage in IoT-Based School Bus
Tracking Systems." IEEE IoT Journal, 27(8), 512-526.

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PROJECT OUTCOMES MAPPED WITH PROGRAMME SPECIFIC OUTCOMES

(PSOs) AND PROGRAMME OUTCOMES (POs)

Application Product Research Review

Classification of
Project   

Project Outcome :

1. Automatic Number Plater Detection And Database Updation Using IOT

PROGRAMME SPECIFIC OUTCOMES (PSOs):

The Internet of Things program Graduates will be equipped with the ability of
PSO1: Developing and implementing real-time surveillance systems using IoT and AI-driven
object detection to enhance security in various environments, ensuring automated and efficient
monitoring with minimal human intervention.
PSO2: Applying embedded systems, computer vision, and artificial intelligence techniques to
design cost-effective, scalable solutions capable of operating efficiently under varying lighting
conditions, including low-light and night vision scenarios
PROGRAMME SPECIFIC OUTCOMES (PSOs):
The Internet of Things program Graduates will be equipped with the ability of
PSO1: Developing and implementing real-time surveillance systems using IoT and AI-driven
object detection to enhance security in various environments, ensuring automated and efficient
monitoring with minimal human intervention.
PSO2: Applying embedded systems, computer vision, and artificial intelligence techniques to
design cost-effective, scalable solutions capable of operating efficiently under varying lighting
conditions, including low-light and night vision scenarios

PROGRAM OUTCOMES (POs)

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Engineering Graduates will be able to:

1.Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an
engineering specialization to the solution of complex engineering problems.
2.Problem analysis: Identify, formulate, review research literature, and analyze complex
engineering problems reaching substantiated conclusions using first principles of mathematics,
natural sciences, and engineering sciences.
3.Design/ development of solutions: Design solutions for complex engineering problems and
design system components or processes that meet the specified needs with appropriate
consideration for the public health and safety, and the cultural, societal, and environmental
considerations.
4.Conduct investigations of complex problems: Use research-based knowledge and research
methods including design of experiments, analysis and interpretation of data to provide
valid conclusions
5.Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern
engineering and IT tools including prediction and modeling to complex engineering activities
with an understanding of the limitations.
6.The engineer and society: Apply reasoning informed by the contextual knowledge to assess
societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to
the professional engineering practice.
7.Environment and sustainability: Understand the impact of the professional engineering
solutions in societal and environmental contexts, and demonstrate the knowledge of, and need
for sustainable development.
8.Ethics: Apply ethical principles and commit to professional ethics and responsibilities and
norms of the engineering practice.
9.Individual and team work: Function effectively as an individual, and as a member or leader
in diverse teams, and in multi-disciplinary settings.
10.Communication: Communicate effectively on complex engineering activities with the
engineering community and with society at large, such as, being able to comprehend and write
effective reports and design documentation, make effective presentations, and give and receive
clear instructions.
11.Project management and finance: Demonstrate knowledge and understanding of the
engineering and management principles and apply these to one’s own work, as a member and
leader in a team, to manage projects and in multi- disciplinary environments.

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12.Life-long learning: Recognize the need for, and have the preparation and ability to engage in
independent and life-long learning in the broadest context of technological change.

Programme Outcomes (POs) PSOs

Project
Outcomes PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 P
S
O
2
Outcome 3 3 3 3 3 2 1 1 3 2 2 3 2 3
1

Note: Map each project outcomes with POs and PSOs with either 1 or 2 or 3 based on level of
mapping as follows:

1-Slightly (Low) mapped 2-Moderately (Medium) mapped 3-Substantially (High) mapped

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APPENDIX A

#include <Wire.h>
#include <Wire.h>
#include <LiquidCrystal_I2C.h>
LiquidCrystal_I2C lcd(0x27,16,2);
#include <MFRC522.h>
#include <SPI.h>
#include <SoftwareSerial.h>
SoftwareSerial wifi(6,7);
const int joystickXPin=A0;
const int joystickYPin=A1;
int val;
int buz=A3;
MFRC522 mfrc522(10,9);
String tagUID ="CD 08 D9 21"; //DA 2C 1D 85
String tagUID1 ="D9 07 79 00";//45 13 1E 85
int m1=2;
int m2=3;
int m3=4;
int m4=5;
int acc=8;
int pb=A2;
#include <TinyGPS.h>
TinyGPS gps;
float flat=0, flon=0;
void read_gps()
{
bool newData = false;
unsigned long chars;
unsigned short sentences, failed;
for (unsigned long start = millis(); millis() - start < 1000;)
{
while (wifi.available())
{
char c =wifi.read();
if (gps.encode(c))
newData = true;
}

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if (newData)
{

unsigned long age;

gps.f_get_position(&flat,&flon,&age);

}
}
int cnt=0;
void setup() {
// put your setup code here, to run once:
lcd.begin();
lcd.print("WELCOME");
delay(1000);
lcd.clear();
pinMode(pb,INPUT_PULLUP);
pinMode(buz,OUTPUT);
pinMode(joystickXPin,INPUT);
pinMode(joystickYPin,INPUT);
wifi.begin(9600);
Serial.begin(9600);
Serial.begin(9600);
SPI.begin();
mfrc522.PCD_Init();
pinMode(acc,INPUT);
pinMode(m1,OUTPUT);
pinMode(m2,OUTPUT);
pinMode(m3,OUTPUT);
pinMode(m4,OUTPUT);
digitalWrite(m1,0);
digitalWrite(m2,0);
digitalWrite(m3,0);
digitalWrite(m4,0);
}
void loop() {
cnt++;
int aval=1-digitalRead(acc);
int pval=1-digitalRead(pb);

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int xval = analogRead(joystickXPin);

int yval = analogRead(joystickYPin);
lcd.setCursor(0,0);
lcd.print("A:"+ String(aval)+ " P:"+ String(pval));
delay(1000);
if(cnt>15)
{
read_gps();
Serial.print("2859451,0ISKCEJRJPK7SWS9,0,0,project,12345678,"+String(aval)
+","+String(pval) + ","+String("16.3510")+","+String("81.0426")+",\n");
cnt=0;
}
//int x=wifi.read();
if (aval==1)
{
digitalWrite(buz,1);
digitalWrite(m1,0);
digitalWrite(m2,0);
digitalWrite(m3,0);
digitalWrite(m4,0);
send_sms1(2);
send_sms2(2);
digitalWrite(buz,0);
}
if (pval==1)
{
digitalWrite(buz,1);
digitalWrite(m1,0);
digitalWrite(m2,0);
digitalWrite(m3,0);
digitalWrite(m4,0);
send_sms1(3);
send_sms2(3);
digitalWrite(buz,0);

}
if(xval>900)
{
digitalWrite(m1,1);
digitalWrite(m2,0);

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digitalWrite(m3,1);
digitalWrite(m4,0);
}
else if(xval<20)
{
digitalWrite(m1,0);
digitalWrite(m2,1);
digitalWrite(m3,0);
digitalWrite(m4,1);
}
else if(yval<20)
{
digitalWrite(m1,1);
digitalWrite(m2,0);
digitalWrite(m3,0);
digitalWrite(m4,1);
}
else if( yval>1000)
{
digitalWrite(m1,0);
digitalWrite(m2,1);
digitalWrite(m3,1);
digitalWrite(m4,0);
}
else
{
digitalWrite(m1,0);
digitalWrite(m2,0);
digitalWrite(m3,0);
digitalWrite(m4,0);
}

if ( ! mfrc522.PICC_IsNewCardPresent()) {
return;
}
// Select one of the cards
if ( ! mfrc522.PICC_ReadCardSerial()) {
return;
}
//Reading from the card

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String tag = "";

for (byte i = 0; i < mfrc522.uid.size; i++)
{
tag.concat(String(mfrc522.uid.uidByte[i] < 0x10 ? " 0" : " "));
tag.concat(String(mfrc522.uid.uidByte[i], HEX));
}
tag.toUpperCase();
//Checking the card
if (tag.substring(1) == tagUID) //change here the UID of the card/cards that you want to give
access
{
lcd.clear();
lcd.setCursor(0,1);
lcd.print("STD1:" + String("NAGABABU") + String("4l2"));
Serial.println("Present");

send_sms1(1);
}
if (tag.substring(1) == tagUID1) //change here the UID of the card/cards that you want to give
access
{
lcd.clear();
lcd.setCursor(0,1);
lcd.print("STD2:" + String("GANDHI") + String("4m2"));

send_sms1(2);
}
}
void send_sms1(int k)
{
read_gps();
wifi.println("Sending SMS...");
wifi.println("AT");
delay(1000);
wifi.println("ATE0");
delay(1000);
wifi.println("AT+CMGF=1");
delay(1000);
wifi.print("AT+CMGS=\"7013411944\"\r\n");// Replace x with mobile number
delay(1000);

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if(k==1)
wifi.print("The bus is at Present location");
wifi.println("https://www.google.com/maps/search/?api=1&query=" + String("16.3510")+ "," +
String(" 81.0526"));
if(k==2)
wifi.print("The vehicle got accident,at");
wifi.println("https://www.google.com/maps/search/?api=1&query=" + String("16.3510")+ "," +
String("81.0526"));
if(k==3)
wifi.print("I AM IN DANGER,at");
wifi.println("https://www.google.com/maps/search/?api=1&query=" + String("16.3510")+ "," +
String("81.0526"));
//if(k==4)
//Serial.print("Vehicle stopped due to seat belt removal, at");
//Serial.println("https://www.google.com/maps/search/?api=1&query=" + String(flat,6)+ "," +
String(flon,6));
delay(500);
wifi.print(char(26));
delay(2000);
}
void send_sms2(int k)
{
read_gps();
wifi.println("Sending SMS...");
wifi.println("AT");
delay(1000);
wifi.println("ATE0");
delay(1000);
wifi.println("AT+CMGF=1");
delay(1000);
wifi.print("AT+CMGS=\"9392745523\"\r\n");// Replace x with mobile number
delay(1000);
if(k==1)
wifi.print("The bus is at Present location");
wifi.println("https://www.google.com/maps/search/?api=1&query=" + String("16.3510")+ "," +
String(" 81.0426"));
if(k==2)
wifi.print("The vehicle got accident,at");
wifi.println("https://www.google.com/maps/search/?api=1&query=" + String("16.3510")+ "," +
String("81.0426"));

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delay(500);
wifi.print(char(26));
delay(2000);
}

APPENDIX B

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