SMART HIGHWAY SYSTEM

(ES-452: Major Project - Dissertation)

submitted in partial fulfillment of the requirement

for the award of the degree of

Bachelor of Technology
in
Electronics & Communication Engineering

Submitted by

YASH KAUSHIK
35220802821

Under the supervision of

Dr. KOMAL BHAGAT

Associate Professor

Department of Electronics & Communication Engineering

Bhagwan Parshuram Institute of Technology
PSP-4, Sector-17, Rohini, Delhi-110089

May/June 2025
 BHAGWAN PARSHURAM INSTITUTE OF TECHNOLOGY

VISION OF THE INSTITUTE

• To establish a leading Global Center of Excellence in multidisciplinary education, training and

research in the area of Engineering, Technology and Management.
• To produce technologically competent, morally & emotionally strong and ethically sound
professionals who excel in their chosen field, practice commitment to their profession and
dedicate themselves to the service of mankind.

MISION OF THE INSTITUTE

• To develop world class Laboratories and other Infrastructure conducive in acquiring latest
knowledge and expertise.
• To bridge the knowledge and competency gaps of institute’s fresh pass-outs vis-à-vis field
requirements.
• To strengthen Industry- Institute Interaction and partnership for imbibing corporate culture
amongst our faculty and students.
• To promote research culture among faculty and students enhancing their academic and
professional confidence needed to face global challenges. To honour commitment towards
social and moral values
• To honour commitment towards social and moral values.

BHAGWAN PARSHURAM INSTITUTE OF TECHNOLOGY

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 PROGRAM OUTCOMES (POs)

PO 1. Engineering Knowledge: Apply knowledge of mathematics, science, engineering

fundamentals, and an engineering specialization to the solution of complex engineering
problems.
PO 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.
PO 3. Design/development of Solutions: Design solutions for complex engineering problems and
design system components or processes that meet specified needs with appropriate
consideration for public health and safety, and the cultural, societal, and environmental
considerations.
PO 4. Conduct Investigations of Complex Problems: Use research-based knowledge and
research methods including design of experiments, analysis and interpretation of data, and
synthesis of the information to provide valid conclusions.
PO 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.
PO 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.
PO 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.
PO 8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and
norms of the engineering practice.
PO 9. Individual and Team Work: Function effectively as an individual, and as a member or
leader in diverse teams, and in multi-disciplinary settings.
PO 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.
PO 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.
PO 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

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 BHAGWAN PARSHURAM INSTITUTE OF TECHNOLOGY

COURSE OUTCOMES (COs)

CO1: Students will demonstrate the ability to independently investigate research literature to
identify and articulate engineering problems. They will also recognize the community that stands
to benefit from solving the identified engineering problem and exhibit a commitment to
environmental consideration.
CO2: Students will develop the ability to create a Gantt chart for project scheduling, assigning
responsibilities to each team member. Additionally, they will independently explore a
comprehensive range of engineering tools applicable to the identified engineering problem and
select the most appropriate tool for developing the solution.
CO3: Students will demonstrate the ability to apply identified concepts and engineering tools to
generate a design solution for the identified problem. Subsequently, they will analyse and interpret
the results of experiments conducted on the designed solution to draw valid conclusions.
Additionally, they will possess the skill to perform budget analysis for the project by efficiently
utilizing resources.
CO4: In adherence to professional ethics, students will acquire the ability to participate in
proficient written communication through the project report, research paper or poster presentation.
Furthermore, students will develop effective oral communication skills by presenting project work,
conducting project demonstrations, and creating project-related videos. They will also exhibit the
skills necessary to collaborate within a team, make valuable contributions, and assume leadership
roles.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 BHAGWAN PARSHURAM INSTITUTE OF TECHNOLOGY

SUSTAINABLE DEVELOPMENT GOALS (SDGs)

SDG 1 NO POVERTY

SDG 2 ZERO HUNGER

SDG 3 GOOD HEALTH & WELL-BEING

SDG 4 QUALITY EDUCATION

SDG 5 GENDER EQUALITY

SDG 6 CLEAN WATER & SANITATION

SDG 7 AFFORDABLE & CLEAN ENERGY

SDG 8 DECENT WORK & ECONOMIC GROWTH

SDG 9 INDUSTRY, INNOVATION & INFRASTRUCTURE

SDG 10 REDUCED INEQUALITIES

SDG 11 SUSTAINABLE CITIES & COMMUNITIES

SDG 12 RESPONSIBLE CONSUMPTION & PRODUCTION

SDG 13 CLIMATE ACTION

SDG 14 LIFE BELOW WATER

SDG 15 LIFE ON LAND

SDG 16 PEACE & JUSTICE STRING INSTITUTIONS

SDG 17 PARTNERSHIPS FOR THE GOALS

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 DEPARTMENT OF ELECTRONICS & COMMUNCIATION
ENGINEERING

VISION OF THE DEPARTMENT

To emerge as a Center of Excellence producing globally competent and morally sound

professionals in the field of Electronics & Communication Engineering who will practice
commitment to their profession and dedicate themselves to the service of mankind.

MISION OF THE DEPARTMENT

➢ To develop state-of-the-art laboratories providing relevant practical inputs to students.

➢ To provide strong knowledge base to students in the area of Electronics & Communication
Engineering, and to train them as per requirement of industries and research organizations.
➢ To facilitate institute industry interaction to the benefit of stake holders and to motivate teachers
for continuous improvement of their academic standards.

PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

PEO 1: Graduate will have the fundamental and advance knowledge in Mathematics, Science,
Electronics & Communication Engineering and design methodologies to successfully accomplish
their professional career in industry as an Engineer, theoretically practically, in the field of
Electronics & Communication Engineering, or become an entrepreneur.
PEO 2: Graduate will have strong fundamental knowledge in specialized areas of Electronics &
Communication Engineering to contribute towards research and developments through paper
publications, projects and pursue higher studies in their specialized fields.
PEO 3: Graduate shall learn all interpersonal skills and inculcate sense of social responsibilities
and environmental concerns so as to make them good leaders and citizens.

PROGRAM SPECIFIC OUTCOMES (PSOs)

PSO 1: Students will have proficiency in grasping fundamental principles of Electronics &
Communication Engineering and effectively applying them across diverse domains, including
Semiconductors, Communications, Signal processing, Antennas, Networking, VLSI, Embedded
systems, and becoming adept in the latest tools and methodologies employed in both research and
industry.
PSO 2: Student will foster critical thinking to evaluate engineering issues pertinent to Electronics
& Communication Engineering through the cultivation of profound expertise and skills in the
realms of fundamental sciences, engineering mathematics, and core engineering principles,
enabling the resolution of intricate engineering dilemmas.
PSO 3: Student will be able to acquire the skill to conduct independent research, seek innovative
solutions, and make contributions to the progress of knowledge in specialized areas of electronics
and communication engineering. Adhere to ethical principles in engineering practice, research, and
innovation, while exemplifying a steadfast dedication to integrity, social responsibility, and
sustainable development.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 COURSE OUTCOME TO PO MAPPING
COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12
CO1 2 2 0 2 0 2 3 0 0 0 0 2
CO2 2 2 3 2 3 0 0 0 2 0 0 2
CO3 3 3 3 3 2 0 2 0 2 0 0 3
CO4 0 0 0 0 0 0 0 3 3 3 2 1

Justification for CO-PO Mapping:

• CO1:
o PO1 & PO2: Critical literature review and problem articulation require strong
fundamentals and problem-solving skills.
o PO4: Investigation of problems is central to CO1.
o PO6: Recognizing community relevance aligns with societal responsibilities.
o PO7: Environmental commitment maps directly.
o PO12: Independent research fosters lifelong learning.
• CO2:
o PO1, PO2, PO4: Involves critical thinking, scheduling, and decision-making.
o PO3: Tool selection and solution planning involve designing systems.
o PO5: Exploration and use of modern engineering tools.
o PO9: Team responsibility assignment maps to individual and teamwork.
o PO12: Use of diverse tools requires continuous learning.
• CO3:
o PO1 to PO4: Design, application, experimentation, and interpretation.
o PO5: Use of appropriate tools in design and testing.
o PO7: Budgeting and resource use require sustainability understanding.
o PO9: Working with others on analysis fosters teamwork.
o PO12: Resource management and experimentation promote lifelong learning.
• CO4:
o PO8: Ethics in communication and reporting.
o PO9: Teamwork, collaboration, and leadership.
o PO10: Written, oral, visual communication through reports/presentations.
o PO11: Demonstrating leadership and teamwork reflects project management.
o PO12: Exposure to research/publications supports lifelong learning.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 CO TO PSO MAPPING

PSO1 PSO2 PSO3

CO1 2 2 3

CO2 3 2 2

CO3 3 3 3

CO4 1 1 3

Justification for CO–PSO Mapping:

• CO1:
o PSO1: Students connect fundamental ECE concepts with real-world problems.
o PSO2: Involves analysis and problem identification using core engineering
principles.
o PSO3: Reflects ethical research behavior, independent inquiry, and socially
responsible solutions.
• CO2:
o PSO1: Strong correlation due to tool selection across ECE domains.
o PSO2: Involves applying engineering and mathematical tools critically.
o PSO3: Students independently explore methods, reflecting a research-oriented
mindset.
• CO3:
o PSO1: High involvement in designing and testing systems across ECE domains.
o PSO2: Strong analytical and mathematical grounding to validate solutions.
o PSO3: High research component—interpreting results, drawing conclusions,
budgeting, and sustainability.
• CO4:
o PSO1: Minimal technical tool use here, so only a slight correlation.
o PSO2: Limited technical application, but communication of analytical results still
matters.
o PSO3: Strong ethical conduct, teamwork, communication, and contribution to
knowledge via presentations or papers.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 PROJECT TO SDG MAPPING
PROJECT TITLE: SMART HIGHWAY SYSTEM

MAPPED SUSTAINABLE DEVELOPMENT GOALS

(1/2/3/4/5/6/7/8/9/10/11/12/13/14/15/16/17)

SDG 7, SDG 9, SDG13

Project

Justification for SDG mapped.

SDG 7 - Affordable & Clean Energy
The project utilizes renewable energy sources (solar, wind, and noise energy to power
streetlights and traffic monitoring systems, promoting sustainable energy usage. These clean
energy solutions reduce dependency on conventional electricity and lower operational costs.
Additionally, the use of energy-efficient LED lighting systems with adaptive brightness control
ensures minimal energy wastage, making highway management both eco-friendly and cost-
effective.
SDG 9: Industry, Innovation & Infrastructure
The integration of smart technology in highway systems improves transportation
infrastructure, enhances traffic management, and increases road safety. The inclusion of IoT-
based sensors, real-time traffic monitoring, automated alert systems, and wireless
communication modules showcases innovation in engineering and smart infrastructure
development. The system promotes a shift towards digitally managed highways, supporting
industrial growth through technological innovation and providing a foundation for scalable,
future-ready infrastructure.
SDG 17: Climate Action
The project reduces carbon footprint by promoting renewable energy use and optimizing energy
efficiency in highways. By leveraging renewable energy and optimizing energy usage through
smart lighting and automated traffic control, the project lowers the carbon footprint associated
with highway operations. Moreover, real-time environmental monitoring (e.g., air quality,
temperature) enables authorities to track and respond to climatic condition

Project to PO mapping

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

Project 3 3 3 3 3 2 1 2 2 3 2 3

Justification for Project to PO mapping

PO1: Engineering Knowledge (3/3)

The project applies principles of electronics communication, and renewable energy for
highway system development

PO2: Problem Analysis (3/3)

It identifies and addresses energy wastage and inefficient traffic management on highways.

PO3: Design/Development of Solutions (3/3)

The system is designed to optimize energy usage, integrate renewable sources, and implement smart
traffic control mechanisms

PO4: Conduct Investigations of Complex Problems (3/3)

Utilizes structured dataset analysis, model training/testing, performance evaluation (e.g.,
accuracy, precision, recall), and result interpretation.

PO5: Modern Tool Usage (3/3)

The project involves hardware components like microcontrollers, sensors, and software tools
for data visualization and communication.

PO6: The Engineer and Society (2/3)

The system benefits society by improving road safety, reducing energy wastage, and promoting
sustainable practices.

PO7: Environment and Sustainability (1/3)

While the project is health-focused, early detection can reduce resource consumption in long-
term cancer treatments, offering indirect environmental benefits.

PO8: Ethics (2/3)

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
The project adheres to ethical engineering principles by focusing on safety, sustainability, and
responsible innovation.

PO9: Individual and Team Work (2/3)

The project involves teamwork in research, development, and implementation phases..

PO10: Communication (3/3)

Effective communication is required for system design, data analysis, and documentation of results.

PO11: Project Management and Finance (2/3)

The project involves planning, budgeting, and resource allocation for hardware and software
components

PO12: Life-long Learning (3/3)

The project encourages continuous learning about emerging technologies, energy-efficient solutions,
and smart infrastructure innovations.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 Project to PSO mapping

PSO 1 PSO 2 PSO 3

Project 3 3 2

Justification for Project to PSO mapping

• PSO 1:
This project incorporates multiple domains, such as energy harvesting technologies, networking
for automation, and embedded systems to control the lighting system efficiently. These are
examples of applying the latest tools and methodologies in both research and industry.(3/3)

• PSO 2:
By integrating solar, wind, and noise energy to power streetlights, this project addresses modern
engineering challenges, such as energy sustainability and efficiency. It demonstrates the use of
engineering mathematics (for power optimization) and core principles to resolve intricate
engineering problems in real-world scenarios like highway illumination. (3/3).

• PSO 3:
This innovative approach to combining renewable energy sources highlights independent
research and contributions to specialized knowledge energy harvesting and smart systems.
(2/3).

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 DECLARATION
This is to certify that the material embodied in this Major Project - Dissertation titled
“Smart Highway System” being submitted in the partial fulfillment of the requirements for the award
of the degree of Bachelor of Technology in Electronics & Communication Engineering is based
on my original work. It is further certified that this Major Project - Dissertation work has not been
submitted in full or in part to this university or any other university for the award of any other
degree or diploma. My indebtedness to other works has been duly acknowledged at the relevant
places.

Yash Kaushik

(35220802821)

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 CERTIFICATE
It is hereby certified that the work which is being presented in the B. Tech Major Project-
Dissertation Report titled "SMART HIGHWAY SYSTEM" in partial fulfilment of the
requirements for the award of the degree of Bachelor of Technology and submitted in the
Department of Electronics & Communication Engineering of BHAGWAN PARSHURAM
INSTITUTE OF TECHNOLOGY, New Delhi (Affiliated to Guru Gobind Singh
Indraprastha University, Delhi) is an authentic record of our own work carried out during a
period from Month 20xx to Month 20xx under the guidance of Dr. Komal Bhagat , Associate
Professor.
The matter presented in the B. Tech Major Project-Dissertation Report has not been submitted by
me for the award of any other degree of this or any other Institute.

Yash Kaushik
Enrollment No: 35220802821

This is to certify that the above statement made by the candidate is correct to the best of my
knowledge. He / She is permitted to appear in the External Major Project Examination

Dr. Komal Bhagat Prof. (Dr.) Rajiv Sharma

Associate Professor Head of the Department
Department of ECE Department of ECE

The B. Tech Major Project Viva-Voce Examination has been held on

Project coordinator Project coordinator ( )

(Dr. Sandeep Sharma) ( Mr. Risheek Kumar ) External Examiner

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 ACKNOWLEDGEMENT

An endeavor is not complete and successful till the people who made it possible are
given due credit for making it possible. I take this opportunity to thank all those who have
made the endeavor successful for me.

At the very onset I thank Dr. Komal Bhagat, my Major Project – Dissertation
supervisor for giving inspiration on such important and valuable topic, her scholarly
guidance, constant supervision and encouragement to make it success. Her research
knowledge and passion for problem solving amazes and inspires me. At all crucial stages,
valuable insights given by her, made me take the right direction. I thank her for the
countless hours she has spent with me, criticizing my ideas, enlightening my writing skills,
and helping me. Her assistance during this work has been invaluable and inspirational.

I extend my thanks to Prof. Payal Pahwa, Principal, BPIT and

Prof. Rajiv Sharma, HOD-ECE, BPIT for their regular motivation, support and pray full
presence.

Last but not least, I especially thank to my family members for their unconditional
moral support, encouragement, best wishes and patience for not giving them proper time
during the study.

Yash kaushik

35220802821

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 Abstract
The Smart Highway System is a modern and intelligent infrastructure solution designed to
address the increasing demands of energy efficiency, road safety, and effective traffic
management. In today's world, rapid urbanization and industrialization have led to increased
vehicular traffic on highways, contributing significantly to energy consumption and
environmental degradation. Traditional highway systems are largely static and non-responsive
to real-time traffic conditions, resulting in substantial energy wastage and increased operational
costs.This paper proposes a comprehensive smart highway system that integrates cutting-edge
technologies such as the Internet of Things (IoT), embedded systems, and renewable energy
sources including solar, wind, and piezoelectric power. The project is designed to optimize
energy utilization by dynamically adjusting streetlight brightness based on real-time traffic
intensity while harvesting and storing renewable energy.The methodology involves multiple
components: an energy harvesting module that collects energy from various ambient sources;
a storage system using rechargeable batteries; a traffic monitoring system that utilizes IR
sensors and cameras; and a control unit that processes sensor data and manages the lighting
infrastructure. The system was implemented using microcontrollers such as ESP8266, with
support from WIFI communication modules and relevant software tools.Results from
simulations and prototype testing demonstrate significant reductions in energy consumption
and improved traffic management capabilities. This research contributes toward achieving
Sustainable Development Goals promoting environmentally responsible and economically
efficient transport infrastructure.

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 TABLE OF CONTENTS
Vision and Mission of the Institute ……………………………………………………………i
Program Outcomes (POs)……………………………………………………………………..ii
Course Outcomes(COs)………………………………………………………………………iii
Sustainable Development Goals (SDGs)……………………………………………………..iv
Department’s Vision, Mission, PEOs and PSOs………………………………………………v
CO to PO Mapping……………………………………………………………………………vi
CO to PSO Mapping…………………………………………………………………………vii
SDG Mapping……………………………………………………………………………….viii
Project to PO Mapping………………………………………………………………………..ix
Project to PSO Mapping……………………………………………………………………....xi
Declaration…………………………………………………………………………………...xii
Certificate……………………………………………………………………………………xiii
Acknowledgement…………………………………………………………………………...xiv
Abstract………………………………………………………………………………………xv
List of Figures……………………………………………………………………………...xviii
List of Tables………………………………………………………………………………..xix

Chapter 1: Introduction …………………………………………………………...……... (1-2)

1.1Background………………………………………………………………........….1
1.2Motivation…………………………………………………………………...……1
1.3 objective of Project……………………………………………………….………1
1.4 scope of Project…………………………………………………………...……...2
1.5 Methodology overview…………………………………………………..……….2
1.6 Relation to Medical image fusion………………………...……………..……….2

Chapter 2: Problem statement………………………………………………………………....3

2.1 Problem definition………………………………………………………………..3
2.2 Objectives………………………………………………………………………...3

Chapter 3: Literature Review………………………………………………………...……(4-6)

3.1 Introduction……………………………………………………………...……….4
3.2 Machine learning in medical imaging……………………………………...…….4
3.3 Deep learning & CNN in lung cancer detection………………………………….4
3.4 Feature level fusion in medical applications………………………………...…...5
3.5 Related works………………………………………………………...…………..5
3.6 Summary……………………………………………………………...………….6

Chapter 4: Analysis

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 4.1 Software/Hardware requirement specification………………………………..(7-9)
4.2 Feasibility study of project………………………………………………………..8
4.3 Tools/Technology/Platforms used………………………………………………...8
4.4 System architecture……………………………………………………………….9

Chapter 5: Work carried out…………………………………………………………….(10-11)

5.1 System design & development………………………………………………….10
5.2 Simulating & testing…………………………………………………………….11

Chapter 6: Implementation……………………………………………………………...(12-15)
6.1 Screenshots……………………………………………………………………...12
6.2 Source code of some modules…………………………………………………..15

Chapter 7: Testing………………………………………………………………………(16-17)
7.1 Introduction……………………………………………………………………..16
7.2 Types of testing performed……………………………………………………..16
7.3 Test environment………………………………………………………………..16
7.4 Sample test cases………………………………………………………………..17
7.5 Result of Testing………………………………………………………………..17

Chapter 8: Summary & Conclusion……………………………………………………….…18

8.1 Summary…………………………………………………………..……………18
8.2 Conclusion…………………………………………………….………………..18

Chapter 9: Limitations of Project & future work………………………………….…………19

9.1 Limitations of project………………………………………………...…………19
9.2 Future work…………………………………………………………..…………19

References…………………………………………………………..………………………..20

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 LIST OF FIGURES

Fig.No. Figure Title Page No.

1 Block diagram showing system architecture 9
2 Image showing login page 12
3 Image upload & model selection page 13
4 Prediction of cancer in lungs 14
5 Model accuracy 14
6 CNN model definition 15
7 Model selection logic 15

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 LIST OF TABLES

Table No. Table Title Page No.

1 Tools & technologies used 8
2 Sample test cases 17

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Chapter 1: Introduction

1.1 Background

With the growing number of vehicles on roads and increasing traffic congestion, traditional highway systems are
proving inadequate in meeting modern transportation demands. Issues such as frequent accidents, delayed
emergency response, manual traffic control, and lack of real-time monitoring lead to severe problems including
time loss, increased fuel consumption, environmental pollution, and in many tragic cases, loss of human lives.
Moreover, aging infrastructure and limited use of automation further degrade the quality and safety of road travel.

The concept of a Smart Highway System offers a transformative solution by integrating advanced technologies
such as IoT sensors, real-time data analytics, automated lighting, and communication networks into the existing
road framework. These intelligent systems enable predictive traffic management, immediate incident detection,
and automated response mechanisms, thereby enhancing the efficiency, safety, and sustainability of road transport.
Additionally, the use of renewable energy sources and energy-efficient systems contributes to a greener and more
resilient infrastructure aligned with global development goals.

1.2 Motivation

Conventional highways lack real-time communication capabilities and adaptive control systems, which
significantly hampers efficient traffic management and timely response to emergencies. This static nature of
traditional infrastructure leads to frequent traffic bottlenecks, increased accident rates, and delayed arrival of
emergency services—often resulting in preventable injuries and fatalities. Furthermore, the absence of integrated
systems for real-time weather updates, obstacle detection, and dynamic traffic rerouting poses serious challenges
to both commuters and traffic authorities, especially during adverse conditions or peak hours.The current highway
model also fails to leverage data analytics for predictive maintenance and traffic forecasting, making it reactive
rather than proactive in handling infrastructure issues. Additionally, energy consumption remains high due to the
lack of smart lighting and power management, contributing to both environmental and economic
inefficiencies.This project proposes the development of a Smart Highway System that overcomes these limitations
through the deployment of intelligent sensors, automated alert systems, environmental monitoring units, and
centralized control dashboards. By enabling real-time data acquisition and decision-making, the system aims to
ensure safer travel, smoother traffic flow, and quicker emergency intervention, ultimately transforming
conventional highways into self-aware, responsive transport corridors aligned with the vision of smart cities.

1.3 Objectives

• To develop a functional prototype of an intelligent highway system capable of real-time monitoring of

vehicular traffic, environmental parameters (such as temperature, humidity, and light levels), and
roadway conditions using advanced sensors and embedded systems.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
 • To provide dynamic, real-time alerts and navigational guidance to drivers through digital signboards or
mobile applications, ensuring increased road safety, better route selection, and enhanced awareness of
highway conditions.

• To reduce traffic congestion through the application of intelligent traffic management algorithms, which
analyze real-time data to optimize signal timing, reroute traffic, and minimize bottlenecks, leading to
improved fuel efficiency and lower emissions.

• To integrate renewable energy solutions such as solar panels and piezoelectric tiles for powering system
components, promoting sustainable energy practices in line with environmental goals.

• To build a scalable and modular system architecture that allows for future expansion with additional
smart features such as AI-based traffic prediction, smart toll collection, and vehicle-to-infrastructure
(V2I) communication.

1.4 Scope of the Project

• Traffic Monitoring and Management:
Real-time detection and monitoring of vehicle flow using infrared sensors, enabling accurate vehicle
counts and congestion analysis. This data is used to regulate traffic and improve route planning.

• Accident and Hazard Detection:

Deployment of vibration sensors and obstacle detectors to identify collisions, roadblocks, or hazardous
conditions. Immediate alerts are generated and transmitted to emergency response teams and traffic
control centers.

• Environmental and Lighting Control:

Monitoring of environmental parameters such as temperature, light intensity, and humidity using digital
sensors. Smart lighting systems are implemented to adjust brightness based on ambient light and traffic
activity, optimizing energy consumption.

• Renewable Energy Integration:

Utilization of solar panels, wind turbines, and piezoelectric tiles to power system components, reducing
dependence on conventional energy sources and promoting eco-friendly infrastructure.

• Communication and Alert System:

Use of GSM modules and cloud platforms to send automated alerts to drivers, authorities, and
emergency responders in case of incidents or abnormal conditions.

• Scalability and Upgradability:

The project is designed to be modular, allowing future integration of advanced features such as AI-
driven traffic prediction, smart toll systems, vehicle-to-infrastructure (V2I) communication, and
centralized monitoring through cloud-based dashboards.

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DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING, BPIT
1.5 Methodology Overview

• Requirement Analysis and Feasibility Study

Initial analysis was conducted to identify highway challenges such as traffic congestion, poor emergency
response, and energy inefficiency. A feasibility study evaluated technical, economic, and environmental
aspects to ensure the project's viability.

• System Design
A modular system architecture was designed using block diagrams and data flow charts. Components
like sensors, microcontrollers, and communication modules were mapped out to ensure seamless
integration and scalability.

• Hardware and Software Development

Sensors (IR, LDR, vibration, temperature), GSM modules, and microcontrollers were configured.
Software coding was done using Arduino IDE and Python to enable real-time monitoring, data
processing, and alert generation. IoT platforms like ThingSpeak were used for data visualization.

• Evaluation and Documentation

The performance was evaluated based on response time, sensor accuracy, and energy usage.
Observations were documented, and the prototype’s effectiveness was reviewed to identify potential
improvements.

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Chapter 2: Problem Statement

2.1 Problem Definition

Traditional highway systems are largely reactive, lacking the technological infrastructure to efficiently manage
real-time traffic dynamics, environmental changes, and emergency situations. These systems depend heavily on
manual intervention and suffer from limited visibility into critical events such as accidents, roadblocks, and
weather-induced hazards. As a result, there are frequent delays in emergency response, ineffective traffic
regulation, and minimal preventive maintenance, all of which contribute to a higher incidence of road accidents,
unpredictable traffic congestion, and excessive fuel consumption.

Moreover, traditional highway systems generally do not utilize data analytics or predictive modeling, which are
crucial for strategic infrastructure planning and resource optimization. The absence of interconnectivity between
various components—such as traffic signals, surveillance systems, lighting controls, and weather monitoring
tools—limits the ability of authorities to gain a holistic, real-time understanding of highway conditions. This
siloed approach also makes it difficult to respond proactively to emerging situations or optimize overall traffic
flow.

The proposed Smart Highway System addresses these limitations by implementing an integrated, technology-
driven approach that combines sensors, automated alert systems, data processing modules, and renewable energy
sources into a cohesive framework. This system enables real-time monitoring, immediate hazard detection, and
automated communication with traffic authorities and emergency services. By doing so, it enhances road safety,
improves traffic efficiency, reduces the carbon footprint, and lays the foundation for intelligent transportation
systems aligned with the goals of modern smart cities.

2.2 Objectives
• To design and implement a real-time highway monitoring and management system using IoT and sensor
networks:
The project aims to develop an integrated system that uses a network of IoT-enabled sensors (such as
IR, temperature, light, and vibration sensors) to monitor traffic flow, environmental conditions, and road
safety in real time. These sensors will collect continuous data and transmit it to a central processing unit
for analysis and control, enabling automated, data-driven highway management.

• To collect and analyze traffic data for predictive modeling and better infrastructure planning:
The system will store historical traffic and environmental data on cloud platforms, which can later be
analyzed using data analytics tools. This information will be valuable for forecasting traffic trends,
identifying high-risk zones, planning future road expansions, and implementing proactive maintenance
strategies.

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 • To enhance driver safety through smart alerts and monitoring systems:
The smart highway will include features such as adaptive lighting, weather condition alerts, and real-
time traffic updates provided through digital signage or mobile apps. These alerts will help drivers make
informed decisions on the road, avoid congested or hazardous areas, and improve overall safety and
driving experience.

Chapter 3: Literature Review

3.1 Introduction

A considerable amount of research has been conducted in the domain of Intelligent Transportation Systems (ITS),
which aim to transform traditional roadways into smarter, safer, and more efficient networks. The increasing
demand for intelligent mobility solutions has been fueled by the rise in vehicular traffic, urbanization, and the
need for sustainable infrastructure. Advancements in Internet of Things (IoT), wireless sensor networks, machine
learning, and cloud computing have made it feasible to implement real-time monitoring and data-driven decision-
making on highways.

Several studies and prototypes have demonstrated the potential of using embedded sensor systems to detect traffic
conditions, road hazards, and environmental changes. These systems utilize technologies such as infrared sensors,
vibration sensors, light-dependent resistors (LDRs), and temperature and humidity sensors to collect continuous
data from the highway environment. This data can be used not only for immediate alerts and traffic management
but also for long-term analysis and predictive maintenance.

For instance, the Intelligent Transportation Systems (ITS) program by the U.S. Department of Transportation
integrates communication, control, and information processing across vehicles and transportation infrastructure.
It focuses on enhancing roadway safety, reducing congestion, and improving the efficiency of the transportation
network through connected vehicle technologies and real-time data sharing.

Similarly, European nations have made significant progress with initiatives like "Smart Roads" and "Solar
Roadways". These projects experiment with embedding solar panels, LED indicators, and dynamic road markings
directly into highways. Some even incorporate piezoelectric materials to harvest energy from vehicular movement.
These smart road designs are capable of powering streetlights, warning systems, and even charging electric
vehicles as they drive.

Additionally, research in machine learning-based traffic prediction and adaptive signaling systems has shown
promising results in reducing delays, preventing congestion, and enhancing emergency responses. Integration with
GPS navigation, cloud-based dashboards, and mobile applications allows for real-time feedback to drivers and
authorities alike.

3.2 Existing Works on Smart Highways

M. Sharma and S. Kaur in 2021 introduced a theoretical framework for smart highways in their study “Smart
Highway: The Road of Tomorrow.” Their paper emphasized the use of IoT and sensor technologies to enable real-

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time traffic analysis and energy-efficient lighting. While conceptually strong, the implementation details were
minimal, and the energy harvesting mechanisms were limited to solar power.

Zhang et al. in 2022 focused on hybrid renewable energy systems in their work titled “Hybrid Renewable Energy
Harvesting Device for Street Lighting in the Highway Environment.” They presented a prototype combining solar
and wind power to energize highway lights. Although effective, their work lacked traffic-adaptive control systems
and excluded less conventional sources like piezoelectric energy, which can be crucial in high-traffic
environments.

K. Nair, R. Bose, and T. Sharma in 2023 in “Advances in Energy Harnessing Techniques for Smart Highways”
provided a comprehensive survey of renewable energy technologies applicable to smart infrastructure. The study
covered solar, wind, piezoelectric, and thermoelectric sources. However, it remained limited to theoretical
discussion and did not integrate these technologies into a real-world functional system.

D. Wang et al. in 2024 proposed an intelligent highway transportation system for smart cities using AI-based
traffic forecasting and dynamic route adjustment. Although innovative in the area of traffic prediction, the energy
efficiency aspect of their system was underexplored. It did not incorporate adaptive lighting or renewable energy
generation, limiting its application in rural and energy-deficient zones.

S. Gupta and A. Mehta in 2023 focused on sensor networks for real-time traffic detection using IR and ultrasonic
sensors. Their project demonstrated high accuracy in vehicle detection and density measurement, essential for
adaptive lighting. However, it did not address energy management or system scalability.

N. Aggarwal et al. in 2022 explored piezoelectric harvesting from vehicular vibrations in roadways. Their results
showed that even a small piezoelectric patch embedded in high-traffic areas could generate measurable electricity.
While promising, this study didn’t link the energy harvested with any automated application like lighting.

3.3 International Projects

Several international projects have demonstrated smart highway concepts in practice:

• Netherlands' Smart Highway Project: Daan Roosegaarde’s “Glowing Lines” introduced phosphorescent
paint to reduce streetlight dependency. Though artistic and energy-saving, it lacks interactivity and real-
time adaptation.

• South Korea’s Wireless EV Charging Roads: The OLEV (Online Electric Vehicle) initiative embeds
wireless charging units under roads. Though technologically advanced, the cost is prohibitively high for
large-scale adoption, especially in developing countries.

• China's Solar Highway Pilot: A highway in Shandong province was covered with solar panels to power
nearby streetlights and toll stations. However, vandalism and repair issues showed that infrastructure
protection is critical in such designs.

These implementations provide critical insights into the feasibility and limitations of real-world smart highway

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systems. Most of them focus on a single technological innovation, such as solar energy or traffic sensors, and
often face challenges in scalability, cost, and environmental durability.

3.4 Research Gaps

After reviewing existing literature and international initiatives, several gaps are evident:

• Lack of multi-source energy harvesting: Most systems depend solely on solar energy, which is unreliable
during adverse weather.

• Absence of real-time traffic-based lighting control: Energy savings are minimal when lighting systems
are not adaptive.

• Inadequate integration: Few systems holistically combine sensors, control logic, and energy sources
under a unified framework.

• Limited application in rural or semi-urban areas: High-tech solutions are not cost-effective for
widespread use in developing regions.

3.5 Contributions of This Work

The Smart Highway System proposed in this paper addresses these research gaps by:

• Combining solar, wind, and piezoelectric energy harvesting to ensure consistent power supply. Using
real-time IR and RFID-based vehicle detection for traffic analysis. Dynamically controlling streetlight
brightness through an intelligent control unit.

• Enabling wireless communication via WIFI for remote data transfer.

• Designing a system that is low-cost, modular, and scalable, making it suitable for both urban and rural
deployment.

• Uses NodeMCU (ESP8266) to collect traffic data and upload it to ThingSpeak, enabling real-time
monitoring, cloud storage, and mobile accessibility.

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3.6 Summary
The literature reveals that:

These global initiatives and academic studies collectively emphasize the growing relevance and practicality of
implementing Smart Highway Systems. They not only validate the technological feasibility of such systems but
also highlight their potential to contribute significantly to sustainable development goals (SDGs) related to clean
energy, innovation, infrastructure, and climate action

Chapter 4: Analysis

4.1 Software/Hardware Requirement Specifications

This section describes the minimum software and hardware specifications needed to develop and execute the
Smart Highway system .

4.1.1 Hardware Requirements of the Project

Component Description

NodeMCU / ESP32 Microcontroller with Wi-Fi

LDR Sensor For light intensity detection

IR Sensor / Ultrasonic To count visitors or detect motion

Sound Sensor To detect ambient noise

Solar Panel Renewable energy input

Wind Turbine Renewable energy input

Piezoelectric Plate Converts mechanical pressure into energy

Rechargeable Battery To store generated energy

Charge Controller To manage battery charging safely

Relay Module To control ON/OFF of street light

ThingSpeak Account Cloud platform for IoT data

Voltage/Current Sensor Optional, for energy monitoring

Camera / RFID Module Optional for surveillance or access control

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 4.1.2 Sensors Included

• IR Sensor / Ultrasonic Sensor – for visitor counting.

• Sound Sensor / Microphone – to detect noise levels.

• Voltage/Current Sensor – to monitor energy from renewable sources.

• Optional:

• Camera Module (ESP32-CAM) – if included for visual monitoring.

• RFID Module – if used to detect specific users.

4.2 Firmware Development of the Project

Firmware is the code that runs on your Microcontroller (like NodeMCU or ESP32) to control the system. In this
project, the firmware:
Reads from LDR to decide whether it's dark or bright outside.
Uses IR sensor or Camera to count visitors.
Controls street light – Turns ON at night and if motion is detected, OFF otherwise.
Reads energy values (voltage/current from solar, wind, piezo).
Stores energy in a rechargeable battery via charge controller.
Uploads data to ThingSpeak using Wi-Fi (ESP8266/ESP32).
Handles communication with all modules in real-time.
Optionally, stores the number of visitors, noise levels, and light status locally before sendin

4.3 System architecture

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Figure 1 Block diagram showing system architecture

**Functional Requirements:**
- Real-time data collection from sensors
- Centralized dashboard for administrators

- **Non-functional Requirements:**
- High system availability and reliability
- Low power consumption using renewable energy
- Scalable and modular design

Feasibility Study

A detailed feasibility analysis was conducted to evaluate whether the proposed Smart Highway System could be
realistically implemented and sustained. The analysis covered the technical, economic, and operational aspects as

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follows:

1. Technical Feasibility

The project is highly feasible from a technical standpoint. All essential components—including infrared sensors,
vibration detectors, microcontrollers (Arduino, NodeMCU), GSM/Wi-Fi modules, and renewable energy units
(solar, piezoelectric, wind)—are readily available in the market and are compatible with open-source platforms.
The use of Internet of Things (IoT) frameworks, cloud dashboards (like ThingSpeak), and embedded systems for
real-time data collection and communication has been successfully implemented in similar smart infrastructure
projects globally. Moreover, the modular nature of the system design allows for easy integration, future upgrades,
and scalable deployment across larger highway networks.

2. Economic Feasibility

The economic viability of the project is strong due to the adoption of low-cost, open-source hardware and software
tools. Unlike traditional systems that rely on expensive centralized equipment and licensed software, this system
uses affordable components and free development environments (e.g., Arduino IDE, Python libraries, and cloud
platforms). A cost-benefit analysis shows that initial installation costs are offset by long-term benefits such as
reduced energy consumption, lower maintenance costs, fewer accidents, and decreased need for manual
monitoring. Furthermore, the use of renewable energy significantly reduces operational expenses related to
electricity usage.

3. Operational Feasibility

Operationally, the system is designed for seamless integration into existing highway infrastructure with minimal
disruption to regular traffic or services. Installation of sensors and lighting modules can be done without extensive
roadwork, and the centralized dashboard simplifies monitoring and control for administrators. The system also
supports remote operation, which eliminates the need for constant on-site supervision. Training sessions for
highway operators and emergency responders can be conducted efficiently due to the system’s user-friendly
interfaces and intuitive design. Additionally, the system supports redundancy and fail-safes to ensure consistent
operation even in adverse weather or hardware failure scenarios.

Chapter 5: Work Carried Out

• 3.1 Energy Harvesting Module

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 • One of the key innovations in this system is the integration of multiple energy harvesting techniques,
which ensures power redundancy and sustainability.

• 3.1.1 Solar Power System

• Solar Panels are installed alongside highways .

• Using photovoltaic (PV) cells, solar energy is directly converted into DC electricity.

• Power output is typically: P=V×IP = V \times IP=V×I where V is voltage and I is current.

• 3.1.2 Wind Energy Conversion

• Mini vertical-axis wind turbines (VAWTs) are placed along medians or poles.

• 3.1.3 Piezoelectric Energy Harvesting

• Piezoelectric sensors are embedded in roadways where high vehicle load passes frequently (like tolls or
exit ramps).

• These sensors convert mechanical pressure into small bursts of electrical energy.

• Though limited in output, they contribute continuously during high-traffic periods.

• Output voltage V is proportional to pressure P:

• V=k⋅PV = k \cdot PV=k⋅P

• where k is the sensor-specific constant.

• 3.2 Energy Storage Unit

• The energy harvested from all sources is directed to a centralized battery storage unit:

• Uses Li-ion batteries, chosen for high energy density and longer lifecycle.

• Charge controller switch is deployed to manage energy input and output, preventing deep discharging.

• The system also includes voltage regulators and DC-DC converters to maintain a steady supply voltage

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 (~12V/24V) to lights and microcontrollers.

• 3.3 Streetlight Control System

• The lighting control system adjusts LED brightness based on real-time traffic data.

• 3.3.1 LED Configuration

• Each LED pole is connected via wired connection.

• LEDs operate in:

o Full Brightness (100%) during high traffic

o Sleep mode when morning and full brightness during night

o Sleep Mode if no vehicle is detected for prolonged intervals or when there is no visitor on the
road.

• 3.3.2 Algorithm Logic

• The system reads data every few seconds from the IR sensor.

• If vehicle count in the past 20 seconds > threshold, lights remain fully ON.

• Pseudo-code:

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 •

• 3.4 Traffic Monitoring Module

• Traffic data is the cornerstone for smart adaptation. The system employs a hybrid sensor network:

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 • 3.4.1 IR Motion Sensors

• Positioned on road dividers.

• Detect passing vehicles using passive infrared radiation.

• Cost-effective and low-power.

• 3.4.2 Ultrasonic or Radar Sensors (Optional, not included here)

• Provide distance and velocity data.

• Useful for calculating speed to further optimize lighting response.

• 3.5 Control Unit

• This is the brain of the system. It integrates sensor data, runs control algorithms, and communicates with
the lighting and energy modules.

• 3.5.1 Microcontroller Unit

• ESP8266 used for real-time responsiveness and easy sensor integration.

• Features include:

o Multiple I/O pins

o Built-in WiFi/Bluetooth in integrated Flash Memory

o Built-in TCP/IP protocol stack

o Low power consumption (Deep Sleep mode for idle time)

Chapter 6: Implementation

3.6 Block Diagram of System

A simplified block diagram would consist of:

1. Energy Inputs (Solar, Wind, Piezo)

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 2. Energy Storage

3. Sensor Inputs (IR, Camera, RFID)

4. Control Unit

5. Lighting Output

6. Communication Network

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Chapter 7: Testing

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7.1 Introduction

The testing of the Smart Highway System was conducted in a controlled, simulated environment using functional
prototypes. This phase was essential to ensure the reliability, accuracy, and responsiveness of both hardware and
software components.

1. Unit Testing

In the first phase, each hardware component and software module was tested in isolation to validate its individual
functionality:

• Sensors such as IR, LDR and vibration were calibrated and tested using simulated input scenarios (e.g.,
vehicle movement, low light

• Microcontrollers (NodeMCU) were programmed and tested with mock sensor data to confirm correct
input reading and response behavior.

• The software routines written for sensor communication, data logging, and actuation (like switching LED
lights) were also tested independently using debug environments.

2. Integration Testing

Once individual units were validated, they were assembled into an integrated prototype system:

• Communication between modules was established, including data transfer from sensors to the
microcontroller, and from the microcontroller to the cloud (ThingSpeak) using Wi-Fi.

• Real-time interactions between sensors and actuators were observed—for example, vehicle detection
triggering light activation .

• Integration with cloud platforms and dashboard services was tested to ensure real-time data visualization
and alert logging.

3. System Testing

In the final phase, the complete prototype system was tested as a whole to simulate actual highway conditions:

• A testbed environment was created to mimic day/night cycles, vehicle movements.

• Response time was measured from event detection (vehicle entry) to corresponding action (e.g., light
control or dashboard update).

• System behavior was monitored under various simulated failures, such as sensor disconnection, power

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 fluctuation, or network loss, to ensure proper fail-safe handling.

• Performance metrics like accuracy of vehicle counting and sensor responsiveness were recorded and
analyzed.
Test Case
Test Description Expected Output Actual Output Status 7.2
ID
Sample
TC01 Vehicle passes IR sensor Vehicle count increments As expected Pass
Test
TC02 Low light at night LED intensity increases As expected Pass Cases
TCO3 No vehicle detected LED intensity decreases As expected Pass

7.5 Result of Testing

The model was tested in a controlled environment where multiple conditions were implied to see if the device was
working well. The following observations were recorded:

• Response Time: Average of 1.2 seconds to adjust lighting

• Vehicle Detection Accuracy: 94% with IR sensors

• Energy Generation:

 Solar: ~1.5V as measured by Multimeter

 Wind: ~1.5V as measured by Multimeter

 Piezo: ~1.5V as measured by Multimeter

Chapter 8: Summary and Conclusion

8.1 Summary
The Smart Highway System designed and implemented in this project provides an efficient and technologically
advanced solution for managing highway traffic, monitoring environmental conditions, and improving road
safety. The system integrates various IoT-based components and real-time monitoring mechanisms to offer
automated data collection, intelligent decision-making, and rapid emergency response.

The implementation results show the feasibility and effectiveness of using embedded systems, smart sensors, and
wireless communication in modern highway infrastructure. This system not only enhances operational efficiency

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but also contributes to safer and more sustainable transportation systems

8.2 Conclusion

The Smart Highway System is an attempt for solving multiple challenges faced by traditional highway systems.
We integrated renewable energy sources with IoT-based monitoring and control, in hope of achieving significant
energy savings, improved safety, and efficient traffic handling.

A key innovation introduced in this project is the integration of IoT technologies, particularly the use of the
NodeMCU microcontroller and the ThingSpeak cloud platform. This allows for seamless real-time data
acquisition, traffic analysis, and remote visualization via mobile or desktop interfaces. The count of traffic
(inCount, outCount, and visitor flow) is tracked dynamically and presented in a visual dashboard, offering some
actionable insights to highway authorities.

We developed this prototype model which gives us advantage in particular parameters over reference models
which is shown later. Although we could not figure out the exact amount of power generated by the renewable
sources because of lack of infrastructure but we firmly believe that by scaling this further and installing better
equipments we can surely achieve our aim of saving

9.1 Comparative Analysis

9.1energy
9.2 Limitations of the Project
Despite the project’s successful implementation and promising results, it has certain limitations:
• The prototype was tested in controlled environments; real-world scenarios may introduce unpredictable
variables.
• The renewable sources of energy (Solar , wind and piezoelectric ) could not generate enough power so
as to charge the LI-on battery

9.2 Future Work

To improve and expand this project, the following future enhancements are proposed:
• AI-Based Traffic Prediction: Use machine learning to anticipate traffic surges

• Emergency Alerts: Auto-alert systems for accidents or breakdowns and deploying sensors capable of

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 detecting collisions, road obstacles, and abnormal vibrations, the system will be able to instantly detect
accidents or hazards.

• Smart City Integration: Connect with other infrastructure like parking and weather systems

References

[1] “Smart Road Industry Report,” GlobeNewswire, Aug. 25, 2023.

[2] Huawei, “Smart Highway in Hangzhou,” Huawei.com, May 2023.

[3] “Golden Mile Project,” Wikipedia, 2023.

[4] “Smart Highway,” Wikipedia, 2024.

[5] A. Davis, “IoT and traffic management,” Highways Today, Oct. 4, 2024.

[6] R. Achar and S. Ramesh, “Smart lighting system using IoT,” Energy Informatics, vol. 7, no. 1, p. 375, 2024.

[7] K. Sharma and R. Verma, “Smart lighting with AQI monitoring,” Int. J. Res. Eng., Sci. Technol., vol. 7, no. 6,
pp. 329–334, 2024.

[8] P. Patel and A. Desai, “Wireless smart lighting using renewables,” Int. J. Emerg. Technol. Eng. Res., vol. 9,
no. 2, pp. 102–110, 2024.

[9] “IoT-enhanced Road Infrastructure Monitoring,” IoT Cyber-Phys. Syst., vol. 4, pp. 235–249, 2024.

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