Nano Tree Based Charging System Using IoT

Sharanabasava

, Siddesh H M

Yogesh Y R

, Yuvaraj H

and Ganesha G C

Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering,

Bangalore 560078, Karnataka, India

Keywords: Arduino, Sensors, Artificial Tree, Carbon Paper, Embedded System.

Abstract: This Nano tree design based on biomimetic technology is offering new creative ideas to capture the

environmental energies, like solar energy, wind and convert them into electricity. The artificial tree will

exploit all the possible thin-film deposition, thermophotovoltaic materials to maximize energy conversion;

with its 3D texture of the surface of the leaf, the Nano tree captures solar radiation efficiently. Energy

conversion is, therefore, much more efficient than in traditional solar panels. Additionally, we introduce a

type of pollution detection system using an MQ gas sensor and Arduino embedded in the artificial tree to

monitor harmful gases and absorb CO2 through carbon paper. For the urban traffic congestion problem, we

proposed a density-based dynamic traffic signal management system. IR sensors and Arduino control the

signal, adjusting the time according to the real-time traffic density in order to optimize traffic flow. We address

key global issues such as innovations in renewable energy, pollution-free life, and overcoming traffic

congestion through ecologically friendly solutions, efficiency, and adaptability.

1 INTRODUCTION

This is the Intelligent Nano Tree-Based Charging

System for Smart Traffic Management using IoT-the

innovative solution that will come to solve problems

of urbanization and transportation. Renewable energy

harvesting, IoT technology, and smart traffic

management all are involved in building this

sustainable, efficient, and intelligent method. The key

challenge is to optimize the utilization of energy,

decongest the traffic, and work toward improving

public safety through the use of renewable sources of

energy, such as solar and wind power; monitor

generation and usage of energy through IoT; smart

traffic management through the usage of IR sensors;

and optimize the streetlight by employing LDR and

IR sensors.

Key constituents of the system include harvesting of

renewable energies using solar panels as well as wind

turbines, an IoT-based platform for monitoring and

https://orcid.org/0009-0001-9133-4342

https://orcid.org/0009-0009-1155-8986

https://orcid.org/0009-0006-1520-7946

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https://orcid.org/0009-0002-3944-1922

control, Thing Speak, in addition to IR sensor inputs

in intelligent traffic management based on real-time

density perception and optimization in the signalling

timings along with automated street lighting through

LDR sensors detecting daylight and IR sensors that

detect objects. It provides several advantages: from

energy efficiency to the reduction of congestion,

improved public safety, sustainability with respect to

the environment, and even real-time data analytics.

Touching applications of sustainability of nature,

public safety, urban planning, and transport

management, the project thus introduces a revolution

into the urban infrastructure as eco-friendly, efficient,

and intelligent transport systems of the modern city.

Its success will lead to model urban development and

place it as a highly important initiative for creating

sustainable and liveable cities.

Sharanabasava, , H M, S., H, Y., Y R, Y. and G C, G.

Nano Tree Based Charging System Using IoT.

DOI: 10.5220/0013577600004639

In Proceedings of the 2nd International Conference on Intelligent and Sustainable Power and Energy Systems (ISPES 2024), pages 103-107

ISBN: 978-989-758-756-6

103

2 LITERATURE REVIEW

Adaptive Control of Streetlights Using Optimization

of Energy Muhammad Asif, Sarmad Shams, Samreen

Hussain, Jawad Ali Bhatti, Munal Rashid MDPI

2022. In this paper the proposed system. s to develop

a adaptive control system of street light and decreases

energy resources. Many researchers have proposed a

number of methodologies and ideas to reduce the

energy wastage of the street lights and also

highlighted the ways to make them smarter.".

"Hybrid Powerplant Using Solar and Wind

Energy Ahmad Sahru Romadhon and Tri

Widyaningrum, ICST 2022. In this paper, the

technology uses both solar and wind energy as a

hybrid solar energy system, the utilization of solar

energy which utilizes cell and utilization of wind

energy is utilizes for generating the electricity.".

"Automatic Traffic Management Scheme" This is

the most widely automatic system. It adopts a very

simple time-based system that's work on the time

interval basis, which is currently inefficient for

random and non-uniform traffic, but time. interval

Basis is very time wasting it is a fast process.

P. Sinhmar in his paper has suggested solution to

reduce the number of traffic jams with the use of IR

transmission and micro controller. Counting of

passing vehicles is done through IR transmitter, and

receiver, the decision to change the traffic delay is

made by microcontroller based on the collected

information. Such a system helps in getting accurate

statistics and thus helps in designing better traffic

signal lights.

K.M. Yousef et al (Yousef et al., 12010) in his

paper has developed an adaptive traffic control

system based on a traffic infrastructure using wireless

sensor network to control the flow of traffic. He also

developed an intelligent traffic controller to control

the operation of the traffic infrastructure supported by

WSN. It senses the traffic and dynamically changes

the traffic lights through wireless transmission. It

only adds convenience to already existing traffic light

system and not safety.

Wen in his paper has come out with a framework

for dynamic and automatic traffic light control

system. They fix RFID tags to the cars and make a

note of that number of cars, average speed, etc.

through RFID refers and store in the database by

passing the information wirelessly. That database

later acts as an input for control of the traffic signal

lights, which helps in reduction of the traffic

congestion.

Simple Traffic Management Scheme

Traffic is managed by one man only. If there are

four roads where vehicles are coming, then the man

needs to control the traffic. He has to release one by

one. The scheme uses very little manpower, and it is

not difficult to handle when there is more traffic.

3 GAPS IDENTIFIED

This project addresses a critical gap in existing

research by focusing on efficient energy utilization,

real-time implementation, and sustainable

production. Our innovative approach harnesses

electricity from a nano tree using solar panels and

wind energy, providing a sustainable power source.

The generated energy powers:

1. Intelligent street lighting systems with

monitoring capabilities

2. Automated traffic management systems based

on real-time tracking

3. Pollution control measures using carbon paper

This integrated approach demonstrates a holistic

strategy for sustainable energy production and

utilization, paving the way for smarter,

environmentally conscious urban infrastructure.

4 METHODOLOGY

This The Nano Tree-based Charging System

harnesses solar and wind energy, utilizing IoT

technology to optimize traffic management, street

lighting, and pollution monitoring. Solar panels

which extract the sunlight from the sun and wind

turbines which extract the wind from the environment

to generate electricity and stored in a battery and

monitored in real-time on ThingSpeak. The system

adjusts traffic signal timings based on vehicle density

detected by IR sensors on two roads.

1. Intelligent street lighting systems with

monitoring capabilities

2. Automated traffic management systems based

on real-time tracking

3. Pollution control measures using carbon paper

For street lighting, an LDR sensor monitors

daylight intensity, automatically turning lights off

during the day and on at night. Additionally, an object

detection sensor adjusts street light intensity

according to street activity.

A carbon paper pollution detector measures

pollution levels, displaying data on an LCD display.

This comprehensive system integrates renewable

ISPES 2024 - International Conference on Intelligent and Sustainable Power and Energy Systems

104

energy, IoT automation, and sustainable solutions for

urban development.

Key features include:

• Renewable energy harvesting

• IoT-based automation

• Real-time traffic management

• Intelligent street lighting

• Pollution monitoring and control

• Energy efficiency

• Data-driven decision making

• A microcontroller uses this data to adjust

traffic lights dynamically, giving priority to the road

with more vehicles and ensuring smoother traffic

flow.

The system also optimizes street lighting. During

the day, an LDR sensor keeps the lights off, while at

night, it turns them on automatically. Additionally, IR

sensors detect movement, ensuring that lights are

only activated when needed, conserving energy. To

address air pollution, a carbon paper-based sensor

measures pollutants like carbon monoxide or

particulate matter, with the results displayed on an

LCD screen for easy monitoring. IoT connects all

these components, allowing for centralized control

and real-time updates. This project presents an

innovative approach to tackling urban challenges

while promoting energy efficiency and sustainability.

Figure 1: Block diagram

5 APPLICATIONS

Nano Tree-Based Charging System: The IoT-enabled

innovation integrates renewable energy from both

solar panels and wind turbines. Energy so harvested

is employed to power intelligent traffic management,

ensuring that signal timings are adjusted according to

vehicle density sensed through IR sensors. LDR-

based brightness of street light is optimized for

daylight detection. It can have applications in fields

such as Intelligent Transportation Systems,

Environmental Monitoring, Public Safety, Energy

Efficiency, and Disaster Management. Industries that

will benefit from it are industries in Transportation,

Energy, Construction, Government, and Urban

Planning. Real-world implementations include city-

wide traffic management, smart highways, and street

light energy efficiency. This sustainable solution is

transforming urban landscapes, enabling enhanced

sustainability, and improving quality of life toward a

smarter and greener future.

Figure 2: Prototype

6 RESULTS

The proposed systems demonstrated significant

energy efficiency through the integration of

renewable energy sources and IoT-enabled adaptive

lighting, optimizing power consumption to meet real-

time requirements. The intelligent street lighting

system exhibited excellent adaptability to varying

climatic conditions, ensuring consistent and reliable

performance. Furthermore, the Arduino and IR

sensor-based traffic control system effectively

enhanced traffic management by improving flow and

reducing congestion through dynamic, real-time

adjustments. These results confirm the potential of

the systems to address energy and traffic challenges,

offering sustainable and intelligent solutions for

urban and remote infrastructure development.

Figure 3: Streetlights

Nano Tree Based Charging System Using IoT

105

Street lights are always in off mode during the

day, but at night, they are dim. Whenever the IR

Sensor senses a person or object near the lights, they

blow brighter.

Figure 4: Traffic monitor

Depending on the density of vehicles on both roads,

the traffic signals operate accordingly.

Figure 5: Solar panels artificial tree

An artificial tree uses solar panels, from which

most of the electricity is generated for the overall

objectives. The electricity generated from the

artificial tree will be supplied to the traffic system,

street lights, and also to the overall monitoring of the

system.

7 CONCLUSION

Nano This paper presents a comprehensive study on

an intelligent street lighting system integrated with

IoT and nano tree-based energy harvesting

technology, demonstrating its potential for energy

conservation, easy of maintenance, and improved

operational efficiency. The proposed system is

particularly well-suited on deployment in both urban

and remote areas with low traffic density, offering

significant energy savings and addressing critical

issues such as power theft. Furthermore, its ability to

adapt to unprecedented climatic changes ensures

uninterrupted functionality and reliability.

Additionally, a traffic light optimization system

using Arduino and IR sensors was designed and

developed to enhance urban traffic management. This

system effectively integrates hardware and software

components, enabling real-time traffic control and

paving the way for efficient road planning. In

conclusion, the implementation of IoT-enabled nano

tree-based charging systems, coupled with optimized

traffic control mechanisms, provides a sustainable

and intelligent approach to addressing energy,

environmental, and urban traffic challenges.

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