Smart Dual-Axis Solar Tracking System with Weather Monitoring

and Automated Panel Cleaning

A. Yasmine Begum

, K. Yashaswini

, G. Jahanavi

, D. Dinesh

, M. Uday Reddy

and Krishna Moorthy Vincent

Department of Electronics and Communication Engineering, Mohan Babu University (Erstwhile Sree Vidyanikethan

Engineering College), Tirupati, Andhra Pradesh, India

Transcendent, Energy Tech Solutions, Coimbatore, Tamil Nadu, India

Keywords: Dual-Axis Solar Tracking, Automated Panel Cleaning, Weather Monitoring, IoT Connectivity, NodeMCU

(ESP8266), UBIDOTS Platform, Light Dependent Resistor (LDR) Sensors, DC Geared Motors Etc.

Abstract: This project illustrates an advanced system which is a Smart Dual-Axis Solar Tracking System to measure

atmospheric conditions with automated panel cleaning. The project setup uses a NodeMCU (ESP8266)

microcontroller, which provides Greater IoT connectivity for real-time data visualization and control via the

UBIDOTS platform. It has four LDR (Light Dependent Resistor) to sense the sunlight direction, which helps

in adjusting the two aircraft to keep their solar panels facing the sun most of the time. The system uses

temperature, humidity, and ambient light intensity sensors in order to control environmental conditions of

LEDs and to ensure their working conditions. Based on the detected weather condition, such as a rain or dust

accumulation and the presence of the wiper or a System-controlled servo motor, an automatic cleaning

mechanism is activated. Environmental parameters and system status information are presented locally,

through LCD module. This is especially useful in varying climate conditions where maintenance is required

to maximise the performance of solar energy harvesting.

1 INTRODUCTION

Due to the increasing demand of energy globally as

well as the depletion of conventional fossil resources,

the quest for sustainable, renewable energy sources

has greatly enhanced. Solar energy is one alternative

that is abundant and sustainable. However, factors

such as sun position, environment and clean PV

modules have an overarching influence on the

performance of photovoltaic (PV) systems. By using

our dual-axis sun tracking systems along with

displayed automatic cleaning systems and

environmental monitoring, a complete approach has

been devised to enhance the harvesting of solar

energy.

Solar tracking systems are designed to adjust PV

panels to align with the sun as it moves throughout

the day in order to maximize energy capture, and

dual-axis trackers adjust on both the horizontal and

vertical axes in order to ensure optimal alignment

with the sun's path. Compared to fixed installations,

studies suggest these systems can dramatically

increase energy output. As an illustration, researchers

have shown that by employing a dual-axis solar

tracker with a cleaning system, energy efficiency is

maintained via optimal solar panel alignment and

cleanliness.

Some environmental factors that decrease the

performance of solar panels are temperature,

humidity, and dust accumulation. Soiling, or dust

deposition, can incur significant efficiency losses.

Mitigation techniques, such as automated cleaning

systems, are important to keep these systems

operating at peak performance. Research shows that

soiling recovery can be removed through the

implementation of cleaning mechanisms, which,

when combined with tracking systems, increases the

efficiency of solar energy systems. Despite the

progress made, several challenges remain in the body

of current literature:

• Environmental Flexibility: Many solar trackers

are focused on the position of the sun, but often

neglect contemporary environmental factors like

dust deposition, precipitation, and cloud cover.

Begum, A. Y., Yashaswini, K., Jahanavi, G., Dinesh, D., Reddy, M. U. and Vincent, K. M.

Smart Dual-Axis Solar Tracking System with Weather Monitoring and Automated Panel Cleaning.

DOI: 10.5220/0013908000004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 4, pages

53-61

ISBN: 978-989-758-777-1

This bug can lead to suboptimal energy

harvesting during inclement weather.

• Maintenance issues: Soiling - the accumulation of

dust and dirt on solar panels - can lead to a

dramatic decrease in efficiency. Hand cleaning

methods are time-consuming and may not be

feasible for large installations.

• Cost and Complexity of System: Integrating

multiple elements together, such as tracking,

weather monitoring or an automated cleaning

capability, could render the system complex and

priced higher. These conjunctive systems can

still be difficult to make verifiable and affordable.

Our study is motivated by the challenge of developing

an integrated solution that addresses the

challenges of the existing solar energy systems.

By combining dual-axis tracking with automatic

cleaning and real-time weather tracking, the

proposed system aims to enhance energy

efficiency, reduce maintenance costs, and ensure

reliable performance across a variety of

environmental conditions.

The objectives of this paper are as follows:

• Design and implementation the first step are to

create dual axis solar tracking system with

weather monitoring sensors as well as automatic

cleaning system.

• Real-Time Adaptation: In order to optimize

energy absorption and maintain the efficiency of

the panels, it allows the system to dynamically

adjust to changing ambient conditions.

• Performance Evaluation: To investigate the

energy output increase of the integrated system,

compared with conventional fixed and single-axis

tracking systems.

This paper makes the following contributions:

• Integrated System Development: Outlines the

design and development of a cost-effective dual-

axis solar tracker system, complete with

automated cleaning and live weather observation

capabilities.

• Improved Efficiency: Demonstrates that, relative

to traditional fixed solar panels, the proposed

system has the potential to increase energy

production by as much as 30%.

• High Recap: Demonstrate the system power

and flexibility by providing an in-depth describe

about its working under a variety of

environmental conditions.

This paper's remaining sections are arranged as

follows: The literature review in Section 2 covers the

current state of research on automated cleaning

systems, weather monitoring integration, and solar

tracking systems. Section 3: Design and

Implementation of the System: explains the proposed

integrated system's architecture, parts, and features.

The experimental methodologies and performance

evaluation results are presented in Section 4,

Experimental Setup and Results. Section 5:

Conclusion and Future Work: Provides a summary of

the paper's contributions and suggests possible lines

of inquiry for further study.

The goal of this endeavor is to enhance dependable

and efficient solar energy systems by tackling the

stated difficulties in an integrated manner.

2 RELATED WORKS

There are many studies about the use of Arduino

microcontrollers in photovoltaic panel tracking

systems in order to increase their power output.

Summary This literature review examines key

studies related to the development and

implementation of Arduino-based solar trackers.

Ali, S. S. and Ali, S. M. (2017) Arduino based

solar tracking system. This paper describes the

designing of Arduino based solar tracking system.

The authors do a good job explaining the system's

design, including how the authors interpolated data

from light sensors on an Arduino microcontroller to

position solar panels to receive maximum sunlight.

The research elucidates on the possible operational

implementations of green energy solutions through

Arduino.

Jasni, N. F. F. et al. (2018). Sun Tracking System

Using LabVIEW And Arduino Here we propose a

solar tracking system that is controlled and monitored

with Arduino board and LabVIEW software. The

technology first measures how much sunshine there

is using light sensors and automatically adjusts the

orientation of the panel based on that. This synergy

between hardware and software tools is also

highlighted through LabVIEW that allows real-time

display of data and control of the system.

Biswas, M. & et al., (2017). Solar-Automatic-

Tracking-System-Arduino-and-Blink-Detection-

Power-Source This paper suggests an Arduino-based

solar tracking system with enhanced blink detection

capacity to avoid damage to solar panels. In addition

to following sunshine with light sensors, the system

has an algorithm for detecting sudden light intensity

changes and starts preventive measures. This method

contributes to safe and efficient harvesting of solar

energy.

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

Muthukrishnan, R., and S. Padmanaban (2018). A

Smart sun tracking system - based on Arduino. The

method used sunlight-detecting light-dependent

resistors (LDRs) to track the sun before using a pair

of servos motors to move the screen. "The central

task of the tracking system is being achieved by the

Arduino managing the hardware components, control

algorithms, and overall system design," the authors

state. Kumar, S. and Kumar, A. (2019), Arduino

based Solar Tracking System Design and

Implementation The main focus of the authors is the

implementation ofArduino based solar tracker

system. Not only the hardware configuration, i.e.,

sensors and actuators, but also the software

programming required to run the system is discussed

in detail. The study provides a complete guide with

system calibration and testing procedures on similar-

type projects.

M, F, Ghazali, and collaborators (2019) Solar

tracker system using Arduino. The system

architecture comprises of Arduino-controlled servo

motors for the panel movement and LDR sensors for

detecting sunshine. Besides explaining how effective

the system is in collecting solar energy, the authors

furnish Arduino programming code. Jayanthi, J., &

P. Sreelatha (2017). How to make a solar tracker

system and control it with Arduino. The design and

implementation of an Arduino-based solar tracking

system are discussed in this research study. It gives a

thorough analysis of the control algorithm,

experiments, and system components, sending with

accuracy the system response to maintain ideal panels

alignment.

R. S. Sujith et al (2018) Arduino-based solar

tracking system. They saw more solar energy from

their solar tracker based on Arduino. The hardware in

the design of the system comprises of servo motors,

LDR sensors and a control system that ensures the

panel is always oriented toward the sun.

See also: R. Sahay et al. (2017) Angular Position

Control and Receiving Set-Up of Solar Tracker. This

work presents the design and application of an

Arduino based solar tracking system. It includes

software development, hardware component

selection, and experimental results showing the

system's greater ability to harvest solar energy.

3 PROPOSED METHOD

The discussed system is a complete solution, which

would improve the reliability and efficiency of PV

installations by employing a two-axis solar tracking

system along with an on-the-fly inclement weather

monitoring system and also a corresponding

automated panel cleaning system. This strategy

mitigates poor energy collection from fixed

placements due to the sun's path, environmental and

biological interference, and soiled systems (Sharma,

S. K., Sharma, V., & Choudhary, A. (2020). Figure 1

illustrates the proposed system architecture.

3.1 Dual-Axis Solar Tracking

Mechanism

The system uses a dual-axis tracking, which means

that the panels can be adjusted along both horizontal

and vertical axis. This configuration allows the

panels to be held at a right angle to the sun throughout

the day to collect solar irradiance as efficiently as

possible. In this system, LDR acts as a sensor to

touch the sun position of them and gives real time data

to a microcontroller that controls the position of the

panels using servo motors. This Specialized

Alignment could generate much higher energy than

fixed or One-Axis systems.

3.2 Real-Time Weather Monitoring

To further enhance performance, the system

incorporates weather sensors that track

environmental parameters like temperature,

humidity, and rainfall. And the real-time data

provided by these sensors allow the system to make

accurate adjustments in the orientation of the panel

based on the changing weather conditions. When

empty, during cloudy or rainy days, for example, the

system would adjust the angle of the panels to reduce

the risk of damage and prepare them to capture

energy as the conditions become favorable. Such

adaptability enhances the resilience and efficiency of

the system for a myriad of environmental factors.

3.3 Automated Panel Cleaning System

Building up dust and debris on solar panels can

considerably deter their energy output. To address

this issue, the proposed system features an automatic

cleaning mechanism. The washing system uses

sensors to monitor the degree of soiling on the surface

of the panels and performs cleaning when the "dirt"

level exceeds the set threshold. The cleaning

mechanism, managed by the microcontroller, then

uses brushes or wipers to clear off any lingering

debris, thereby keeping the panels performing at

maximum efficiency with no human input required.

Smart Dual-Axis Solar Tracking System with Weather Monitoring and Automated Panel Cleaning

This measure is especially useful in dry areas in

which dust collects.

3.4 System Integration and Control

At the core of the system is a microcontroller that

takes the input of the LDRs and weather sensors and

uses it to manage the tracking mechanism along with

the cleaning device. The system will be able to

autonomously adapt to changes in the environment,

maintain meaningful angles of the solar panels and

also maintain cleanliness in order to maximise

energy production by integrating these components.

This comprehensive strategy not only streamlines

operations but also minimizes maintenance expenses

and prolongs the life of the photovoltaic system.

Such a dual-axis solar tracking system integrated

with weather monitoring and automated cleaning has

been proposed as a potential effective method to

harvest solar energy. This system allows for

continuous and optimal performance of solar PV

installations by overcoming the challenges of

environmental differences and panel soiling.

Figure 1: Architecture of the proposed method.

3.5 Hardware Setup for Dual-Axis

Solar Tracking Mechanism

The proposed system integrates a dual-axis solar

tracking mechanism with real-time weather

monitoring and an automated panel cleaning system

to enhance the efficiency and reliability of

photovoltaic (PV) installations. Below is a detailed

description of the hardware components for each

subsystem. (Gupta, S., & Verma, A. (2021))

3.5.1 Light Dependent Resistors (LDRs)

These sensors detect the intensity and direction of

sunlight. Four LDRs are strategically positioned to

ascertain the sun's location, providing input signals to

the microcontroller to adjust the panel's orientation

accordingly. Figure 2 shows the LDR sensor.

Figure 2: LDR Sensor.

3.5.2 Microcontroller (e.g., NodeMCU

ESP8266)

Serves as the central processing unit, interpreting data

from the LDRs and executing control algorithms to

manage the movement of the solar panels. Figure 3

shows the node MCU microcontroller.

Figure 3: Node MCU Microcontroller.

3.5.3 Motor Driver

Interfaces between the microcontroller and the servo

motors, providing the necessary current and voltage

to drive the motors based on control signals from the

microcontroller. Figure 4 shows the Motor Driver.

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

Figure 4: Motor Driver.

3.5.4 DC Motor

Two DC motors drive the left and right wheels of the

robot. These motors provide precise movement and

turning capability, enabling efficient locomotion in

both manual and automatic modes. Figure 5 shows

the DC Motor.

Figure 5: DC Motor.

3.5.5 Power Supply Unit

Ensures a stable power source for the microcontroller

and motors, typically derived from the solar panels

themselves or an auxiliary battery system. Figure 6

show the 12v Battery Power supply.

Figure 6: 12 V Battery Power Supply.

3.6 Real-Time Weather Monitoring

System

Temperature and Humidity Sensor (DHT11):

Monitors ambient temperature and humidity levels,

supplying data to the microcontroller for

environmental assessment. Figure 7 shows the

Temperature and Humidity Sensor.

Figure 7: Temperature and Humidity Sensor.

3.7 Automated Panel Cleaning System

Servo Motor: Drives the cleaning apparatus, which

may consist of rotating brushes or wipers, to remove

accumulated dirt from the panels.

3.8 Integration and Control Interface

LCD Display Module: Provides real-time feedback

on system status, including environmental conditions

and operational parameters, facilitating user

monitoring and interaction. Figure 8 show the LCD

display.

Figure 8: LCD Display.

Smart Dual-Axis Solar Tracking System with Weather Monitoring and Automated Panel Cleaning

3.9 Solar Panel

Solar panels consist of individual units called

photovoltaic cells. These cells are typically made of

semiconductor materials, often crystalline silicon,

which can generate an electric current when exposed

to sunlight. Figure 9 shows the Solar panel.

Figure 9: Solar Panel.

3.10 Algorithm

1. Initialization

• System Boot-Up: Upon powering the system,

initialize all sensors, actuators, and the

microcontroller.

• Calibration: Set the initial position of the solar

panels to a default safe orientation, typically facing

east at a horizontal tilt.

• Time Synchronization: Retrieve the current date

and time from the Real-Time Clock (RTC) module

to calculate the sun's position accurately.

2. Dual-Axis Solar Tracking

• Sun Position Calculation: Utilize the synchronized

time and geographical location data to compute the

sun's azimuth and elevation angles using

established solar position algorithms.

• Panel Orientation Adjustment

• Azimuth Control: Compare the current panel

azimuth angle with the calculated sun azimuth

angle.

• If the panel is misaligned, activate the horizontal

axis motor to rotate the panel toward the sun's

azimuth.

3. Real-Time Weather Monitoring

• Data Acquisition: Collect data from environmental

sensors, including temperature, humidity, light

intensity, and rain detection.

• Environmental Assessment:

• High Wind Conditions: If wind speeds exceed a

predefined threshold, reposition the panels to a

horizontal position to minimize wind resistance.

• Rain Detection: Upon detecting rainfall, pause

cleaning operations to prevent potential damage and

consider the natural cleaning effect of rain.

• Low Light Conditions: In the event of low ambient

light (e.g., during heavy cloud cover), decide

whether to enter a power-saving mode or adjust the

panel orientation to capture diffuse light more

effectively.

4. Automated Panel Cleaning

• Soiling Detection: Utilize dust sensors to assess the

level of dirt accumulation on the panel surfaces.

• Cleaning Cycle Initiation:

• Threshold Evaluation: If the detected soiling level

surpasses a set threshold, schedule a cleaning

operation.

• Safety Checks: Ensure that environmental

conditions are suitable for cleaning (e.g., no rain,

moderate wind speeds).

• Cleaning Process:

• Activation: Engage the cleaning mechanism, which

may involve brushes or wipers, to remove debris

from the panel surface.

• Monitoring: Track the cleaning progress to ensure

thorough debris removal.

• Completion: Once cleaning is complete, return the

cleaning apparatus to its standby position.

5. Data Logging and Communication

• Data Recording: Log all sensor readings, panel

positions, and cleaning activities for performance

analysis and maintenance records.

• Remote Monitoring: Transmit real-time data to a

central monitoring system or user interface,

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

allowing for remote oversight and control

adjustments as necessary.

3.11 Implementation

Figure 10 illustrates the implementation of flow.

Figure 10: Implimentation of the flow chart.

4 EXPERIMENTAL RESULTS

The experimental evaluation of the proposed Smart

Dual-Axis Solar Tracking System with integrated

weather monitoring and automated panel cleaning

was conducted to assess its performance in enhancing

photovoltaic (PV) efficiency. The study focused on

comparing energy outputs under various operational

modes and environmental conditions (Ahmed et al.

2020). Figure 11 shows the Hardware setup.

Figure 11: Experimental Hardware Setup.

The system was tested over a period of one month,

during which data were collected under different

scenarios:

1. Fixed Panel without Cleaning: Solar panels

remained stationary without any cleaning

mechanism.

2. Fixed Panel with Cleaning: Stationary panels

equipped with the automated cleaning system.

3. Dual-Axis Tracking without Cleaning: Panels

adjusted their orientation to track the sun but lacked

the cleaning mechanism.

4. Dual-Axis Tracking with Cleaning: Panels both

tracked the sun and utilized the automated cleaning

system.

The data collected were analyzed to determine the

average daily energy output and overall efficiency

improvements for each scenario (Al-Hinai et al.

2019) as shown in Table 1.

Table 1: Comparison of Solar Panel Performance.

Operational

Mode

Average Daily

Energy Output

(Wh)

Efficiency

Improvement

(%)

Fixed Panel

without Cleaning

1,200 Baseline

Fixed Panel with

Cleaning

1,320 +10

Dual-Axis

Tracking without

Cleaning

1,560 +30

Dual-Axis

Tracking with

Cleaning

1,700 +41.7

1) Effect of Dual-Axis Tracking: A dual-axis tracker

integrated into the system can enhance energy

capture significantly. Tracking, unclean: These

panels produced 30% more energy than the baseline.

Start

Initialize all components

Dual-Axis Solar Tracking

Real-Time Weather

Monitoring

Data Logging and

Communication

Data Visualization in

UBIDOTS

End

Smart Dual-Axis Solar Tracking System with Weather Monitoring and Automated Panel Cleaning

This is consistent with past research that has shown

that dual-axis trackers can increase energy output by

about 28% over fixed systems.

2) Effect of Automated Cleaning: Introducing the

automated cleaning system for fixed panels

produced a 10% efficiency increase relative to the

baseline. This finding aligns with research showing

that consistent cleaning can improve panel efficiency

by some 7%

3) Combined Impact: Integration of both dual-axis

tracking and automated cleaning resulted the most

energy production, 41.7% compared to baseline This

highlights the combined advantages of both optimal

sun exposure and clean panels.

Experimental Evaluation of Solar Energy

Harvesting Using the Proposed System The

integration of dual-axis tracking, coupled with

automated cleaning and real-time weather

responsiveness, guarantees that the panels are always

positioned to maximize sunlight capture, resulting in

a significant enhancement in energy efficiency. This

conclusion supports the implementation of

integrated integrated solutions to optimize the

performance of solar PV installations Beldjilali, A.,

& Gana, I. (2021).

5 CONCLUSION AND FUTURE

SCOPE

By combining dual-axis solar tracking systems with

real-time weather monitoring and automatic panel

cleaning mechanisms, the efficiency and reliability of

photovoltaic (PV) installations are found to

significantly improve. The proposed system

overcomes two fundamental challenges with solar

energy harvesting: proper alignment of the panel and

surface cleanliness. It has been experimentally

validated that this kind of integrated systems can

increase energy output up to 30% in comparison to

fixed solar panels. This advancement highlights the

opportunity to enhance solar energy capture through

the integration of advanced tracking technologies

and automation techniques in maintenance.

Future Work The proposed system has the

capability to extend by incorporating machine

learning techniques, the system can learn from

historical weather data and make predictions about

future conditions.

REFERENCES

Ali, S. S., & Ali, S. M. (2017). Solar tracking system using

Arduino. In 2017 IEEE International Conference on

Power, Control, Signals and Instrumentation

Engineering (ICPCSI) (pp. 1-5). IEEE.

Jasni, N. F. F., Abdullah, A. S., Anuar, A. F., & Zahari, M.

H. (2018). Solar tracking system using Arduino and

LabVIEW. In 2018 IEEE Symposium on Computer

Applications & Industrial Electronics (ISCAIE) (pp.

107-110). IEEE.

Biswas, M., Dutta, S., & Chanda, S. K. (2017). Arduino-

based automatic solar tracking system with blink

detection. In 2017 International Conference on

Intelligent Computing and Control Systems (ICICCS)

(pp. 1-5). IEEE.

Muthukrishnan, R., & Padmanaban, S. (2018). Arduino-

based smart solar tracking system. In 2018 Second

International Conference on Inventive Communication

and Computational Technologies (ICICCT) (pp. 1396-

1400). IEEE.

Kumar, S., & Kumar, A. (2019). Design and

implementation of solar tracking system using Arduino.

In 2019 5th International Conference on Advanced

Computing & Communication Systems (ICACCS) (pp.

1270-1274). IEEE.

Ghazali, M. F., Hussain, A., Abdullah, R. S., Rahim, A. H.

A., & Lazi, J. A. (2019). Sreelatha, P., & Jayanthi, J.

(2017). Design and implementation of a solar tracking

system using Arduino. International Journal of

Engineering Science and Computing, 7(10), 14853-

14857.

Sujith, R. S., Mohanraj, M., Kumar, S. S., Arun, S. P., &

Sathyan, S. (2018). Arduino based solar tracking

system. International Journal of Engineering &

Technology, 7(3.32), 1050-1053.

Sahay, R., Singh, S., & Kumar, S. (2017). Design and

implementation of solar tracking system using Arduino.

International Journal of Advanced Research in

Electrical, Electronics and Instrumentation

Engineering, 6(8), 6745-6753.

Sarwar, M. S., Tasnim, S., Karmaker, S. K., & Biswas, B.

(2019). Arduino-based automatic solar tracker. In 2019

International Conference on Robotics, Electrical and

Signal Processing Techniques (ICREST) (pp. 23-28).

IEEE.

Sharma, S. K., Sharma, V., & Choudhary, A. (2020).

Arduino-based dual-axis solar tracking system. In 2020

International Conference on Smart Electronics and

Communication (ICOSEC) (pp. 227-230). IEEE.

Gupta, S., & Verma, A. (2021). Development of Arduino-

based solar tracking system for maximizing energy

output. In 2021 International Conference on Power,

Energy and Smart Grid (ICPESG) (pp. 1-5). IEEE.

Ahmed, S., Paul, D., Dey, S., Hossain, M. F., & Tumpa, S.

K. (2020). Automatic sun tracking system using

Arduino. International Journal of Scientific Research

in Computer Science, Engineering and Information

Technology, 6(6), 176-180.

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

Al-Hinai, M., Al-Rizzo, H., & Al-Hajri, M. (2019). Solar

tracking system using Arduino. International Journal

of Engineering Science Invention, 8(4), 62-66.

Beldjilali, A., & Gana, I. (2021). Dual-axis sun tracking

system using Arduino. International Journal of

Electrical and Computer Engineering (IJECE), 11(3),

2702-2711.

Smart Dual-Axis Solar Tracking System with Weather Monitoring and Automated Panel Cleaning