An

Industrial Oriented Mini Project Report

On
GEASTURE CONTROLLED ROBOT WITH JUST HAND MOMENTS USING
ARDUINO UNO
Submi ed in par al fulfillment of the requirements for the
award of the degree of
BACHELOR OF TECHNOLOGY
IN
ELECTRONICS AND COMMUNICATION ENGINEERING
Under the esteemed guidance of
Mr. Dr. Khaja Mujeebudden Quadry
Assistant Professor
Submi ed By
NAME ROLL NO
J. AMULYA (23J25A0410)
N. DHANUSH (23J25A0427)
A. ADARSH (22J21A0401)
P. AKSHITH (22J21A0421)

DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING

JOGINPALLY B.R ENGINEERING COLLEGE

(Affiliated to JNTUH, Hyderabad and Approved by AICTE New Delhi) (Accredited by NAAC A+
GRADE , Recognized under sec on 2(f) of UGC Act, 1956 & ISO 9001:2015 Cer fied
Ins tu on)

Bhaskar Nagar, Yenkapally (V), Moinabad Mandal, R.R.Dist, Hyderabad,

Telangana-75
2024-2025

1
 CERTIFICATE
DATE: 09/06/2025

This is cer fied that this report en tled “GEASTURE HAND ROBOT CONTROLLER WITH HAND
MOMENTS” is the report of mini project submi ed by J AMULYA (23J25A0410), N DHANUSH
(23J25A0427), A ADARSH (22J21A0401), P AKSHITH (22J21A0421), during 2024-2025 in
par al fulfillment of the requirements for the award of the Degree of Bachelor of Technology
in Electronics & Communica on Engineering of Jawaharlal Nehru Technological University
Hyderabad. This is to jus fy that this project is done by them under the guidance of me.

Internal Guide Head of the Department

Mr. Dr. Khaja Mujeebudden Quadry Dr. B. ABDUL RAHEEM
Assistant professor Professor & Head,
department of ECE

Project Coordinator
Sri. A. RAJAIAH
M.Tech., (Ph.D).
Assistant Professor External Examiner

Principal
Dr.B.V. RamanaReddy
JBREC

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 ACKNOWLEDGEMENTS

We take this opportunity to remember and acknowledge the coopera on, good will
and support both moral and technical extended by several individuals out of which our project
has evolved. We shall always cherish our associa on with them.

We are greatly thankful to Dr. B.V. RAMANA REDDY Principal of our college, for
extending his valuable help. We shall forever cherish our associa on with his for his constant
encouragement, perennial.

We express our profound gra tude to Dr. B. ABDUL RAHEEM , professor, Head of
Department of Electronics and Communica on Engineering, for his constant support and
encouragement in comple ng our project.

We would also like to thank Dr. Khaja Mujeebudden Quadry our internal guide,
without whose sugges ons and encouragement, this project would not have been possible.

We express our sincere thanks and gra tude to our project coordinators
Sri. A. RAJAIAH, Assistant professor, Sri. M. GOVINDU, Associate professor, Department of
ECE, Joginpally B.R. Engineering College for their valuable help and encouragement
throughout the project work.

We are also greatly thankful to all the faculty members of the Department who
provided their feedback and valuable sugges ons at different stages of the project and helped
in the success of the project. With immense gra tude and pleasure we take this opportunity
to thank our parents and friends who have been a catalyst in the realiza on of our project.

PROJECT ASSOCIATES
J. AMULYA (23J25A0410)
N. DHANUSH (23J25A0427)
A. ADARSH (22J21A0401)
P. AKSHITH (22J21A0421)

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 ABSTRACT
Gesture Controlled Robot with Just Your Hand Movements using
Arduino UNO
This project presents a gesture-controlled robot designed to navigate a house
environment using hand movements as input. The system leverages motion sensors, such as an
MPU6050 accelerometer and gyroscope, to detect hand gestures, which are then processed by
an Arduino microcontroller. Wireless communication via Bluetooth or RF modules enables
real-time control of the robot, allowing it to move forward, backward, left, or right based on
predefined gestures.

The robot is equipped with DC motors controlled through an L293D motor driver,
ensuring smooth movement. Additionally, an ultrasonic sensor enhances obstacle detection,
preventing collisions. This intuitive control mechanism eliminates the need for traditional
remote controllers, making it particularly useful for assistive applications, such as aiding
individuals with mobility impairments.

The project integrates IoT principles, enabling potential future enhancements like voice
control, smartphone integration, or AI-based gesture recognition. The system's modular design
ensures scalability, allowing further improvements in automation and smart home applications.

Keywords:
1. Gesture Control

2. Arduino UNO

3. ADXL335 Accelerometer

4. Wireless Communication
5. RF 433 MHz Module

6. Motor Driver (L298N)

7. DC Motors

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 CONTENTS
ACKNOWLEDGEMENTS
ABSTRACT
LIST OF FIGURES
CHAPTER 1 – INTRODUCTION 08-10

1.1 Introduction to Embedded Systems

1.2 Characteristic of embedded system

1.3. Applications Of Embedded Systems

1.4. Introduction To the Project

CHAPTER 2- LITERATURE REVIEW 10-11

2.1 Literature Review

CHAPTER 3-EXISTING METHOD 11-12

3.1 Exis ng System

CHAPTER 4 - PROPOSED SYSTEM 13-33

4.1 Proposed System

4.2 Transmi er

4.2.1 Hardware Tools

4.2.1.1 Arduino UNO

4.2.1.2 ADXL 335 Module

4.3 Receiver

4.3.1 Hardware Tools

4.3.1.1 RF 433 Module

4.3.1.2 Motor Driver L298N

4.4 So ware Tools

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CHAPTER 5 -APPLICATIONS & ADVANTAGES – DISADVANTAGES 34-35

5.1 Applica ons

5.2 Advantages
5.3 Disadvantages
CHAPTER 6 - RESULTS&CONCLUSION &FUTURE ENHANCEMENT 36-40

6.1 Results
6.2 Conclusion
6.3 Future enhancement

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LIST OF FIGURES:
Figure no Name of the figure Pg.no
Figure no. 4.2.1 Block diagram of Transmitter 14
Figure no. 4.2.2 Connection of TX side 18
Figure no. 4.2.1.1 Arduino UNO 19
Figure no. 4.2.1.2 Arduino UNO pinout 21
Figure no. 4.2.2.1 ADXL 335 module 23
Figure no 4.3.1 Block diagram of RX 25
Figure no 4.3.2 Connection diagram of RX 29
Figure no 4.3.1.1 RF 433 Module 30
Figure no 6.1 Result 37

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 CHAPTER NO. 1

INTRODUCTION

1.1 INTRODUCTION TO EMBEDDED SYSTEMS:

An embedded system is a special-purpose computer system designed to perform one or a few

dedicated functions, sometimes with real-time computing constraints. It is usually embedded
as part of a complete device including hardware and mechanical parts. In contrast, a general-
purpose computer, such as a personal computer, can do many different tasks depending on
programming. Embedded systems have become very important today as they control many of
the common devices we use.

Since the embedded system is dedicated to specific tasks, design engineers can optimize it,
reducing the size and cost of the product, or increasing the reliability and performance.
Some embedded systems are mass-produced, benefiting from economies of scale.

Physically embedded systems range from portable devices such as digital watches and MP3
players to large stationary installations like traffic lights, factory controllers, or the systems
controlling nuclear power plants. Complexity varies from low, with a single microcontroller
chip, to very high with multiple units, peripherals and networks mounted inside a large chassis
or enclosure.

In general, "embedded system" is not an exactly defined term, as many systems have some
element of programmability. For example, Handheld computers share some elements with
embedded systems — such as the operating systems and microprocessors which power them
— but are not truly embedded systems, because they allow different applications to be load and
peripherals to be connected.

An embedded system is some combination of computer hardware and software, either fixed in
capability or programmable, that is specifically designed for a particular kind of application
device. Industrial machines, automobiles, medical equipment, cameras, household appliances,
airplanes, vending machines, and toys (as well as the more obvious cellular phone and PDA)
are among the myriad possible hosts of an embedded system. Embedded systems that are
programmable are provided with a programming interface, and embedded systems
programming is a specialized occupation.Certain operating systems or language platforms are
tailored for the embedded market, such as Embedded Java and Windows XP Embedded.

8
However, some low-end consumer products use very inexpensive microprocessors and limited
storage, with the application and operating system both part of a single program. The program
is written permanently into the system's memory in this case, rather than being loaded into
RAM (random access memory), as programs on a personal computer are.

1.2. CHARACTERISTIC OF EMBEDDED SYSTEM

 Speed (bytes/sec): Should be high speed

 Power (watts): Low power dissipation
 Size and weight: As far as possible small and low weight
 Accuracy (%error): Must be very accurate
 Adaptability: High adaptability and accessibility
 Reliability: Must be reliable over a long period of time

1.3. APPLICATIONS OF EMBEDDED SYSTEMS

We are living in the Embedded World. You are surrounded with many embedded products,
and your daily life largely depends on the proper functioning of these gadgets. Television,
Radio, CD player of your living room, Washing Machine or Microwave Oven in your kitchen,
Card readers, Access Controllers, Palm devices of your workspace enable you to do many of
your tasks very effectively. Apart from all these, many controllers embedded in your car take
care of car operations between the bumpers and most of the times you tend to ignore all these
controllers.

 Robotics: industrial robots, machine tools, Robocop soccer robots

 Automotive: cars, trucks, trains
 Aviation: airplanes, helicopters
 Home and Building Automation
 Aerospace: rockets, satellites
 Energy systems: windmills, nuclear plants
 Medical systems: prostheses, revalidation machine.

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1.4. INTRODUCTION TO THE PROJECT:

Introduction:

Gesture-controlled robotics is revolutionizing human-machine interaction by enabling intuitive

control mechanisms. This project, Gesture Controlled House Move Robot Using ADXL335,
utilizes an ADXL335 accelerometer to detect hand movements, allowing users to navigate a
robot within a household environment effortlessly.

The ADXL335 is a 3-axis accelerometer that measures tilt and motion, providing analog output
signals corresponding to hand gestures. These signals are processed by an Arduino
microcontroller, which interprets the gestures and transmits control commands wirelessly via
RF or Bluetooth modules. The robot responds to these commands by moving forward,
backward, left, or right, ensuring smooth navigation.

To drive the robot, DC motors are controlled using an L293D motor driver, enabling precise
movement. Additionally, an ultrasonic sensor is integrated to detect obstacles, preventing
collisions and enhancing safety. The system’s wireless control eliminates the need for physical
controllers, making it particularly beneficial for individuals with mobility impairments.

This project demonstrates the practical applications of embedded systems and IoT, offering a
scalable solution for smart home automation. Future enhancements could include voice control,
smartphone integration, or AI-based gesture recognition, further improving accessibility and
functionality.

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 CHAPTER NO. 2

LITERATURE REVIEW
2.1 Literature Review

Gesture-controlled robotics has been extensively studied in the field of human-machine

interaction, particularly for applications in assistive technology, automation, and smart
environments. Various research works have explored the use of accelerometers and gyroscopes
to detect hand movements and translate them into robotic control signals.

Early studies focused on MEMS-based accelerometers, such as the ADXL335, which provides
analog output signals corresponding to hand gestures. Researchers have demonstrated that
these signals can be processed by microcontrollers like Arduino to control robotic movement
efficiently. Wireless communication technologies, including RF and Bluetooth modules, have
been integrated to enable remote operation, enhancing accessibility for users.

Several works have highlighted the importance of gesture recognition algorithms in improving
accuracy and responsiveness. Machine learning techniques, such as deep learning-based
gesture classification, have been explored to refine control mechanisms. Additionally,
ultrasonic sensors have been incorporated into robotic systems to enhance obstacle detection
and prevent collisions.

Recent advancements in IoT and embedded systems have expanded the scope of gesture-
controlled robots, enabling smart home automation and assistive applications. Studies have
proposed integrating voice control, smartphone connectivity, and AI-based gesture recognition
to further enhance usability.

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 CHAPTER NO.3

EXISTING METHOD

3.1 Existing System

Gesture-controlled robots have been widely explored in human-machine interaction,
particularly for applications in assistive technology, automation, and smart environments.
Traditional robotic control systems rely on joysticks, buttons, or remote controllers, which can
be cumbersome and less intuitive for users. The existing systems primarily focus on
accelerometer-based gesture recognition, where hand movements are detected and translated
into robotic commands.

Most gesture-controlled robots utilize MEMS-based accelerometers, such as the

ADXL335, which provides analog output signals corresponding to hand gestures. These signals
are processed by microcontrollers like Arduino, which interpret the gestures and transmit
control commands wirelessly via RF or Bluetooth modules. The robot responds to these
commands by moving forward, backward, left, or right, ensuring smooth navigation.

Existing systems often incorporate ultrasonic sensors for obstacle detection, preventing
collisions and enhancing safety. However, many implementations lack advanced gesture
recognition algorithms, limiting their accuracy and responsiveness. Some systems integrate
machine learning techniques to refine control mechanisms, but these are not yet widely adopted
in low-cost applications.

Recent advancements in IoT and embedded systems have expanded the scope of
gesture-controlled robots, enabling smart home automation and assistive applications. Studies
have proposed integrating voice control, smartphone connectivity, and AI-based gesture
recognition to further enhance usability.

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 CHAPTER NO.4

PROPOSED SYSTEM
4.1 Proposed System

The proposed system aims to enhance the functionality and efficiency of gesture-controlled
robots by integrating ADXL335 accelerometer-based gesture recognition with improved
wireless communication and obstacle detection mechanisms. Unlike traditional remote-
controlled robots, this system enables users to navigate a robot within a household environment
using hand movements, making it more intuitive and accessible.

The ADXL335 accelerometer detects tilt and motion, generating analog signals that are
processed by an Arduino microcontroller. These signals are mapped to predefined gestures,
allowing the robot to move forward, backward, left, or right based on hand movements.
Wireless communication via RF or Bluetooth modules ensures real-time control, eliminating
the need for physical controllers.

To enhance safety and efficiency, the robot integrates an ultrasonic sensor for obstacle
detection, preventing collisions and ensuring smooth navigation. The L293D motor driver
controls DC motors, enabling precise movement and responsiveness. Additionally, the system
is designed for scalability, allowing future enhancements such as voice control, smartphone
integration, and AI-based gesture recognition.

This gesture-controlled robotic system offers a practical solution for smart home automation
and assistive applications, particularly benefiting individuals with mobility impairments. By
leveraging IoT and embedded systems, the proposed design ensures a user-friendly, efficient,
and adaptable robotic platform

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4.2 Transmitter (TX)

BLOCK DIAGRAM:

Fig: 4.2.1 Block Diagram for TX

The RF-based motor control system utilizes wireless communication to remotely operate DC
motors using an RF 433 MHz receiver module. At the core of the system is the Arduino UNO,
which processes signals received from the RF 433 Module RX. The transmitter sends
commands that are decoded by the receiver, allowing precise control over motor movement.

The motor driver L298N acts as an interface between the Arduino and the DC motors,
facilitating bidirectional control. The right and left motors receive commands from the motor
driver, enabling movement in different directions based on the signals processed. The inclusion
of two separate batteries ensures stable power supply—one battery powers the Arduino, while
the other supplies energy to the motor driver and motors, ensuring efficient operation.

This system is particularly useful for robotic vehicles, automation projects, and remote-
controlled devices. By eliminating wired connections, it offers enhanced flexibility, mobility,
and user convenience. The use of RF communication allows long-range control, making it ideal
for home automation, industrial applications, and smart security systems. Future enhancements
could incorporate IoT-based control, smartphone integration, or AI-powered automation to
further improve usability and efficiency

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Transmitter code:
#include <VirtualWire.h>

#define m1 2

#define m2 3

#define m3 4

#define m4 5

void setup()

vw_set_rx_pin(11);

vw_setup(2000);

pinMode(m1, OUTPUT);

pinMode(m2, OUTPUT);

pinMode(m3, OUTPUT);

pinMode(m4, OUTPUT);

vw_rx_start();

Serial.begin(9600);

void loop()

uint8_t buf[VW_MAX_MESSAGE_LEN];

uint8_t buflen = VW_MAX_MESSAGE_LEN;

if (vw_get_message(buf, &buflen))

if(buf[0]=='f')

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{

digitalWrite(m1,HIGH);

digitalWrite(m2,LOW);

digitalWrite(m3,HIGH);

digitalWrite(m4,LOW);

Serial.println("Forward");

else if(buf[0]=='b')

digitalWrite(m1,LOW);

digitalWrite(m2,HIGH);

digitalWrite(m3,LOW);

digitalWrite(m4,HIGH);

Serial.println("Backward");

else if(buf[0]=='r')

digitalWrite(m1,HIGH);

digitalWrite(m2,LOW);

digitalWrite(m3,LOW);

digitalWrite(m4,LOW);

Serial.println("Left");

else if(buf[0]=='l')

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 {

digitalWrite(m1,LOW);

digitalWrite(m2,LOW);

digitalWrite(m3,HIGH);

digitalWrite(m4,LOW);

Serial.println("Right");

else if(buf[0]=='s')

digitalWrite(m1,LOW);

digitalWrite(m2,LOW);

digitalWrite(m3,LOW);

digitalWrite(m4,LOW);

Serial.println("Stop");

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CONNECTION DIAGRAM:

Fig: 4.2.2 Connection diagram of TX side

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4.2.1 HARDWARE TOOLS:
4.2.1.1 ARDUINO UNO
The Arduino Uno is an open-source microcontroller board based on the Microchip
ATmega328P microcontroller and developed by Arduino.cc. The board is equipped with sets
of digital and analog input/output (I/O) pins that may be interfaced to various expansion
boards (shields) and other circuits. The board has 14 digital I/O pins (six capable
of PWM output), 6 analog I/O pins, and is programmable with the Arduino IDE (Integrated
Development Environment), via a type B USB cable. It can be powered by the USB cable or
by an external 9-volt battery, though it accepts voltages between 7 and 20 volts. It is similar to
the Arduino Nano and Leonardo. The hardware reference design is distributed under a Creative
Commons Attribution Share-Alike 2.5 license and is available on the Arduino website. Layout
and production files for some versions of the hardware are also available.

Fig:4.2.1.1 Arduino UNO

Special pin functions:

Each of the 14 digital pins and 6 analog pins on the Uno can be used as an input or output,
under software control (using pinMode (), digitalWrite (), and digital Read () functions). They
operate at 5 volts. Each pin can provide or receive 20 mA as the recommended operating
condition and has an internal pull-up resistor (disconnected by default) of 20-50K ohm. A

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maximum of 40mA must not be exceeded on any I/O pin to avoid permanent damage to the
microcontroller. The Uno has 6 analog inputs, labeled A0 through A5; each provides 10 bits of
resolution (i.e. 1024 different values). By default, they measure from ground to 5 volts, though
it is possible to change the upper end of the range using the AREF pin and the analog Reference
() function.

In addition, some pins have specialized functions:

 Serial / UART: pins 0 (RX) and 1 (TX). Used to receive (RX) and transmit (TX) TTL serial
data. These pins are connected to the corresponding pins of the ATmega8U2 USB-to-TTL
serial chip.
 External interrupts: pins 2 and 3. These pins can be configured to trigger an interrupt on
a low value, a rising or falling edge, or a change in value.
 PWM (pulse-width modulation): pins 3, 5, 6, 9, 10, and 11. Can provide 8-bit PWM output
with the analogWrite() function.
 SPI (Serial Peripheral Interface): pins 10 (SS), 11 (MOSI), 12 (MISO), and 13 (SCK).
These pins support SPI communication using the SPI library.
 TWI (two-wire interface) / I²C: pin SDA (A4) and pin SCL (A5). Support TWI
communication using the Wire library.
 AREF (analog reference): Reference voltage for the analog inputs.

Communication:

The Arduino/Genuino Uno has a number of facilities for communicating with a

computer, another Arduino/Genuino board, or other microcontrollers. The ATmega328
provides UART TTL (5V) serial communication, which is available on digital pins 0 (RX) and
1 (TX). An ATmega16U2 on the board channels this serial communication over USB and
appears as a virtual com port to software on the computer.

The 16U2 firmware uses the standard USB COM drivers, and no external driver is
needed. However, on Windows, a .inf file is required. Arduino Software (IDE) includes a serial
monitor which allows simple textual data to be sent to and from the board. The RX and TX
LEDs on the board will flash when data is being transmitted via the USB-to-serial chip and
USB connection to the computer (but not for serial communication on pins 0 and 1). A
SoftwareSerial library allows serial communication on any of the Uno's digital pins.

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 Fig:4.2.1.2 Arduino UNO pinout

The Arduino UNO is the central processing unit in this system, responsible for
interpreting input signals and executing programmed instructions. It operates using a
microcontroller that processes external commands and responds accordingly via its digital and
analog pins. The Arduino receives input, processes it using a predefined algorithm, and
generates corresponding output signals.

The board includes multiple I/O pins that allow users to interface with external sensors
and modules. It uses PWM (Pulse Width Modulation) for precise signal control, enabling
smooth execution of programmed functions. The Arduino operates on embedded C
programming, where logic is defined through structured code to execute specific tasks.

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 With built-in serial communication (UART, SPI, I2C), Arduino can exchange data
with various devices seamlessly. Additionally, it offers flexibility in programming, supporting
functions such as decision-making algorithms, automation control, and real-time signal
processing. Its adaptability makes it ideal for a variety of IoT, robotics, and automation
applications.

Pin Description:

 LED: There is a built-in LED driven by digital pin 13. When the pin is high value, the LED
is on, when the pin is low, it is off.
 VIN: The input voltage to the Arduino/Genuino board when it is using an external power
source (as opposed to 5 volts from the USB connection or other regulated power source).
You can supply voltage through this pin, or, if supplying voltage via the power jack, access
it through this pin.
 5V: This pin outputs a regulated 5V from the regulator on the board. The board can be
supplied with power either from the DC power jack (7 - 20V), the USB connector (5V), or
the VIN pin of the board (7-20V). Supplying voltage via the 5V or 3.3V pins bypasses the
regulator, and can damage the board.
 3.3V: A 3.3 volt supply generated by the on-board regulator. Maximum current draw is 50
mA.
 GND: Ground pins.
 IOREF: This pin on the Arduino/Genuino board provides the voltage reference with
which the microcontroller operates. A properly configured shield can read the IOREF pin
voltage and select the appropriate power source, or enable voltage translators on the
outputs to work with the 5V or 3.3V.
 Reset: Typically used to add a reset button to shields that block the one on the board.

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4.2.2.1ADXL 335 Module:

The ADXL335 is a 3-axis accelerometer designed for motion and tilt sensing
applications. It provides analog voltage outputs proportional to acceleration in the X, Y, and Z
axes, making it ideal for gesture recognition, robotics, and IoT-based automation.

Key Features:

 Supply Voltage: 1.8V to 3.6V

 Current Consumption: 350 μA (typical)

 Acceleration Range: ±3g

 Bandwidth: Adjustable (0.5 Hz to 1600 Hz for X/Y, 0.5 Hz to 550 Hz for Z)

 Shock Resistance: Up to 10,000g

 Package Size: 4mm × 4mm × 1.45mm (LFCSP)

Fig : 4.2.2.1. ADXL 335 Module

Working Principle:

The ADXL335 uses micro-machined capacitive sensing to detect acceleration. When

motion occurs, the internal mass shifts, altering the capacitance between fixed and moving
plates. This change is converted into an analog voltage output, which can be processed by a
microcontroller like Arduino for real-time applications.

Applications:

 Gesture-controlled robotics

 Tilt sensing in mobile devices

 Gaming controllers

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  Industrial vibration monitoring

 Wearable health devices

The ADXL335 accelerometer module is widely used in various applications due to its
ability to measure acceleration in three axes (X, Y, Z) with high precision. Below are some
of its key applications:

1. Gesture-Controlled Robotics

 The ADXL335 is commonly used in gesture-controlled robots, where hand

movements are translated into commands for robotic movement.

 It enables wireless control of robotic arms, vehicles, and drones by detecting tilt and
motion.

2. Tilt Sensing in Mobile Devices

 Smartphones and tablets use accelerometers like the ADXL335 for screen
orientation detection.

 It helps in auto-rotation features, ensuring the display adjusts based on device

positioning.

3. Gaming Controllers

 The module is integrated into motion-sensing gaming controllers, allowing users to

interact with games through physical movements.

 It enhances virtual reality (VR) and augmented reality (AR) experiences.

4. Industrial Vibration Monitoring

 Used in machinery health monitoring, detecting vibrations and anomalies in

industrial equipment.

 Helps in predictive maintenance, reducing downtime and improving efficiency.

5. Wearable Health Devices

 Integrated into fitness trackers and smartwatches to monitor physical activity.

 Used in fall detection systems for elderly care, alerting caregivers in case of sudden
movements.

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6. Image Stabilization in Cameras

 Helps in reducing motion blur by compensating for hand tremors in digital cameras.

 Enhances video recording stability, ensuring smooth footage.

4.3 Receiver (RX)

Block Diagram

Fig :4.3.1.Block Diagram of RX

The RF-based motor control system enables wireless operation of DC motors using an
RF 433 MHz receiver module. This setup is commonly utilized in remote-controlled robots,
automation systems, and smart mobility solutions. The system incorporates key components
such as Arduino UNO, RF 433 MHz Receiver, L298N Motor Driver, DC Motors, and batteries,
ensuring smooth communication and movement control.

The RF 433 Module RX receives signals from a transmitter, which are then processed
by the Arduino UNO. Based on the received command, the Arduino UNO sends control signals
to the L298N Motor Driver, which operates the right and left motors accordingly. The motor
driver regulates power and provides directional control, allowing the robot or vehicle to move

25
Receiver code:
#include <VirtualWire.h>

#define x A0

#define y A1

#define z A2

char *data;

int x_val;

int y_val;

int z_val;

int x_val2;

int y_val2;

int z_val2;

void setup()

vw_set_tx_pin(12);

vw_setup(2000);

pinMode(x, INPUT);

pinMode(y, INPUT);

pinMode(z, INPUT);

Serial.begin(9600);

x_val2 = analogRead(x);

y_val2 = analogRead(y);

z_val2 = analogRead(z);

26
void loop()

x_val = analogRead(x);

y_val = analogRead(y);

z_val = analogRead(z);

int x_axis = x_val - x_val2;

int y_axis = y_val - y_val2;

int z_axis = z_val - z_val2;

if(y_axis >= 60)

data="f";

vw_send((uint8_t *)data, strlen(data));

vw_wait_tx();

delay(500);

Serial.println("Forward");

else if(y_axis <= -60)

data="b";

vw_send((uint8_t *)data, strlen(data));

vw_wait_tx();

delay(500);

Serial.println("Backward");

27
 else if(x_axis >= 60)

data="r";

vw_send((uint8_t *)data, strlen(data));

vw_wait_tx();

delay(500);

Serial.println("Right");

else if(x_axis <= -60)

data="l";

vw_send((uint8_t *)data, strlen(data));

vw_wait_tx();

delay(500);

Serial.println("Left");

else

data="s";

vw_send((uint8_t *)data, strlen(data));

vw_wait_tx();

delay(500);

Serial.println("Stop");

}
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CONNECTION DIAGRAM:

Fig :4.3.2. Connection Diagram Of RX

The system illustrated in the image utilizes an ADXL receiver to capture hand gesture
inputs, which are processed by the Arduino UNO. The ADXL335 accelerometer detects tilt and
motion, converting analog signals into digital outputs. These signals are then sent to the
Arduino UNO, which interprets the data and generates movement commands.The motor driver
(L298N) plays a crucial role in controlling the DC motors, directing their movement based on
commands received from the Arduino UNO.

It ensures smooth operation and precise directional control. To power the system, a
battery provides a stable energy source for both the Arduino UNO and the motor driver,
ensuring continuous functionality. This setup enables gesture-controlled robotics, making it
ideal for applications in automation, assistive technologies, and smart mobility. The modular
design allows for future enhancements, such as wireless communication, IoT integration, and
AI-powered gesture recognition.

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4.3.1 HARDWARE TOOLS

4.3.1.1.RF 433 Module

The RF 433 MHz module is a widely used wireless communication module that
operates at 433 MHz frequency, enabling long-range data transmission. It consists of a
transmitter (TX) and receiver (RX), allowing devices to communicate wirelessly over distances
of up to 100 meters in open space.

Fig :4.3.1.1 RF 433 Module

Working Principle

The transmitter (TX) converts digital signals into radio waves using Amplitude Shift Keying
(ASK) modulation. These waves are then transmitted through an antenna. The receiver (RX)
captures these signals, amplifies them, and decodes the data for further processing. The receiver
module requires an external antenna to improve signal reception.

Technical Specifications

 Frequency: 433 MHz

 Modulation: ASK (Amplitude Shift Keying)

 Operating Voltage: TX (3V-12V), RX (5V)

 Transmission Speed: Up to 10Kbps

 Range: 30-100 meters (depending on antenna and environment)

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Applications:
The RF 433 MHz module is widely used in various wireless communication
applications due to its long-range capabilities, low power consumption, and cost-
effectiveness. Some of its key applications include:

1. Remote Control Systems

 Used in wireless remote controls for home appliances, garage doors, and lighting
systems.

 Commonly integrated into car key fobs for remote locking and unlocking.

2. Home Automation & Security

 Enables wireless door/window sensors, motion detectors, and alarm systems.

 Used in smart home automation for controlling lights, fans, and electronic devices.

3. Wireless Sensor Networks

 Applied in weather stations to transmit temperature, humidity, and pressure data.

 Used in environmental monitoring systems for air quality and pollution tracking.

4. Industrial & IoT Applications

 Facilitates wireless data transmission in factory automation and industrial

monitoring.

 Integrated into IoT-based smart devices for remote control and data logging.

5. Robotics & Embedded Systems

 Used in wireless robotic control for gesture-based and remote-operated robots.

 Enables RF-based motor control systems for automation and mobility solutions.

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4.3.1.2 Motor Driver L298N

The L298N motor driver is a dual H-Bridge motor driver module designed to control
DC motors and stepper motors efficiently. It is widely used in robotics, automation, and
embedded systems due to its ability to handle high voltage and current loads.

Key Features:

 Voltage Range: 5V to 35V

 Current Handling: Up to 2A per channel

 Dual H-Bridge Configuration: Allows bidirectional control of two DC motors

 PWM Support: Enables speed control

 Built-in 78M05 Voltage Regulator: Provides 5V output for microcontrollers

 Heat Sink: Prevents overheating during operation

Working Principle:

The L298N module operates using an H-Bridge circuit, which allows forward and
reverse movement of motors by controlling the polarity of the voltage applied. The ENA and
ENB pins enable PWM-based speed control, while IN1, IN2, IN3, and IN4 determine the
direction of motor rotation.

4.4 SOFTWARE TOOL

Arduino IDE

The Arduino IDE (Integrated Development Environment) is the official software used
for writing, compiling, and uploading code to Arduino boards. It provides a user-friendly
interface for programming microcontrollers, making it ideal for embedded systems and IoT
projects.

Key Features:

1. Code Editor – Allows users to write and edit Arduino sketches (.ino files).

2. Compiler & Debugger – Converts code into machine-readable instructions and checks
for errors.

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 3. Serial Monitor – Enables real-time communication with the Arduino board for
debugging.

4. Library Manager – Provides access to pre-built libraries for sensors, motors, and
communication modules.

5. Board Manager – Supports multiple Arduino boards, allowing easy selection and
configuration.

6. Cross-Platform Compatibility – Works on Windows, macOS, and Linux.

How It Works:

 Users write code in C/C++ using predefined functions.

 The compiler translates the code into a hex file.

 The bootloader on the Arduino board executes the uploaded program.

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 CHAPTER NO.5

ADVANTAGES & APPLICATIONS

5.1 ADVANTAGES:

Advantages of Gesture Controlled House Move Robot Using Arduino UNO

1. Intuitive Gesture-Based Control

 Eliminates the need for physical controllers or remotes.
 Users can operate the robot effortlessly with hand movements, enhancing
accessibility.
2. Wireless Operation
 Uses RF 433 MHz communication, allowing remote control without direct wiring.
 Enables long-range operation, making it suitable for home automation.
3. Energy Efficiency
 Optimized power consumption with Arduino UNO and L298N motor driver.
 Uses low-power components, ensuring longer battery life.
4. Enhanced Mobility
 The ADXL335 accelerometer ensures smooth and precise movement.
 Ideal for assistive applications, helping individuals with mobility impairments.
5. Scalability & Customization
 Can be upgraded with IoT integration, AI-based gesture recognition, or voice control.
 Supports additional sensors for obstacle detection and automation.
6. Obstacle Detection & Safety
 Can integrate ultrasonic sensors to prevent collisions and enhance navigation.
 Ensures safe movement in indoor environments.
7. Real-World Applications
 Used in smart home automation, assistive robotics, and industrial automation.
 Can be adapted for gesture-controlled wheelchairs and robotic assistants.

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5.2 APPLICATIONS

1. Smart Home Automation

 Enables gesture-based control of household robots for cleaning, surveillance, and

assistance.

 Can be integrated with IoT systems for voice and AI-based automation.

2. Assistive Technology

 Helps individuals with mobility impairments by allowing gesture-controlled

movement.

 Can be adapted for wheelchair automation and elderly assistance.

3. Robotics & AI Integration

 Used in gesture-controlled robotic arms for industrial automation.

 Can be enhanced with AI-powered gesture recognition for precision control.

4. Security & Surveillance

 Can be equipped with cameras and sensors for gesture-controlled patrolling

robots.

 Useful for automated security monitoring in restricted areas.

5. Educational & Research Projects

 Helps students and researchers explore embedded systems, IoT, and robotics.

 Provides a hands-on learning experience in gesture recognition and automation.

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 CHAPTER NO. 6

RESULTS & CONCLUSION&FUTURE SCOPE

6.1 RESULTS

1. Accurate Gesture Recognition

 The ADXL335 accelerometer successfully detects hand movements and translates

them into directional commands.

 The system responds effectively to tilt-based gestures, ensuring smooth control.

2. Reliable Wireless Communication

 The RF 433 MHz module enables stable signal transmission between the gesture
controller and the robot.

 The communication range allows remote operation, making it suitable for home
automation.

3. Efficient Motor Control

 The L298N motor driver ensures precise speed and direction control of the motors.
 The robot moves smoothly in forward, backward, left, and right directions based
on hand gestures.

4. Low Power Consumption

 The Arduino UNO optimizes energy usage, ensuring stable operation with minimal
power requirements.
 The system can run efficiently on battery power, making it portable.

5. Real-Time Responsiveness

 The robot reacts instantly to hand gestures, demonstrating low-latency control.

 The system maintains consistent performance across multiple test scenarios.

6. Enhanced Mobility & Stability

 The robot maintains balance and stability even on uneven surfaces.

 The gesture-based control eliminates the need for physical controllers, improving
usability.

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7. Scalability & Future Enhancements

 The system can be upgraded with IoT connectivity, AI-powered gesture

recognition, and obstacle detection.

 Future improvements could include voice control, cloud integration, and machine
learning algorithms for adaptive automation.

Fig: 6.1 Results

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6.2 CONCLUSION
The Gesture Controlled House Move Robot successfully integrates wireless
communication, motion sensing, and motor control to enable intuitive, hands-free operation.
The ADXL335 accelerometer accurately detects hand movements, translating them into
directional commands, while the RF 433 MHz module ensures reliable signal transmission
between the gesture controller and the robot. The L298N motor driver effectively regulates
motor speed and direction, enabling precise movement, and the Arduino UNO optimizes power
consumption for stable operation.

This project showcases the potential of gesture-based automation in assistive

technology, smart home applications, and robotics. The ability to control movement using
simple hand gestures enhances accessibility, making it particularly useful for individuals with
mobility impairments. Additionally, the system’s wireless functionality eliminates the need for
physical controllers, improving convenience and usability.

Future enhancements could include IoT connectivity, AI-powered gesture recognition,

and obstacle detection for improved functionality. Expanding the system with voice control,
cloud integration, and advanced machine learning algorithms could further refine its
capabilities, making it a more intelligent and adaptive solution for automation. The project
demonstrates how embedded systems and sensor-based control mechanisms can revolutionize
human-machine interaction, paving the way for more sophisticated applications in home
automation, healthcare, and industrial robotics.

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6.3 FUTURE ENHANCEMENT:
The Gesture Controlled House Move Robot has significant potential for
advancements in automation, IoT, and AI-driven control systems. Here are some key areas
for future development:

1. IoT Integration for Smart Home Automation

 Connecting the robot to cloud-based IoT platforms for remote monitoring and
control.

 Enabling voice commands and mobile app control for enhanced accessibility.

2. AI-Powered Gesture Recognition

 Implementing machine learning algorithms to improve gesture accuracy.

 Using computer vision for hand tracking and adaptive gesture control.

3. Advanced Obstacle Detection & Navigation

 Integrating ultrasonic, LiDAR, or infrared sensors for collision avoidance.

 Developing autonomous path planning for efficient movement.

4. Energy Optimization & Battery Management

 Using solar-powered charging for sustainable energy solutions.

 Implementing low-power microcontrollers for extended battery life.

5. Multi-Functional Expansion

 Adding payload capabilities for carrying objects in smart homes.

 Enhancing robotic arms for assistive applications.

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6.4 REFERENCES

1. DIY Arduino Gesture Control Robot – Learn how to build a gesture-controlled robot
using RF modules, motor drivers, and accelerometers:
https://www.youtube.com/watch?v=svJwmjplm4c

2. Gesture-Controlled Robot with Arduino – A tutorial on using MPU-6050 for motor

control via gestures: https://www.youtube.com/watch?v=Vwvs890ryqg

3. AI Gesture-Controlled Arduino Uno Robot – Using machine learning in PictoBlox

for gesture-based control: https://www.youtube.com/watch?v=ARR3YWnTf-o

4. Gesture Controlled Robot Using Arduino – Step-by-step guide on building a gesture-

controlled robot: https://www.instructables.com/Gesture-Controlled-Robot-Using-
Arduino-1/

5. Hand Gesture Controlled Robot – Arduino Project Hub tutorial on gesture-based

robotic movement: https://projecthub.arduino.cc/abdelkader_ch/hand-gesture-
controlled-robot-3d232f

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