Hand Gesture Controlled Fire Fighting Robot

Abstract

Nowadays fire hazards pose a dangerous threat to life and assets due to the uses of flammable substances, ignition devices, chemical igniters and fire propagation tools. So that this making fire-fighting automation a crucial area of research. This paper presents a hand gesture controlled fire-fighting robot that responds to a user commands via an ADXL accelerometer sensor and RF communication module. The sender RF module captures hand gesture through ADXL using arduino and transmit angle data to the receiver wirelessly, which processes the signals using another arduino and drives motors accordingly. The robot is equipped with fire detection and extinguish system to manage small-scale fires. This technology provides a contactless, efficient, and rapid response system, reducing human risk in hazardous environments.

Introduction

Project Overview

This project aims to develop a gesture-controlled fire-fighting robot to reduce human risk during fire emergencies. It uses an ADXL accelerometer sensor to capture hand gestures, and an RF module for wireless communication between the user and the robot. The robot is equipped with fire detection sensors and a fire extinguishing mechanism, all controlled through two Arduino boards—one for gesture input (sender) and one for robot control (receiver).

Key Components

• ADXL Accelerometer: Captures hand movements (tilt/orientation) and sends analog signals to the Arduino.

• RF Module (433/315 MHz): Enables wireless data transmission between the gesture controller and the robot.

• Arduino (Sender & Receiver): Processes sensor data and controls robot actions.

• L298N Motor Driver: Controls motor direction and speed for robot movement.

• Fire Detection & Suppression: Uses a flame sensor and a small pump or extinguisher to put out detected fires.

Literature Survey Insights

• Traditional fire-fighting robots rely on flame/temperature sensors but lack manual control.

• Bluetooth/Wi-Fi controlled robots face connectivity limitations.

• Gesture-controlled robots offer better usability and response times.

• Combining gesture control with RF communication provides a reliable and intuitive interface.

Working Principle

1. Gesture Capture: User moves hand with ADXL sensor.

2. Signal Transmission: Arduino sender processes movement data and sends it via RF.

3. Signal Reception: Arduino receiver interprets data and directs the robot.

4. Movement Control: Robot moves (forward, backward, left, right) via the motor driver.

5. Fire Response: If fire is detected, the system automatically activates extinguishing equipment.

Conclusion

This research presents a hand gesture-controlled fire-fighting robot as an innovative and effective solution for fire emergencies. By integrating ADXL sensors, RF communication, and Arduino, the system offers a wireless, contactless, and user-friendly alternative to conventional fire-fighting robots. The project demonstrates high accuracy in movement control and rapid response to fire hazards, making it suitable for real-time applications in hazardous environments. Future enhancements may include AI-based fire detection, improved range, and real-time camera integration for advanced monitoring.

References

[1] Kim JH, Starr JW, Lattimer BY (2015) – \"Firefighting robot stereo infrared vision and radar sensor fusion for imaging through smoke.\" Fire Technology 51(4):823. [2] Pack DJ, Avanzato R, Ahlgren DJ, Verner IM (2004) – \"Fire-fighting mobile robotics and interdisciplinary design-comparative perspectives.\" IEEE Transactions on Education 47(3):369. [3] Shah SS, Shah VK, Mamtora P, Hapani M (2013) – \"Fire fighting robot.\" International Journal of Emerging Trends in Technology and Computer Applications 2(4):232 [4] Suarez J, Murphy RR (2012) – \"Hand gesture recognition with depth images: a review.\" Proceedings of IEEE ROMAN 2012. [5] Mansuri R, Vakale S, Shinde A, Patel T (2013) – \"Hand gesture control robot vehicle.\" International Journal of Electronics and Communication Technology 4(SPL-2):77–80.

Copyright

Copyright © 2025 Mrs. Kanupriya, Mohd. Aalim, Anjali Rawat, Md Shahbaz. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.