VOICE CONTROL FOR CAR USING ARDUINO

This project presents the development of a voice-controlled car using an Arduino uno microcontroller and a Bluetooth module (HC-05) for wireless communication. The system enables users to control the car’s movements through voice commands transmitted from a smartphone. The primary objective is to create a hands-free and user-friendly control mechanism for robotic mobility. Voice commands are processed using a smartphone app, which sends the instructions to the Arduino uno via the HC-05 Bluetooth module. The Arduino interprets these commands and controls the car’s movement through a L298N motor driver circuit, enabling actions such as “forward,” “backward,” “left,” “right,” and “stop.“ The car is powered by a rechargeable battery and mounted on a robust chassis with DC motors. This Bluetooth-based solution offers flexibility, cost-effectiveness, and ease of implementation, eliminating the need for voice recognition modules. The project demonstrates the integration of voice command technology and Bluetooth communication, showcasing potential applications in smart vehicles, automation systems, and assistive robotics. The system is scalable and can be enhanced with additional features such as obstacle detection and autonomous navigation. In this proposed project, the emphasis is on voice control of car with automatic braking, speed slow down and avoidance of obstacles automatically or manually (through voice command).In this model, we will use an android app(Android Bluetooth control) to pass on the voice commands to the Arduino through Bluetooth communication using Bluetooth module(HC-05). The implementation focuses on speech-to-command processing, motor control algorithms, and real-time response optimization. The voice recognition system is trained to recognize specific commands with high accuracy, minimizing errors during operation. The project also explores possible extensions, such as integrating wireless communication modules for remote monitoring and control, obstacle detection systems for collision avoidance, and advanced machine learning algorithms for improving voice recognition in noisy environments. By bridging the gap between voice recognition technology and Arduino-based systems, this project highlights the feasibility and practicality of voice-controlled vehicles, showcasing their potential to transform everyday interactions with technology.