International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | A Voice-Driven, Vision-Aware Smart Rover for Assistive, Industrial, and Educational Automation |
|---|---|
| ABSTRACT | This project, titled "A Voice-Driven, Vision-Aware Smart Rover for Assistive, Industrial, and Educational Automation," aims to design and develop an intelligent robotic system that synergistically integrates voice control, computer vision, and autonomous navigation to create a versatile and accessible platform. The core objective is to enable intuitive, handsfree operation of a robotic vehicle through natural language commands while ensuring safe and context-aware movement in real-world environments. The system architecture is built around a multi-layered control framework. At the user interface level, a custom Android mobile application captures spoken commands through the device's microphone. Utilizing Google’s Speech Recognition API, the application converts audio input into text, which is then parsed and wirelessly transmitted to the robotic rover via a Bluetooth (HC-05) module. On the hardware side, an Arduino Nano microcontroller serves as the central processing unit, decoding received commands and executing corresponding actuation routines. Movement is achieved through DC motors driven by an L298N motor driver, allowing precise directional control (forward, backward, left, right) based on voice input. To enhance operational safety and autonomy, the rover is equipped with an ultrasonic sensor (HCSR04) for real-time obstacle detection. A significant innovation of this project is the integration of vision-based intelligence. A mounted camera module continuously captures the rover's surroundings, and an embedded computer vision pipeline performs real-time traffic sign detection and classification. Detected signs are processed, and relevant auditory alerts are generated using a text-to-speech (TTS) system, providing the user with enhanced environmental awareness and making the system suitable for applications in structured environments like campuses or warehouses. The project implements a sophisticated hybrid control system that seamlessly blends manual voice control with autonomous sensor-driven decision-making. This fusion of data from voice commands, camera input, and ultrasonic sensors enables intelligent, context-sensitive navigation, where the rover responds to user intent while proactively avoiding hazards. This project delivers a robust, scalable, and multimodal robotic system that demonstrates the practical convergence of the Internet of Things (IoT), Artificial Intelligence (AI), and Robotics. It lays a foundation for future expansions, including integration with GPS for navigation, cloud connectivity for advanced analytics. |
| AUTHOR | LAXMI NARAYAN SINGH, SHIVAM PRASAD, SNEHA PADMA KUMAR, YASRIN PARWEEN, DR. MALATESH S H Student, Dept. of Computer Science and Engineering, MS Engineering College, Bengaluru, Karnataka, India Professor & HoD, Dept. of Computer Science and Engineering, MS Engineering College, Bengaluru, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401047 |
| pdf/47_A Voice-Driven, Vision-Aware Smart Rover for Assistive, Industrial, and Educational Automation.pdf | |
| KEYWORDS | |
| References | 1. J. C. Jones and A. Flynn, Mobile Robots: Inspiration to Implementation, 2nd ed., A K Peters, Wellesley, MA, USA, 1999. 2. R. Siegwart, I. R. Nourbakhsh, and D. Scaramuzza, Introduction to Autonomous Mobile Robots, 2nd ed., MIT Press, Cambridge, MA, USA, 2011. 3. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson Education, 2021. 4. M. Quigley et al., “ROS: An open-source Robot Operating System,” in Proc. IEEE Int. Conf. on Robotics and Automation Workshop, Kobe, Japan, 2009. 5. K. Ogata, Modern Control Engineering, 5th ed., Prentice Hall, 2010. 6. P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. 7. HC-SR04 Ultrasonic Sensor Datasheet, Elecfreaks, 2018. 8. Arduino Nano Technical Specifications, Arduino Documentation, Arduino.cc. 9. ESP32-CAM Development Board Datasheet, Espressif Systems, 2020. 10. Google Speech Recognition API Documentation, Google Developers, 2023. 11. Dr. Malatesh S. H, Yogith M, Vedamitra G M, and Sunil Bhandari R “Autonomous Night Safety Patrolling Car," International Journal of Innovative Research in Technology (IJIRT), vol. 11, no. 12, May 2025, ISSN: 2349-6002 |
