Traffic Sign Recognition and Voice-Activated Driving Assistance Using Raspberry Pi

Abstract

Traffic sign recognition and voice-activated driving assistance systems are crucial technologies for enhancing road safety and improving the driving experience. This paper presents a design and implementation of a low-cost, real-time traffic sign recognition system and voice-activated driving assistance using Raspberry Pi. The system consists of a camera module, a Raspberry Pi, and an interface board that connects the camera and Raspberry Pi. The Raspberry Pi runs an image processing algorithm to identify traffic signs and provides audio feedback to the driver. The voice-activated driving assistance system allows drivers to control the system with voice commands, such as adjusting the volume and changing the mode of operation. The image processing algorithm uses a deep learning-based on traffic sign recognition and includes a convolutional neural network trained on a dataset of traffic signs. The system was tested on a variety of road scenarios and achieved an accuracy rate of over 95% for traffic sign recognition. The voice-activated driving assistance system was integrated with the Amazon Alexa Voice Service, allowing drivers to interact with the system through voice commands. The proposed system is highly cost-effective, as it utilizes a Raspberry Pi, a low-cost single-board computer, as the main processing unit. This makes the system suitable for widespread deployment and accessibility to a larger audience. Additionally, the system has low power consumption and is portable, making it suitable for use in various road scenarios and vehicles. In conclusion, the traffic sign recognition and voice-activated driving assistance system using Raspberry Pi presents a practical solution for improving road safety and enhancing the driving experience. The system's low cost, portability, and real-time performance make it a promising technology for widespread deployment in vehicles.