Smart Cane: Obstacle Recognition for Visually Impaired People Based on Convolutional Neural Network

According to the World Health Organization (WHO), there are millions of visually impaired people in the world who face a lot of difficulties in moving independently. 1.3 billion people are living with some visual impairment problem, while 36 million people are completely visually impaired. We proposed a system for visually impaired people to recognize and detect objects based on a convolutional neural network. The proposed method is implemented on Raspberry Pi. The ultrasonic sensors detect obstacles and potholes by using a camera in any direction and generate an audio message for feedback. The experimental results show that the Convolutional Neural Network yielded impressive results of 99.56% accuracy.