This article describes the architecture and system design for assisting blind people in navigating freely inside an enclosed environment, such as the home or the outdoors. Thus, the proposed technology uses IoT technology and emerging techniques for machine learning to provide high-tech cane functionality that allows visually impaired navigators to walk independently. It also includes mobile applications to safeguard visually impaired persons and allow guardians to observe them. The proposed in this study system is intended to identify and classify any obstacles within a defined distance using machine learning. In this connection, an indoor and outdoor architecture on YOLO v3 is implemented for its detection technique, and multi-layer perceptron (MLP) neural network technology supports this framework. Based on the detection and classification, YOLO v3 and MLP are crucial for their accuracy.