This manuscript introduces VisionAid, an innovative assistive system designed to enhance the independence of visually impaired individuals by facilitating navigation and environmental interaction. VisionAid integrates cutting-edge technologies, including real-time object detection, Optical Character Recognition (OCR), and Text-to-Speech (TTS), to provide dynamic audio feedback. We conducted extensive experiments using the COCO (Common Objects in Context) dataset, which contains thousands of real-world images, as a pretrained model. For object detection, VisionAid leverages YOLOv8 (You Only Look Once), a state-of-the-art deep learning model known for its high accuracy and low-latency performance. This enables the system to accurately detect and identify objects in real time, ensuring reliable feedback for the user. The system also incorporates Tesseract OCR for text recognition, allowing users to access printed or digital text seamlessly. The recognized text is then converted into natural speech using TTS technology, ensuring both visual and textual information are communicated effectively. By combining these capabilities, VisionAid offers an intuitive, accessible means for visually impaired users to interact with and understand their surroundings through auditory feedback.