As advancements in object recognition technology continue to progress, they have found application in a variety of domains, including autonomous vehicles, robotics, and industrial operations. Nevertheless, the potential benefits of these technological strides extend significantly to individuals with visual impairments, who stand to gain the most from such innovations. This study introduces a novel system for object detection tailored to address the needs of the visually impaired, employing state-of-the-art machine learning techniques. Additionally, a voice-guidance approach has been implemented to provide location information about objects to those with sight impairments. In response to these challenges, we have developed an Intelligent Object Detection System specifically designed to assist individuals with visual impairments, harnessing the power of the YOLO algorithm. This groundbreaking solution capitalizes on cutting-edge technology to empower visually impaired individuals, enabling them to lead more independent lives and access essential information. Through the integration of the YOLO algorithm, an advanced object detection system, and machine learning methodologies, our system is capable of real-time object identification and localization within the user’s environment. Furthermore, it can identify and categorize everyday objects, providing real-time auditory feedback to users and assisting them in gauging distances from objects, thereby enhancing their mobility and overall sense of security.