Blind and Visually Impaired (BVI) individuals (Divyangjan) encounter numerous difficulties in mobility and performing daily life activities independently. Though assistive technologies have made significant strides over the past decades, a major issue remains with designs that address the specific need of the BVI population concerning rare situations, particularly in circumstances of poor illumination. The recent advances in AI, deep learning, and computer vision technologies have opened new avenues for consideration to enhance the independence and quality of life of people with visual disabilities. This literature reviews the most advanced technologies in computer vision, deep learning models of various approaches as well as assistive devices, targeting the real problems of the BVI population. Based on a review of some cutting-edge work, the paper describes several major gaps in the solutions available and proposes an integrated vision for a system. The suggested system merges novel low-light enhancement techniques, real-time object-detection algorithms, and natural auditory feedback modalities. These innovative set of solutions will enable the BVI portion of the population within the region to easily apply various cost-effective navigation solutions to enhance mobility with safety and independence in diverse conditions. It is, therefore, concluded that there is an immense need for a variety of mobility technologies that should be made easily available to BVI individuals since these will surely improve their independence and quality of life.