Imagine navigating a bustling shopping mall or a complex office building without sight. For millions of visually impaired individuals, indoor navigation presents a daily challenge. GPS signals fade within building walls, leaving traditional navigation apps useless. Now, researchers are pioneering an innovative solution: an AI-powered “indoor GPS” using only a smartphone. This groundbreaking system leverages the power of deep learning, multimodal models, and large language models (LLMs) to transform a smartphone camera into a sophisticated navigation tool. The phone captures real-time images of the surroundings, which are then wirelessly sent to a nearby Raspberry Pi mini-computer. This clever setup offloads the heavy computational work, keeping the user's phone from overheating and draining its battery. On the Raspberry Pi, sophisticated algorithms analyze the images, identifying architectural features, signage, and potential obstacles. An LLM then translates this visual data into clear, natural language instructions, delivered to the user via audio prompts. "Turn left in 10 feet," the phone might say, or "Caution: stairs approaching." The system even reads signage aloud, providing crucial contextual information. Because all processing happens locally on the Raspberry Pi, sensitive visual data never leaves the building, ensuring user privacy. This localized approach also eliminates the need for a constant internet connection, making the system incredibly reliable. While still in its early stages, this research demonstrates the transformative potential of AI to enhance accessibility and independence for the visually impaired. Future enhancements could include incorporating other sensors like LiDAR for improved obstacle detection, multilingual support, and personalized voice prompts. This AI-powered indoor GPS promises a future where navigating indoor spaces is as seamless and intuitive for the visually impaired as it is for everyone else.