Navigating the development of an assistive indoor technology for the visually impaired, my PhD journey intersected with Google's advanced tools. Tasked with optimizing location accuracy on budget smartphones, I integrated methodologies reminiscent of those in autonomous vehicle systems. The application utilized TensorFlow Lite's version of YOLO from GCP for obstacle detection, enhanced with transfer learning to widen object recognition capabilities. Google's text-to-speech and speech recognition APIs became pivotal, filling the gap in my resource constraints. This talk underscores the power of leveraging accessible tools in creating impactful, innovative tech solutions, while offering insights into the practical challenges and successes of my endeavor.