This week Eshita decided to drop the class due to an overwhelming workload. The two of us remaining thought about continuing the project in the same direction but realized that we lacked the machine learning knowledge to be able to confidently proceed. We thought of how we could still aid the visually impaired without the use of machine learning and decided to go towards direction and navigation instead. Our new project will tell a user how to get from point A to B, avoiding blind unfriendly crosswalks.
The system will be comprised of 2 Raspberry Pis communicating with each other over a wired network. The front-end Pi will be gathering location data using a GPS and IMU, and will communicate that data to the back-end Pi. The back-end Pi will take the location data and will interface with the Google Directions and Roads APIs via a cellular data chip to determine where the user should go next to reach the destination. Information such as the distance to the next intersection, the direction to turn at the intersection, and ETA will be periodically reported via a speaker and a Text-To-Speech engine running on the front-end Pi.
Our team is behind schedule at this point considering that we have to restart most of the research and design, however we are working hard to catch up to where we should be. The skills needed for the project suit our areas of specialization very well and we should be able to dedicate most of our time towards development as opposed to research.