The first problem we solved was detecting the studs behind a wall with higher accuracy than the existing stud detector (data collected by picking up BT signals given out by the Stud Detector). Applying ML over collected data we have been able to create a way to have sharper definitions of the stud.
It was subsequently felt that it was possible to create digitised maps of a wall with the location of studs indicated. This needed a video capture of an LED beep besides the BT signals, both emanating from the stud detector. It was then extended to the idea that it would be possible to project the image back onto the wall, making stud detection much easier. This last part was accomplished to the POC level.
This was an early IOT application we built, the application requiring expertise in Data Science and Image Processing.
Technology Stack:
C#, Android, OpenCV
