Department of Electrical Engineering
For this project our objective is to detect installation errors on the Simpson Strong-Tie LUS26 face mount for wooden beams as efficiently as possible. This job is currently the task of the technicians but Simpsong was wondering if they could streamline the process and detect errors with more accuracy using technology. We are using two different image processing machine learning programs we typed up and are implementing them on a portable single board computer with a camera attached, we choose the Raspberry Pi and it’s accessories.
Originally, we planned on having this device clamp onto the beam and to measure all 3 sides of the face mount at once along with detecting different face mounts but our team leader got hospitalized from covid for over a month recently and the project got delayed. Due to this and the fact that our group was already working with less people than other groups, we got Evan from Strong-Tie and the professors to lower our requirements. Therefore we are only going to focus on the commonly used LUS26 face mount and only detect one or two sides of it.
Abiding by the new requirements, we will prove that our setup is efficient and can easily be expanded into our original design.