The researchers noted that most craftsmen who use lasers to create objects make
A team from the Massachusetts Institute of Technology (MIT) has made this process more secure using machine learning.Scientists at the Computer Science and Artificial Intelligence Laboratory have developed a technology called SensiCut, a platform for determining materials for laser cutters that warnsAbout Potentially Hazardous Materials.
The tool consists of inexpensive hardwarecomponents such as a Raspberry Pi Zero board housed in a 3D PCB. The module is then connected to a laser cutter, and the tool's neural network identifies materials based on an image of the microstructure of the material's surface.
To train the SensiCut algorithm, the commandused over 38 thousand images and 30 types of materials. The tool can also provide guidance on how to use different cutting speeds and settings for different materials.
“Complementing standard laser cuttersWith lensless image sensors, we can easily identify visually similar materials that are often found in workshops and reduce overall waste. To do this, we use the surface structure of the material at the micron level, which is a unique characteristic even when visually similar to another type of material. Without this, you would most likely have to guess the correct title of the material from a large database, ”the researchers noted.
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