A chemical sensor endowed with artificial intelligence can learn to detect certain gases in the air with high sensitivity and selectivity. The device, developed at KAUST, uses machine learning to differentiate the gases according to the way they induce slight temperature changes in the sensor as they interact with it.
Researchers have developed the first in-sensor processor that could be integrated into commercial silicon imaging sensor chips -- known as complementary metal-oxide-semiconductor (CMOS) image sensors -- that are used in nearly all commercial devices that need capture visual information, including smartphones.
The abundance of wrist-worn heart rate measuring devices enables long term cardiovascular monitoring through photoplethysmography (PPG). Such signals contain unique identifiable information that can help in biometric authentication. In this work, we propose Fusion-ID, which use wrist-worn PPG sensors fused with motion sensor data as a way to do bio…
A new study from NC State University combines three-dimensional embroidery techniques with machine learning to create a fabric-based sensor that can control electronic devices through touch. The paper is published in the journal Device.