Making the most of quite little: Improving AI training for edge sensor time series

Engineers at the Tokyo Institute of Technology (Tokyo Tech) have demonstrated a simple computational approach for improving the way artificial intelligence classifiers, such as neural networks, can be trained based on limited amounts of sensor data. The emerging applications of the Internet of Things often require edge devices that can reliably classify behaviors and situations …

Engineers improve electrochemical sensing by incorporating machine learning

Combining machine learning with multimodal electrochemical sensing can significantly improve the analytical performance of biosensors, according to new findings from a Penn State research team. These improvements may benefit noninvasive health monitoring, such as testing that involves saliva or sweat. The findings were published this month in Analytica Chimica Acta.