A new wearable AI system watches your hands through smart glasses, guiding experiments and stopping mistakes before they happen ...

Abstract: With the advent of modernization, it is inevitable from various sources that there is a significant increase in the energy demand. In order to efficiently meet this demand, we need to ensure ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...

Abstract: Condition monitoring and fault detection of machine-level motors are critical in industrial environments. Traditional supervised approaches, which rely on extensive labeled fault data, are ...

A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...

A team of scientists in the United States has combined both spatial and temporal attention mechanisms to develop a new approach for PV inverter fault detection. Training the new method on a dataset ...

AWARE uses waveform signatures to detect and classify early-stage grid faults, enabling proactive intervention. The system combines physics-based models with AI/ML to interpret subtle electrical ...