Algorithms for Fault Detection and Diagnosis in Wireless Sensor Networks Using Deep Learning and Machine Learning - An Overview Abstract: The integration of artificial intelligence (AI) with wireless ...

In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. An application called ‘AndroSensor’ on a smartphone, that retrieves real-time data ...

Machine Learning: Sensors Get Linked In. Aug. 22, 2019. ... Machine learning is a set of algorithms that creates its own algorithms to allow a machine to perform better.

Of these, the supervised model is a better choice for developing soft sensors or creating predictive tags. Although there are hundreds of supervised machine learning models, only a handful of ...

Machine learning (ML) could allow drug firms to create predictive process models that optimize development, production, and quality control. But, before embracing ML on the factory floor ...

STMicroelectronics’ LSM6DSOX iNemo inertial sensor has a machine-learning core to classify motion data based on known patterns to enhance activity tracking in smartphones and wearables. Relieving the ...

Each group of machine learning algorithms has its own dedicated metrics. In the case of Anomaly Detection, we distinguish two metrics that are accessible in ML.NET: AUC - ROC curve and Detection ...