… and (2) generic devices, which can be adapted (“trained”) for analysis of various application
… Adaptation is usually performed by calibrating the sensor system with known samples and …

… and health management of equipment. The fusion of multiple sensors data could improve the
… Wu, “A robust approach of multi-sensor fusion for fault diagnosis using convolution neural …

… Predictions of single-dimensional time series input come from … In this paper we propose a
combination of adaptive online … can be executed within a single embedded device, making use …

… a series of tensor based data fusion methods for CPSS data. … data fusion frameworks and
propose a comprehensive data … space, the sensing devices are physical sensors. Compared …

… of wearable sensors managed by a coordinator device. In … BSNs, including different sensor
fusion methods, to exploit … Specifically, it is a real-time adaptive peak detector algorithm …

… on the integration of sensor fusion techniques, the facilitation of real-time processing via
edge … These instruments are pivotal for the AV's recognition and analysis of its surroundings, …

… sensor network gateways or smart devices. In what follows, we present our recent research
on designing methods and apparatus for distributed sensor data … , runtime adaptation or data …

… data up-sampling/generation techniques, synthetic minority oversampling technique (SMOTE)
[11] and Adaptive … data set, examples of the time series vibration of the the synthetic …

… Sensor fusion, an essential technique in structural health … Also, time series forecasting
models like AutoRegressive … enables adaptation to new data domains, increasing the method’s …

… the information acquired from multiple sources, sensors, databases, and direct information
… multi-sensor/data fusion area will find this book to be a valuable tool for design and analysis, …