ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...

iRhythm (Nasdaq: IRTC) + today announced findings from a study of its Zio long-term continuous monitoring (LTCM) service. Outcomes from the Oxford University-led active monitoring for atrial ...

This project is designed to identify unusual patterns and potential faults in time-series data (e.g., server metrics, sensor readings, financial data). It goes beyond simple anomaly scoring by: The ...

A comprehensive Python-based machine learning solution for detecting anomalies in multivariate time series data from industrial IoT sensors. This solution identifies abnormal behavior patterns and ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The natural gas pipeline network has a complex topology with variable flow directions, ...

Introduction: Recent advances in artificial intelligence have created opportunities for medical anomaly detection through multimodal learning frameworks. However, traditional systems struggle to ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...

Modern industries increasingly rely on multi-sensor technologies to acquire complex, high-dimensional data streams, enabling advanced monitoring and control systems. One critical application is online ...

Remote visible-shortwave infrared (VSWIR) imaging spectrometers such as Earth surface Mineral dust source InvesTigation (EMIT) are enabling a new area of quantitative Earth Science by collecting ...