基于流程,事件驱动,可拓展,响应式,轻量级的规则引擎。

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.

An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in IEEE Internet of Things Magazine.

Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems" published in IEEE Transactions on Industrial Informatics.

Tools and libraries to start working with IoT Data Analytics

Traffic Speed Prediction / Interpolation (1st place submission @ HKUST MSc in Big Data Technology in-class Kaggle Competition)

Complete data pipeline of IoT data to get the actionable insights with graphs and visualization

Handy tool to save and query/format serial port data (e.g. into CSV)

A service designed to analyze and assess the quality of high frequency data collected from Industrial Internet of Things (IIoT) sensors, efficiently.## Dependencies This app reads multiple sensor readings that monitor a machine from LeanXcale database supporting energy efficient and incremental analytics.