t6 Features
Supervised Machine Learning (SML)
Supervised Machine Learning (SML) is a widely used technique in machine learning, and t6 IoT plays a pivotal role in its implementation. With t6 IoT, the process of building and training SML models involves harnessing labeled examples collected from Internet of Things (IoT) devices.
Exploratory Data Analysis
t6 comes with and handfull set of EDA apis. Today the implementation is still in progress but give the opportunity to begin Exploring timeseries datapoints from a specific flow.
Data Fusion
Sensor Fusion is the process of merging multiple values together. Data Fusion on t6 allows to combine multiple measures from several Flows (Tracks) onto another Flow (Primary). This "Fusion" will be made according to an algorithm defined directly on the Primary Flow. Data Fusion is working after the preprocessor engine is transforming the value. And after the Fusion, the value can optionaly be saved to the Primary Flow before it goes to the Decision Rule engine.
Data-annotation
t6 is focused on timeseries, Data-annotation process is classifying Datapoints from Flows using categories. Annotations and Categories are going to be used in the Exploratory Data Analysis process.